diff --git a/Hedging with Real Estate/New_Upgrade_Bengaluru_House_Price_Predition/GradientBoostingRegressor.pkl b/Hedging with Real Estate/New_Upgrade_Bengaluru_House_Price_Predition/GradientBoostingRegressor.pkl new file mode 100644 index 00000000..6ce6ae82 Binary files /dev/null and b/Hedging with Real Estate/New_Upgrade_Bengaluru_House_Price_Predition/GradientBoostingRegressor.pkl differ diff --git a/Hedging with Real Estate/New_Upgrade_Bengaluru_House_Price_Predition/MoreModels.ipynb b/Hedging with Real Estate/New_Upgrade_Bengaluru_House_Price_Predition/MoreModels.ipynb new file mode 100644 index 00000000..29964f9f --- /dev/null +++ b/Hedging with Real Estate/New_Upgrade_Bengaluru_House_Price_Predition/MoreModels.ipynb @@ -0,0 +1,8630 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.pipeline import Pipeline\n", + "import pickle\n", + "import numpy as np\n", + "\n", + "# Scraping the data preprocessing pipeline from the existing Pipeline\n", + "with open('PIPELINE.pkl' , 'rb') as file:\n", + " pipeline = pickle.load(file)\n", + "with open('dataframe.pkl' , 'rb') as file:\n", + " data = pickle.load(file)\n", + "\n", + "data_pipeline = Pipeline(pipeline.steps[:-1])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
Pipeline(steps=[('step1',\n",
+       "                 ColumnTransformer(remainder='passthrough',\n",
+       "                                   transformers=[('col_tnf',\n",
+       "                                                  OneHotEncoder(drop='first',\n",
+       "                                                                sparse_output=False),\n",
+       "                                                  [0, 2])])),\n",
+       "                ('step2', StandardScaler())])
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" + ], + "text/plain": [ + "Pipeline(steps=[('step1',\n", + " ColumnTransformer(remainder='passthrough',\n", + " transformers=[('col_tnf',\n", + " OneHotEncoder(drop='first',\n", + " sparse_output=False),\n", + " [0, 2])])),\n", + " ('step2', StandardScaler())])" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data_pipeline" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Index: 7651 entries, 0 to 10664\n", + "Data columns (total 7 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 area_type 7651 non-null object \n", + " 1 availability 7651 non-null int64 \n", + " 2 location 7651 non-null object \n", + " 3 total_sqft 7651 non-null float64\n", + " 4 bath 7651 non-null float64\n", + " 5 price 7651 non-null float64\n", + " 6 bhk 7651 non-null int32 \n", + "dtypes: float64(3), int32(1), int64(1), object(2)\n", + "memory usage: 448.3+ KB\n" + ] + } + ], + "source": [ + "data.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "X = data.drop(columns = ['price'])\n", + "Y = data['price']" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.ensemble import GradientBoostingRegressor , AdaBoostRegressor , StackingRegressor\n", + "from sklearn.metrics import mean_absolute_error\n", + "from sklearn.model_selection import train_test_split , GridSearchCV , RandomizedSearchCV\n", + "\n", + "x_train , x_test , y_train , y_test = train_test_split(X , Y , shuffle = True , test_size = 0.2)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Fitting 5 folds for each of 1176 candidates, totalling 5880 fits\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-47.027 total time= 0.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-47.426 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-48.581 total time= 0.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-49.476 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-51.104 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-47.331 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-47.979 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-49.854 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-48.490 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-47.679 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-48.269 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-50.282 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-49.113 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-47.874 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-48.998 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-50.646 total time= 0.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-47.737 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-47.932 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-48.804 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-46.554 total time= 0.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-47.384 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-51.388 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-47.792 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-48.987 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-47.376 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-47.600 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-50.936 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-48.515 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-48.145 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-47.335 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-47.629 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-49.033 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-51.758 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-47.643 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-46.991 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-43.134 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-44.723 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-47.921 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-45.516 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-43.048 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-45.768 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-43.109 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-48.420 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-46.118 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-44.608 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-45.248 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-46.878 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-45.033 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-45.867 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-45.036 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-43.724 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-46.721 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-48.213 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-44.819 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-44.943 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-46.269 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-44.929 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-48.054 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-46.757 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-44.384 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-44.637 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-45.367 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-43.408 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-45.974 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-45.522 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-44.389 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-44.358 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-47.715 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-45.476 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-44.775 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-42.292 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-40.214 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-43.914 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-42.545 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-42.712 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-42.079 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-43.719 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-44.275 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-40.960 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-43.431 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-43.453 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-44.939 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-43.028 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-43.192 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-43.354 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-43.500 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-45.802 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-42.777 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-41.519 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-41.497 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-41.530 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-43.517 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-43.521 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-42.250 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-45.237 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-42.514 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-44.287 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-43.913 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-43.856 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-43.117 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-42.329 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-43.407 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-42.672 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-44.286 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-42.309 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-38.506 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-39.499 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-41.835 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-40.497 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-42.928 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-40.710 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-40.324 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-42.019 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-40.445 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-39.040 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-39.290 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-39.584 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-41.582 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-39.474 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-40.175 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-39.998 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-39.135 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-42.849 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-39.986 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-38.788 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-37.408 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-41.330 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-42.653 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-41.051 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-37.679 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-38.798 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-40.407 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-39.850 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-41.750 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-41.049 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-42.316 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-40.928 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-46.847 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-44.840 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-47.150 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-46.159 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-45.009 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-45.310 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-47.040 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-42.413 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-41.787 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-48.243 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-45.953 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-38.908 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-44.477 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-45.223 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-45.954 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-48.669 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-47.135 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-46.065 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-44.547 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-47.838 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-49.400 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-45.807 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-44.746 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-45.970 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-46.234 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-48.149 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-45.446 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-45.300 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-43.881 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-46.597 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-48.193 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-45.715 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-45.672 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-47.385 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-43.958 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-47.410 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-45.077 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-45.287 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-40.306 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-42.056 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-40.712 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-40.468 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-42.520 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-39.983 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-40.622 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-43.673 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-41.245 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-41.127 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-40.778 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-40.608 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-41.602 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-42.659 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-41.863 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-40.389 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-41.722 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-44.767 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-41.092 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-40.953 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-41.823 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-41.055 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-42.963 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-39.943 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-40.593 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-39.454 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-40.509 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-41.306 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-40.557 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-42.891 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-39.212 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-40.891 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-43.363 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-40.398 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-39.566 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-37.665 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-36.710 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-39.068 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-39.139 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-36.586 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-38.428 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-37.951 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-39.686 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-36.351 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-35.356 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-36.285 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-36.896 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-39.296 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-37.909 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-35.915 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-35.890 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-36.770 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-37.648 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-39.054 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-36.641 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-35.612 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-39.401 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-36.963 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-35.993 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-36.519 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-38.676 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-37.474 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-38.508 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-37.521 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-36.552 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-36.746 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-39.044 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-40.368 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-36.409 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-36.942 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-34.232 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-35.038 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-36.936 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-35.160 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-33.710 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-33.990 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-37.210 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-35.313 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-33.978 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-33.894 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-32.286 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-35.236 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-37.003 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-34.544 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-35.178 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-35.362 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-32.768 total time= 0.9s[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-35.979 total time= 0.7s\n", + "\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-34.140 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-33.816 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-33.129 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-35.616 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-35.089 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-32.960 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-35.670 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-32.661 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-34.863 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-37.140 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-33.833 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-33.867 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-44.322 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-48.501 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-33.845 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-34.881 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-35.030 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-34.708 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-49.634 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-47.455 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-46.792 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-45.531 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-46.271 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-46.361 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-47.122 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-49.186 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-32.611 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-46.190 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-47.383 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-49.765 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-47.245 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-45.177 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-46.723 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-44.827 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-49.081 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-46.868 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-46.426 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-47.829 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-46.138 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-46.484 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-46.128 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-50.297 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-45.842 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-47.458 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-47.525 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-48.942 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-46.366 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-46.638 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-44.982 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-46.493 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-46.770 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-45.657 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-40.476 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-43.007 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-41.755 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-43.071 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-40.510 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-42.057 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-42.869 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-44.877 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-42.496 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-42.147 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-42.619 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-41.944 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-41.782 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-44.221 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-41.271 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-40.603 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-43.450 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-43.585 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-41.485 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-41.687 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-43.335 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-43.037 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-42.673 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-42.041 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-40.449 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-43.580 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-40.757 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-41.732 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-44.234 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-41.869 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-41.928 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-41.979 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-42.186 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-42.609 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-42.279 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-39.534 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-37.932 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-40.305 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-37.917 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-38.107 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-39.196 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-36.822 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-40.073 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-37.238 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-37.387 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-36.900 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-39.445 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-40.411 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-37.669 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-39.009 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-37.604 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-39.931 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-40.942 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-37.773 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-36.229 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-38.277 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-38.693 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-38.659 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-39.943 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-37.080 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-38.130 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-39.969 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-39.417 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-37.414 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-39.068 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-37.225 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-40.808 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-39.945 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-40.314 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-36.419 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-34.234 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-35.145 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-36.084 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-34.258 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-37.056 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-33.760 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-38.561 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-36.584 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-35.347 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-34.176 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-34.180 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-37.165 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-36.502 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-36.969 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-35.393 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-33.367 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-37.975 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-37.018 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-36.870 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-33.863 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-34.438 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-35.577 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-36.950 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-35.303 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-33.213 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-34.773 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-36.620 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-37.963 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-35.876 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-33.533 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-42.963 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-33.421 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-43.913 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-36.273 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-46.092 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-37.844 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-43.138 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-42.673 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-36.592 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-43.532 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-42.327 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-33.660 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-44.914 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-43.511 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-42.416 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-42.718 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-43.586 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-45.313 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-43.283 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-42.691 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-41.527 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-44.961 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-43.771 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-43.080 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-42.672 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-41.814 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-44.318 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-42.414 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-44.726 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-44.583 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-45.328 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-41.903 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-43.601 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-42.404 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-41.772 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-44.408 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-42.675 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-42.996 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-46.357 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-42.856 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-36.142 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-37.431 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-37.219 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-37.578 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-35.828 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-36.649 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-37.174 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-39.400 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-37.908 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-36.122 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-35.709 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-36.821 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-37.553 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-36.878 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-36.304 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-36.599 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-38.422 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-38.319 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-36.357 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-37.378 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-37.710 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-35.335 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-38.362 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-36.285 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-36.897 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-35.977 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-35.877 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-39.940 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-36.373 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-36.631 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-37.274 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-37.572 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-40.333 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-38.052 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-35.349 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-31.944 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-33.362 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-35.106 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-33.669 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-32.294 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-34.193 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-32.493 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-32.636 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-32.707 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-32.856 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-31.443 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-33.730 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-34.492 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-32.926 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-32.660 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-31.598 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-34.438 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-34.174 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-33.580 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-32.929 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-32.687 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-33.222 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-32.979 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-32.810 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-34.367 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-33.781 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-32.982 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-34.350 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-33.270 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-32.254 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-31.623 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-33.590 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-34.363 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-32.740 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-32.529 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-29.618 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-30.224 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-29.472 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-31.753 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-30.392 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-29.854 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-30.014 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-31.227 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-31.638 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-29.784 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-31.424 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-29.970 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-30.541 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-29.245 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-30.502 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-30.597 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-29.819 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-31.776 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-30.212 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-29.389 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-30.567 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-30.410 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-31.776 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-30.308 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-29.346 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-28.891 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-30.010 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-31.717 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-29.964 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-44.189 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-29.303 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-45.218 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-46.359 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-29.020 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-30.435 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-44.008 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-44.141 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-43.251 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-30.029 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-31.464 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-45.970 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-46.475 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-44.127 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-46.000 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-43.115 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-45.779 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-44.712 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-28.805 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-44.311 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-42.828 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-44.719 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-48.539 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-43.742 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-43.080 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-45.110 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-43.780 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-45.588 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-46.554 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-44.492 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-42.435 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-45.036 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-43.010 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-45.991 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-43.820 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-43.454 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-42.353 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-44.010 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-46.561 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-45.113 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-42.752 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-37.893 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-39.008 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-40.721 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-38.787 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-37.742 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-40.922 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-38.152 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-41.009 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-38.513 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-37.474 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-38.091 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-35.885 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-39.231 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-39.037 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-40.809 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-37.891 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-38.068 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-38.544 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-40.744 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-37.816 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-39.993 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-37.387 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-39.029 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-39.845 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-37.468 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-37.009 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-39.488 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-42.164 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-36.965 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-39.162 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-37.895 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-38.795 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-40.118 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-39.623 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-37.451 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-33.481 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-34.605 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-35.946 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-33.280 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-35.195 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-33.919 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-33.790 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-34.286 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-33.247 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-35.803 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-33.694 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-33.717 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-36.361 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-35.020 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-33.305 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-33.926 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-33.145 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-34.856 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-34.136 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-33.263 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-33.654 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-34.724 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-37.513 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-36.040 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-33.297 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-33.122 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-34.531 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-35.536 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-35.004 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-33.648 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-33.492 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-35.159 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-37.313 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-35.003 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-30.008 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-32.808 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-32.932 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-32.147 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-31.285 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-33.168 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-31.394 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-31.625 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-30.695 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-30.350 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-31.516 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-30.425 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-31.795 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-32.907 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-30.400 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-30.900 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-30.673 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-31.249 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-32.935 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-30.836 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-31.035 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-31.545 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-32.930 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-31.865 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-31.320 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-29.392 total time= 1.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-30.211 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-31.701 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-32.141 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-39.613 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-29.815 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-31.324 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-30.552 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-40.918 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-32.291 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-30.261 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-30.962 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-32.084 total time= 1.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-41.530 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-40.805 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-40.487 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-41.437 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-38.917 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-42.800 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-40.716 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-39.913 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-40.274 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-41.048 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-42.138 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-41.080 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-40.035 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-39.566 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-42.729 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-41.458 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-41.692 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-39.436 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-40.158 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-42.237 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-41.116 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-40.073 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-40.132 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-39.814 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-40.595 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-40.558 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-43.808 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-40.732 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-40.340 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-39.859 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-41.432 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-41.818 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-39.611 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-32.364 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-34.117 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-32.913 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-35.230 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-33.610 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-34.005 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-32.792 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-35.979 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-33.889 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-33.723 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-31.545 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-33.455 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-34.985 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-33.669 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-32.928 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-31.738 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-33.824 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-35.677 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-33.919 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-33.022 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-32.099 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-35.316 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-33.812 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-33.418 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-32.629 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-32.287 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-33.934 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-34.775 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-33.349 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-33.889 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-32.804 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-33.430 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-35.382 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-32.736 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-34.092 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-28.056 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-30.119 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-29.426 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-30.634 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-28.215 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-28.759 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-29.789 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-31.209 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-29.233 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-28.689 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-27.815 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-30.018 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-30.494 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-28.822 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-29.136 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-28.061 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-29.902 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-30.299 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-29.542 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-28.649 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-28.637 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-30.875 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-29.649 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-29.107 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-28.530 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-28.257 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-28.927 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-30.092 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-29.546 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-28.452 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-28.135 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-29.873 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-30.019 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-29.704 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-26.746 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-25.569 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-27.815 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-28.345 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-26.459 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-25.723 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-25.416 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-26.181 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-26.307 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-26.960 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-25.637 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-25.466 total time= 1.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-26.196 total time= 1.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-27.876 total time= 1.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-26.824 total time= 1.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-25.290 total time= 1.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-26.085 total time= 1.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-26.339 total time= 1.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-27.596 total time= 1.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-26.672 total time= 1.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-25.507 total time= 1.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-25.123 total time= 1.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-26.379 total time= 1.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-27.516 total time= 1.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-25.752 total time= 1.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-26.133 total time= 1.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-26.101 total time= 1.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-25.338 total time= 1.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-27.278 total time= 1.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-26.362 total time= 1.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-44.431 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-43.793 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-46.142 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-45.680 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-25.994 total time= 1.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-43.195 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-44.094 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-27.036 total time= 1.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-44.015 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-26.691 total time= 1.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-46.589 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-25.254 total time= 1.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-45.004 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-40.542 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-47.164 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-44.350 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-42.804 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-45.703 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-42.777 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-43.292 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-44.018 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-46.408 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-44.501 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-26.204 total time= 1.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-41.795 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-44.063 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-43.669 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-46.990 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-42.826 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-41.826 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-42.722 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.01, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-25.999 total time= 1.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-42.839 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-47.379 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-46.598 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-42.880 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-43.777 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-45.094 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-45.187 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-43.380 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-42.592 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-39.150 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-39.124 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-37.620 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-37.032 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-38.383 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-37.932 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-40.344 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-40.920 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-40.019 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-39.215 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-39.470 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-40.643 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-36.188 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-38.400 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-40.097 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-39.815 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-40.373 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-41.387 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-41.672 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-33.638 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-38.247 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-37.299 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-36.706 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-40.332 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-38.595 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-39.439 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-38.081 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-37.075 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-40.467 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-39.964 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-36.220 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-35.670 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-37.310 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-36.581 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-38.555 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-32.907 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-35.480 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-35.194 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-37.800 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-35.461 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-34.828 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-36.248 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-35.729 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-35.407 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-33.014 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-34.106 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-33.984 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-37.368 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-33.969 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-33.567 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-32.587 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-37.216 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-34.783 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-34.691 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-34.378 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-35.530 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-35.137 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-34.964 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-37.327 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-35.220 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-34.155 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-32.888 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-35.161 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-33.780 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-37.926 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-34.690 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-35.578 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-35.113 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-35.988 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-32.922 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-33.978 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-32.247 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-30.279 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-31.891 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-31.293 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-30.619 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-31.905 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-31.820 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-31.733 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-30.919 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-30.159 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-30.334 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-32.864 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-31.316 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-29.796 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-29.659 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-31.143 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-33.761 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-33.881 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-30.461 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-31.198 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-31.110 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-33.692 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-31.117 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-31.752 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-30.159 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-31.346 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-32.453 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-29.774 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-31.758 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-36.601 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-31.152 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-40.566 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-40.353 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-31.816 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-40.929 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-39.442 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-40.320 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-30.178 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-32.860 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-38.076 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-28.908 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-40.512 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-42.253 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-40.885 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-39.678 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-37.750 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-41.757 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-37.032 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-40.464 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-40.275 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-37.281 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-41.714 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-40.414 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-39.920 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-37.372 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-36.923 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-37.850 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-38.019 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-37.959 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-38.570 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-41.279 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-41.623 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-37.681 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-39.458 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-37.322 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-42.423 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-39.279 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-39.886 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-39.860 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-31.646 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-33.905 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-31.744 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-35.011 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-30.315 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-31.207 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-34.352 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-32.549 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-32.440 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-31.135 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-33.303 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-31.832 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-33.378 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-32.416 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-31.421 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-30.456 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-30.676 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-34.311 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-32.952 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-30.843 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-31.361 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-32.708 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-33.551 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-32.051 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-31.829 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-31.606 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-34.756 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-34.434 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-32.187 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-33.425 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-31.085 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-33.721 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-33.757 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-30.675 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-31.246 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-29.613 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-29.671 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-28.728 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-32.517 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-28.551 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-28.930 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-29.142 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-29.544 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-28.680 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-27.809 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-28.534 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-29.064 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-28.878 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-29.363 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-28.170 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-27.785 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-30.612 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-29.579 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-29.399 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-27.580 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-30.463 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-28.033 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-30.719 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-28.955 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-29.455 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-27.944 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-28.340 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-28.574 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-30.208 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-29.227 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-28.232 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-28.293 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-29.041 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-31.380 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-27.426 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-27.502 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-26.716 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-27.854 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-28.449 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-27.705 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-27.748 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-27.081 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-29.059 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-26.755 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-26.931 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-27.227 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-26.727 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-27.896 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-27.667 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-27.119 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-26.840 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-27.148 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-27.359 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-27.404 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-26.428 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-26.456 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-27.403 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-27.572 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-26.899 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-27.339 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-26.371 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-27.624 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-27.779 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-27.556 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-26.810 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-39.777 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-42.150 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-41.564 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-26.551 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-39.267 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-27.451 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-27.371 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-41.730 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-27.601 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-38.715 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-26.985 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-40.579 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-42.767 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-39.710 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-38.850 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-36.309 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-38.100 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-42.833 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-37.973 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-40.092 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-40.128 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-39.983 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-45.274 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-41.649 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-40.544 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-37.806 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-42.744 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-39.841 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-38.278 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-42.205 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-38.640 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-40.585 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-41.598 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-40.874 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-39.807 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-38.564 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-42.140 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-41.045 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-39.071 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-39.085 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-31.983 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-33.029 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-34.965 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-34.899 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-31.675 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-33.119 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-33.463 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-36.914 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-33.624 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-33.159 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-32.208 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-34.520 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-33.281 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-33.571 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-31.447 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-32.130 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-33.376 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-34.420 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-33.793 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-32.234 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-33.650 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-35.121 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-35.169 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-31.193 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-31.779 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-32.795 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-36.155 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-33.073 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-34.440 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-33.614 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-33.073 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-37.474 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-32.850 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-32.146 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-34.599 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-29.780 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-29.009 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-31.133 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-29.907 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-30.699 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-27.888 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-29.654 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-30.982 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-28.115 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-28.343 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-28.363 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-29.247 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-30.054 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-28.503 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-28.711 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-29.609 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-29.940 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-30.588 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-31.889 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-28.060 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-29.175 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-30.039 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-30.774 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-28.831 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-28.242 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-28.134 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-29.487 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-30.371 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-31.083 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-29.711 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-27.364 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-29.510 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-29.469 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-30.918 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-27.741 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-27.114 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-27.282 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-28.152 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-25.870 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-27.627 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-27.588 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-25.982 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-27.676 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-26.907 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-26.380 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-26.651 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-27.511 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-28.892 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-27.685 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-25.797 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-26.480 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-26.889 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-27.713 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-27.758 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-26.039 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-25.689 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-27.387 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-27.653 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-26.511 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-26.616 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-27.496 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-26.860 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-28.397 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-28.323 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-33.764 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-26.954 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-27.142 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-36.745 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-27.978 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-27.026 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-34.439 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-36.387 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-34.021 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-33.378 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-26.642 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-34.296 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-36.183 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-35.349 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-36.499 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-27.468 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-32.827 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-35.779 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-37.462 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-34.814 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-34.647 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-36.959 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-34.925 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-34.477 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-33.416 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-36.530 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-33.612 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-36.423 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-36.041 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-36.833 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-34.825 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-34.584 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-35.170 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-37.789 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-34.400 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-34.601 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-34.459 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-33.577 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-34.720 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-35.918 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-34.407 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-27.832 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-27.982 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-28.658 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-28.357 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-29.594 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-28.204 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-27.473 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-29.950 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-28.160 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-27.166 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-31.023 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-28.121 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-27.449 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-27.219 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-27.699 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-27.335 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-28.793 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-28.800 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-28.072 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-27.936 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-28.652 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-28.514 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-28.614 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-27.755 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-28.240 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-27.320 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-27.724 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-30.155 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-28.491 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-28.281 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-27.411 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-27.341 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-28.331 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-28.469 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-26.062 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-28.514 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-26.419 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-26.660 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-25.314 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-24.993 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-24.557 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-25.129 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-26.249 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-25.122 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-24.544 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-25.124 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-26.074 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-25.454 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-25.332 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-25.104 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-24.538 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-24.787 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-25.965 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-24.477 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-24.324 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-25.069 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-24.595 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-25.243 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-25.759 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-24.977 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-25.034 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-25.563 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-26.202 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-24.446 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-25.212 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-24.280 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-25.253 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-26.065 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-23.263 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-25.556 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-25.099 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-23.970 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-23.431 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-24.382 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-24.759 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-23.216 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-23.992 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-23.657 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-25.034 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-23.800 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-23.061 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-24.939 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-23.460 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-23.504 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-23.763 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-23.686 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-23.999 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-24.347 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-24.537 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-23.559 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-23.250 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-23.665 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-24.395 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-24.146 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-23.416 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-23.595 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-23.166 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-24.972 total time= 1.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-23.565 total time= 1.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-23.120 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-36.298 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-35.950 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-23.435 total time= 1.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-37.945 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-23.499 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-23.328 total time= 1.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-23.936 total time= 1.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-36.432 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-36.230 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-34.878 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-35.582 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-23.176 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-38.880 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-38.391 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-36.166 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-36.384 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-34.597 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-36.682 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-35.858 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-37.145 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-35.461 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-37.143 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-37.432 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-35.544 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-36.929 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-35.673 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-36.295 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-39.358 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-38.321 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-36.591 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-34.597 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-40.634 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-36.423 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-37.272 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-37.400 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-36.792 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-40.564 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-38.100 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-35.767 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-37.316 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-27.072 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-31.070 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-28.795 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-27.456 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-29.382 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-28.176 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-29.366 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-29.653 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-29.081 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-27.351 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-28.416 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-29.304 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-30.134 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-29.150 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-28.106 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-28.612 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-30.741 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-29.385 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-28.563 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-28.283 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-27.752 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-29.223 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-27.975 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-29.646 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-28.811 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-28.827 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-29.088 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-28.862 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-29.782 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-29.018 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-28.352 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-29.077 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-29.368 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-28.699 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-29.027 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-25.068 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-25.146 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-26.689 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-25.343 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-24.081 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-24.600 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-25.312 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-26.885 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-25.917 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-25.932 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-24.880 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-25.370 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-26.295 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-25.797 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-25.064 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-24.572 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-26.361 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-26.128 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-23.602 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-25.159 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-24.569 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-25.281 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-26.735 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-24.992 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-25.524 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-23.972 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-25.525 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-25.908 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-25.686 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-24.691 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-25.399 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-25.016 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-26.722 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-26.191 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-22.971 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-25.418 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-23.618 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-25.088 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-23.226 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-23.148 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-23.439 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-23.365 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-24.515 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-23.176 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-23.666 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-23.113 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-23.426 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-23.549 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-24.130 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-23.365 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-23.058 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-22.851 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-23.800 total time= 1.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-22.677 total time= 1.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-23.448 total time= 1.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-22.772 total time= 1.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-23.204 total time= 1.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-24.508 total time= 1.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-22.511 total time= 1.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-22.917 total time= 1.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-22.887 total time= 1.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-23.481 total time= 1.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-23.133 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-23.194 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-24.742 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-31.850 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-29.871 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-32.345 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-22.706 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-24.143 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-24.047 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-30.717 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-30.916 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-30.053 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-31.687 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-22.366 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-32.845 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-31.852 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-31.839 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-23.113 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-30.518 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-30.894 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-32.197 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-29.966 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-31.328 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-30.425 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-31.076 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-32.199 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-32.158 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-29.803 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-29.438 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-31.740 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-30.541 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-31.215 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-31.226 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-30.344 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-31.700 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-32.245 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-30.933 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-29.632 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-30.019 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-31.938 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-31.440 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-30.657 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-30.965 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-23.899 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-25.551 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-24.858 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-24.661 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-23.472 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-23.568 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-24.988 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-25.001 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-24.442 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-23.757 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-23.641 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-25.101 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-24.423 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-25.294 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-23.996 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-24.327 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-23.583 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-25.834 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-23.561 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-24.613 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-23.457 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-24.575 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-25.866 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-24.021 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-24.371 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-22.922 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-24.524 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-25.152 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-24.263 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-24.331 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-23.890 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-25.972 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-24.292 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-24.126 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-22.751 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-23.920 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-21.010 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-21.562 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-22.786 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-22.741 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-21.745 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-22.107 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-22.579 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-21.405 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-21.906 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-21.660 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-22.045 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-22.198 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-21.721 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-21.537 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-22.341 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-21.710 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-22.170 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-22.175 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-21.741 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-20.988 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-21.664 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-22.443 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-21.852 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-21.805 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-20.944 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-22.094 total time= 1.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-21.964 total time= 1.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-21.400 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-21.582 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-21.142 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-22.191 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-21.578 total time= 1.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-21.162 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-21.011 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-21.153 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-20.766 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-21.243 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-20.771 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-21.068 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-20.612 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-20.738 total time= 1.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-21.127 total time= 1.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-20.907 total time= 1.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-20.609 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-20.514 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-20.907 total time= 1.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-20.801 total time= 1.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-20.576 total time= 1.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-20.101 total time= 1.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-20.675 total time= 1.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-20.952 total time= 1.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-20.422 total time= 1.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-20.547 total time= 1.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-20.986 total time= 1.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-20.097 total time= 1.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-21.053 total time= 1.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-20.810 total time= 1.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-19.907 total time= 1.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-20.158 total time= 1.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-20.448 total time= 2.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-21.030 total time= 2.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-20.660 total time= 2.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-37.773 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-42.849 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-20.295 total time= 2.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-20.345 total time= 2.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-40.947 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-40.935 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-42.308 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-36.385 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-41.658 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-21.107 total time= 1.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-20.582 total time= 2.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-39.955 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-38.659 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-37.913 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-38.206 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-39.359 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-20.970 total time= 1.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-41.805 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-42.156 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-37.894 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-36.037 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-35.757 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-39.945 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-40.771 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-20.554 total time= 1.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-39.094 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-36.619 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-37.786 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-41.818 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-37.231 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.025, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-19.900 total time= 1.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-37.097 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-38.145 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-40.452 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-39.675 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-35.479 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-38.157 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-36.425 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-39.496 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-41.049 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-36.513 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-34.633 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-31.901 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-29.934 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-30.054 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-33.708 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-32.887 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-30.226 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-29.724 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-32.268 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-31.887 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-29.668 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-33.090 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-30.189 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-35.131 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-33.848 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-30.435 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-30.391 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-32.825 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-31.489 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-31.690 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-31.887 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-30.999 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-32.922 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-32.781 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-33.315 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-31.214 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-32.194 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-30.885 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-31.563 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-30.231 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-30.405 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-32.006 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-31.769 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-32.136 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-30.474 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-33.741 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-28.265 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-27.725 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-27.385 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-31.789 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-28.339 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-30.435 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-26.840 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-28.988 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-29.138 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-28.134 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-27.541 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-28.967 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-29.397 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-27.630 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-28.470 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-28.508 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-29.890 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-28.670 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-28.029 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-27.689 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-27.408 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-29.615 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-29.691 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-28.894 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-26.923 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-27.180 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-29.222 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-28.416 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-29.600 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-28.203 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-28.033 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-30.043 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-28.412 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-28.323 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-29.625 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-26.917 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-26.588 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-26.598 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-27.144 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-27.867 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-25.306 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-26.653 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-28.430 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-26.325 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-27.194 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-26.072 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-26.553 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-27.659 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-26.827 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-27.221 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-26.334 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-26.049 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-27.171 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-25.019 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-27.679 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-25.723 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-26.071 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-26.477 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-27.334 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-25.379 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-25.644 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-26.046 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-26.212 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-26.980 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-25.641 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-34.103 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-25.740 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-30.559 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-26.491 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-34.649 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-32.690 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-27.596 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-31.935 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-25.964 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-31.057 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-25.423 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-33.678 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-34.229 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-33.696 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-29.608 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-32.250 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-32.522 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-35.958 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-31.438 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-34.483 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-32.706 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-35.260 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-34.616 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-30.013 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-31.653 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-31.066 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-34.339 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-31.289 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-31.182 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-32.685 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-30.723 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-31.678 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-31.876 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-32.907 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-32.464 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-35.192 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-30.561 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-31.010 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-31.420 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-31.492 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-28.328 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-26.623 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-27.193 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-27.827 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-26.652 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-27.385 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-27.949 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-28.101 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-26.238 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-26.364 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-27.109 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-27.440 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-27.359 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-26.929 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-26.899 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-26.315 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-27.340 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-27.999 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-27.240 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-25.866 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-26.540 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-26.274 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-28.867 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-24.905 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-26.647 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-26.675 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-26.910 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-27.276 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-27.454 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-26.175 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-25.740 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-27.417 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-28.168 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-27.035 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-26.007 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-24.407 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-24.704 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-25.480 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-24.196 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-23.949 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-25.300 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-24.877 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-25.127 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-25.302 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-25.094 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-25.710 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-25.553 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-24.097 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-25.349 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-25.240 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-23.771 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-25.390 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-25.143 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-25.515 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-25.113 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-24.906 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-25.168 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-24.986 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-25.213 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-24.175 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-24.604 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-25.069 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-24.576 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-25.085 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-24.758 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-25.347 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-25.175 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-24.521 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-24.882 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-24.950 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-23.605 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-22.863 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-24.877 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-22.857 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-24.615 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-24.400 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-23.813 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-23.866 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-24.287 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-23.857 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-22.784 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-23.353 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-24.386 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-24.216 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-24.869 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-23.395 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-23.424 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-24.427 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-23.407 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-24.470 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-23.245 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-24.006 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-24.058 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-23.176 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-23.343 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-24.440 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-23.430 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-24.556 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-23.956 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-23.406 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-31.189 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-23.725 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-36.049 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-35.569 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-33.611 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-36.596 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-23.664 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-36.257 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-32.162 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-34.342 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-24.395 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-24.230 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-32.943 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-33.185 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-33.846 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-23.707 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-31.776 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-34.502 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-35.328 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-31.435 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-31.965 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-33.430 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-32.921 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-33.397 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-30.376 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-33.604 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-33.510 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-36.824 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-35.727 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-32.740 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-32.823 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-31.534 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-35.266 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-33.447 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-34.840 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-30.792 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-33.147 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-34.686 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-33.041 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-33.390 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-25.941 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-26.782 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-28.431 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-27.401 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-28.172 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-25.483 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-28.542 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-25.634 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-28.026 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-28.797 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-27.250 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-26.520 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-27.500 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-27.316 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-26.750 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-27.876 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-28.104 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-28.499 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-26.555 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-28.021 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-27.060 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-30.176 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-26.219 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-27.558 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-26.430 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-25.644 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-29.154 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-27.247 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-28.322 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-26.112 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-27.353 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-26.040 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-27.987 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-27.274 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-27.021 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-23.784 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-24.519 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-24.728 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-25.751 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-25.182 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-24.635 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-25.064 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-24.562 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-25.127 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-23.711 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-25.294 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-26.002 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-23.394 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-24.280 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-24.708 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-23.900 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-25.018 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-25.780 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-22.975 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-25.345 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-24.481 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-24.981 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-25.464 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-23.780 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-24.730 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-25.365 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-23.732 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-24.652 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-24.783 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-24.628 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-25.527 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-24.718 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-23.983 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-23.729 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-23.393 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-23.250 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-23.102 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-24.402 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-22.999 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-22.547 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-22.208 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-23.133 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-23.192 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-23.087 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-22.271 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-23.872 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-23.221 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-22.817 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-23.208 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-22.802 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-22.280 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-22.931 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-23.033 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-22.936 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-22.768 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-23.083 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-22.899 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-23.917 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-22.935 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-22.886 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-22.090 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-22.347 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-23.863 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-21.962 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-22.062 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-30.303 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-23.187 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-28.185 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-22.606 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-24.021 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-27.227 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-29.379 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-26.687 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-22.662 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-22.903 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-27.036 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-28.200 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-29.706 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-30.618 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-26.477 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-28.048 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-30.241 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-27.935 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-28.768 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-27.466 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-27.984 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-27.127 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-28.162 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-27.397 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-26.916 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-25.925 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-27.315 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-28.251 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-26.334 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-29.970 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-27.538 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-27.503 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-28.194 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-29.072 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-27.117 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-27.822 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-30.605 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-28.258 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-28.357 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-27.299 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-23.593 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-23.582 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-25.197 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-24.710 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-23.541 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-23.359 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-24.539 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-23.264 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-24.415 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-23.661 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-23.945 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-23.675 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-23.750 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-23.734 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-23.480 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-24.012 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-23.615 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-22.917 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-23.871 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-23.685 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-23.215 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-24.072 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-24.346 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-24.034 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-24.089 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-23.752 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-23.490 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-24.377 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-24.745 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-23.690 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-24.129 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-23.554 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-23.907 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-24.127 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-23.859 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-21.706 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-22.199 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-23.498 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-21.466 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-22.386 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-21.571 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-21.980 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-22.777 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-22.166 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-23.148 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-22.144 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-22.907 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-22.561 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-22.270 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-21.420 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-21.794 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-21.574 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-22.657 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-21.887 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-22.357 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-22.071 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-22.149 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-21.407 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-23.371 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-21.674 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-21.117 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-22.530 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-22.964 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-22.079 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-21.998 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-21.564 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-21.282 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-22.267 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-21.827 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-22.820 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-20.844 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-20.800 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-21.665 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-21.171 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-21.163 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-20.900 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-20.874 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-21.031 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-20.793 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-21.106 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-20.632 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-21.071 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-21.515 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-19.771 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-21.499 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-20.573 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-21.388 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-20.909 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-20.101 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-21.170 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-20.528 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-20.661 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-21.061 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-20.932 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-21.756 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-20.364 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-21.180 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-20.505 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-21.054 total time= 1.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-21.503 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-21.799 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-21.431 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-28.855 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-20.727 total time= 1.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-27.057 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-29.854 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-28.666 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-28.217 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-27.778 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-33.048 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-28.368 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-20.844 total time= 1.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-28.704 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-26.719 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-30.417 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-26.982 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-20.858 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-28.979 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-29.100 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-28.990 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-26.610 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-29.305 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-27.597 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-28.781 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-30.799 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-28.436 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-31.183 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-28.207 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-28.240 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-26.696 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-27.908 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-27.971 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-29.964 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-27.413 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-28.595 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-27.667 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-29.764 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-29.058 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-29.614 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-26.626 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-23.212 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-23.712 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-24.383 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-23.845 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-23.028 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-22.670 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-23.420 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-23.907 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-24.978 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-23.077 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-22.502 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-23.092 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-23.240 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-22.431 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-23.739 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-22.972 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-23.745 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-23.077 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-22.530 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-24.186 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-23.656 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-24.723 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-23.344 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-22.726 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-24.199 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-23.444 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-22.648 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-23.965 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-22.588 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-22.175 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-22.983 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-22.658 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-23.623 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-23.049 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-21.998 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-21.723 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-21.854 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-21.854 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-21.874 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-21.852 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-21.035 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-21.710 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-21.298 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-21.532 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-21.286 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-21.360 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-21.171 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-21.414 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-20.946 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-21.396 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-21.717 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-21.499 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-22.406 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-20.793 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-21.208 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-21.275 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-21.152 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-21.077 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-21.074 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-21.406 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-19.709 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-21.548 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-21.069 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-20.937 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-20.868 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-20.652 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-21.632 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-21.158 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-20.738 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-20.785 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-19.586 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-20.151 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-20.311 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-19.861 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-19.837 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-20.797 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-20.951 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-19.608 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-19.218 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-20.342 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-20.260 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-20.547 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-20.719 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-19.563 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-19.761 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-19.813 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-19.850 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-20.093 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-19.458 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-20.240 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-20.090 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-19.985 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-20.157 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-19.732 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-19.872 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-18.976 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-19.792 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-19.241 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-20.250 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-23.303 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-25.236 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-20.683 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-19.872 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-19.513 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-20.774 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-25.793 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-20.133 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-24.641 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-24.333 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-20.283 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-25.225 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-24.423 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-25.106 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-23.958 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-23.284 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-23.179 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-24.025 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-25.050 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-24.564 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-23.675 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-25.743 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-24.524 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-24.574 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-25.137 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-24.106 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-23.794 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-25.036 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-24.236 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-24.442 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-25.285 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-23.794 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-25.093 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-25.782 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-24.599 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-24.287 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-24.566 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-23.413 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-24.782 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-24.078 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-24.967 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-21.126 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-20.785 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-21.688 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-19.998 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-20.622 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-20.830 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-21.180 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-20.815 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-20.585 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-20.557 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-20.620 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-20.586 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-20.496 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-20.285 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-21.542 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-20.049 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-21.257 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-20.279 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-21.505 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-19.986 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-20.978 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-20.637 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-19.882 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-19.945 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-20.891 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-20.118 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-21.225 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-21.530 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-19.943 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-19.500 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-20.460 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-20.823 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-20.362 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-19.857 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-20.101 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-18.540 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-19.556 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-20.260 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-19.240 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-19.907 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-18.725 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-19.182 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-19.679 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-19.387 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-19.256 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-18.439 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-19.514 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-19.688 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-18.482 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-18.742 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-19.129 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-18.770 total time= 1.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-19.393 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-19.263 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-18.638 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-18.836 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-19.590 total time= 1.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-19.409 total time= 1.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-18.640 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-19.157 total time= 1.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-18.943 total time= 1.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-19.635 total time= 1.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-20.071 total time= 1.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-18.668 total time= 1.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-18.362 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-19.151 total time= 1.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-19.649 total time= 1.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-18.604 total time= 1.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-19.517 total time= 1.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-17.885 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-18.798 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-18.595 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-18.843 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-17.912 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-18.208 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-17.776 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-18.617 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-19.228 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-18.204 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-18.150 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-17.641 total time= 1.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-18.752 total time= 1.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-18.714 total time= 1.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-17.985 total time= 1.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-17.716 total time= 1.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-18.415 total time= 1.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-18.614 total time= 1.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-19.095 total time= 1.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-18.132 total time= 1.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-18.028 total time= 1.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-17.526 total time= 1.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-18.619 total time= 1.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-18.762 total time= 1.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-18.272 total time= 1.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-17.673 total time= 1.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-18.477 total time= 1.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-18.722 total time= 1.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-18.731 total time= 1.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-35.993 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-17.695 total time= 1.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-37.533 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-35.663 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-35.710 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-32.685 total time= 0.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-18.552 total time= 1.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-33.240 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-33.000 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-38.806 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-17.742 total time= 1.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-18.708 total time= 1.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-33.889 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-37.061 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-34.835 total time= 0.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-18.526 total time= 1.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-17.756 total time= 1.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-37.056 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-33.296 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-33.923 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-32.930 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-33.521 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-36.795 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-37.672 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-33.233 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.05, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-18.458 total time= 1.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-36.821 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-35.205 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-39.580 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-38.542 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-34.307 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-33.223 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-34.475 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-32.212 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-35.111 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-37.597 total time= 0.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-33.598 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-35.183 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-32.272 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-34.962 total time= 0.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-33.699 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-35.640 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-29.341 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-28.803 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-33.833 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-27.239 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-29.704 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-28.000 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-30.412 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-28.798 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-29.069 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-29.277 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-27.337 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-27.837 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-28.378 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-26.862 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-29.911 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-28.535 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-30.188 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-30.071 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-27.221 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-30.400 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-28.382 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-28.630 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-29.994 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-28.876 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-26.652 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-26.780 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-30.472 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-28.503 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-29.435 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-27.301 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-27.009 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-29.135 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-29.516 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-29.415 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-27.737 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-25.903 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-25.455 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-28.007 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-25.036 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-25.480 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-25.138 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-26.366 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-26.489 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-26.985 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-24.781 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-26.023 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-24.852 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-26.738 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-25.843 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-24.419 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-26.738 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-27.398 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-25.710 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-27.094 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-25.405 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-26.241 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-25.566 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-26.318 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-27.279 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-24.921 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-27.125 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-24.144 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-25.769 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-26.066 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-26.469 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-25.564 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-25.942 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-24.349 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-25.305 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-24.929 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-23.907 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-25.176 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-24.692 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-24.176 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-23.563 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-24.003 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-23.349 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-25.466 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-22.939 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-25.021 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-25.381 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-24.020 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-24.550 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-24.082 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-23.840 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-24.457 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-24.488 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-24.238 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-24.844 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-23.590 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-25.208 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-24.242 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-25.139 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-23.555 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-25.964 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-24.675 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-24.235 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-25.435 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-23.903 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-24.378 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-23.909 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-24.106 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-28.592 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-31.782 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-24.672 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-29.617 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-28.657 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-26.817 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-28.613 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-25.037 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-28.961 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-23.160 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-29.493 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-32.231 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-29.504 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-27.829 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-27.498 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-29.095 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-26.462 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-29.330 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-28.130 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-28.284 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-28.803 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-30.469 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-28.813 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-27.862 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-29.286 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-28.519 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-31.775 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-27.373 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-27.491 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-28.708 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-29.159 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-29.050 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-27.832 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-28.222 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-29.916 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-30.751 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-29.177 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-28.498 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-25.639 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-24.369 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-25.981 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-24.939 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-25.137 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-23.700 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-25.338 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-25.568 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-25.704 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-25.407 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-25.269 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-27.131 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-25.517 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-25.005 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-25.672 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-23.714 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-25.842 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-24.804 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-25.251 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-25.321 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-25.846 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-25.033 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-25.644 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-25.168 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-24.226 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-24.800 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-24.830 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-27.275 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-25.207 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-25.013 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-25.528 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-24.972 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-25.525 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-24.264 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-24.820 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-23.029 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-23.952 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-24.567 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-24.157 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-23.872 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-23.264 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-22.840 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-24.526 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-23.157 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-23.604 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-22.869 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-24.520 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-24.895 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-24.113 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-21.361 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-23.309 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-23.656 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-22.980 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-23.167 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-23.978 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-23.137 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-24.043 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-23.538 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-23.462 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-23.649 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-23.332 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-22.931 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-23.453 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-22.706 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-22.457 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-23.716 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-23.846 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-24.063 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-23.846 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-23.711 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-21.479 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-22.247 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-22.005 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-21.184 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-23.301 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-22.220 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-21.550 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-23.314 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-22.288 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-22.079 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-22.624 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-21.478 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-22.449 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-24.253 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-21.266 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-22.901 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-21.727 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-22.475 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-22.177 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-21.487 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-23.362 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-22.544 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-23.025 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-22.679 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-22.314 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-21.821 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-22.017 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-23.223 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-22.896 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-24.031 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-29.381 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-22.128 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-31.177 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-29.764 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-22.894 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-22.904 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-29.556 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-28.151 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-26.830 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-22.188 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-30.618 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-22.810 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-32.911 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-29.694 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-31.332 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-27.259 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-30.829 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-29.342 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-30.669 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-31.634 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-28.735 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-29.401 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-29.166 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-30.451 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-31.360 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-28.512 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-28.924 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-28.141 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-31.208 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-29.469 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-31.724 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-28.338 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-28.940 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-29.377 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-29.285 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-28.321 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-28.187 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-31.656 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-30.902 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-30.749 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-24.229 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-24.684 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-25.105 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-24.041 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-25.851 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-23.641 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-25.007 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-23.698 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-23.772 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-23.643 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-25.027 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-25.726 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-23.538 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-24.975 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-24.763 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-23.786 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-24.329 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-26.512 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-24.833 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-25.106 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-24.312 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-24.630 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-25.410 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-25.172 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-23.747 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-24.627 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-23.837 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-24.032 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-24.220 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-24.042 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-23.258 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-24.411 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-25.077 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-25.307 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-25.000 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-22.482 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-22.168 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-22.333 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-22.103 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-22.335 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-21.391 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-22.361 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-22.814 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-22.197 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-23.313 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-22.539 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-23.231 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-23.674 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-23.282 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-22.418 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-23.435 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-21.986 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-22.542 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-22.792 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-22.408 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-22.390 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-21.435 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-22.228 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-23.913 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-20.792 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-22.178 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-22.875 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-21.892 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-22.330 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-21.879 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-23.587 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-22.563 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-23.434 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-22.410 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-21.302 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-21.605 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-21.328 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-21.286 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-20.675 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-21.950 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-21.411 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-21.009 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-21.310 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-20.750 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-21.846 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-20.518 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-21.852 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-22.295 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-21.263 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-20.489 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-22.348 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-20.888 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-21.636 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-21.629 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-21.195 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-20.937 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-21.087 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-21.666 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-20.404 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-20.010 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-21.810 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-21.473 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-21.249 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-21.274 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-20.575 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-26.442 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-24.560 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-22.518 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-20.579 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-21.116 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-21.298 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-26.905 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-24.036 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-26.475 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-24.667 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-21.392 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-25.300 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-26.678 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-25.148 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-24.842 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-24.987 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-25.089 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-27.247 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-24.746 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-24.741 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-24.374 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-25.621 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-25.740 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-24.685 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-25.154 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-24.643 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-25.274 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-25.198 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-25.491 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-26.470 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-26.108 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-25.065 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-25.299 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-24.879 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-25.532 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-24.493 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-23.743 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-26.877 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-25.210 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-25.433 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-22.611 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-22.595 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-22.089 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-21.393 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-21.288 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-22.247 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-22.341 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-23.248 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-22.501 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-21.594 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-23.072 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-20.896 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-21.993 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-22.123 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-22.350 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-22.604 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-22.775 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-21.939 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-22.097 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-21.085 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-22.068 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-22.956 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-22.102 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-22.841 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-22.937 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-21.289 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-22.452 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-23.239 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-22.413 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-22.091 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-21.809 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-22.057 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-21.186 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-21.445 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-22.293 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-20.689 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-21.023 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-20.486 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-20.469 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-20.189 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-20.788 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-20.462 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-20.750 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-20.238 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-21.540 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-21.248 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-20.228 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-21.125 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-20.940 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-21.704 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-21.156 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-20.877 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-21.023 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-21.380 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-19.925 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-19.648 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-20.759 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-20.804 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-20.994 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-20.156 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-20.666 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-20.589 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-20.682 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-20.270 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-21.046 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-21.119 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-20.179 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-21.235 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-20.612 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-20.353 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-20.212 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-19.945 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-20.764 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-19.958 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-19.968 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-19.627 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-19.943 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-19.987 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-19.456 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-20.223 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-18.926 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-20.779 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-19.674 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-19.544 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-19.526 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-18.847 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-19.949 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-19.476 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-19.709 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-18.528 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-19.043 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-19.408 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-20.200 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-19.130 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-20.002 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-18.567 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-19.343 total time= 1.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-19.632 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-19.122 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-19.489 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-18.477 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-23.681 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-25.336 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-25.823 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-19.634 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-25.316 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-26.585 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-24.908 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-19.178 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-25.583 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-26.706 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-19.547 total time= 1.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-24.912 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-25.979 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-24.303 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-19.617 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-25.562 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-25.299 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-25.847 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-26.528 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-26.663 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-24.634 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-25.733 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-25.906 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-25.545 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-24.306 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-24.765 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-23.489 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-24.380 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-24.278 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-25.728 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-23.952 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-25.370 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-26.751 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-25.627 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-24.646 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-24.554 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-27.193 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-25.057 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-25.481 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-21.983 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-22.746 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-21.724 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-21.229 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-22.334 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-21.194 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-21.380 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-21.899 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-21.706 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-21.373 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-21.218 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-21.341 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-21.384 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-20.182 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-20.517 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-21.000 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-21.994 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-20.782 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-20.815 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-22.134 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-20.760 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-21.549 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-22.162 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-20.158 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-20.348 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-20.320 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-21.132 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-21.375 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-21.411 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-20.292 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-22.068 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-21.767 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-20.882 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-21.384 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-21.922 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-19.803 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-20.364 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-19.999 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-19.069 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-19.984 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-20.054 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-19.245 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-19.416 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-19.968 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-19.510 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-18.870 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-19.966 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-19.437 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-19.284 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-19.242 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-19.572 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-19.994 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-19.732 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-18.979 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-19.914 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-18.858 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-19.681 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-20.028 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-19.005 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-19.042 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-19.361 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-20.350 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-19.197 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-18.845 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-19.520 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-20.400 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-19.518 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-19.997 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-20.160 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-19.857 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-18.676 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-18.547 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-19.485 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-18.790 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-19.736 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-18.415 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-19.172 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-18.464 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-19.187 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-18.825 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-17.297 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-19.300 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-18.655 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-18.332 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-18.133 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-17.962 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-19.077 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-19.396 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-18.361 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-18.257 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-18.264 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-18.420 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-17.875 total time= 1.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-17.999 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-18.908 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-18.032 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-18.324 total time= 1.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-19.112 total time= 1.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-18.233 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-17.666 total time= 1.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-19.315 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-19.280 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-21.821 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-19.360 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-22.624 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-22.886 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-21.571 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-18.468 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-21.390 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-21.788 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-18.061 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-21.358 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-22.725 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-21.808 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-21.608 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-21.651 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-22.749 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-21.504 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-21.576 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-22.175 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-22.890 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-21.480 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-21.895 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-21.285 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-21.862 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-21.784 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-22.393 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-22.194 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-22.553 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-21.706 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-21.372 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-22.216 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-21.722 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-20.784 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-22.240 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-21.363 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-22.256 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-22.153 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-21.958 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-20.765 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-18.993 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-19.894 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-19.644 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-19.778 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-18.771 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-18.931 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-19.612 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-19.670 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-19.588 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-20.223 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-19.285 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-18.877 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-19.774 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-18.894 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-19.943 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-18.359 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-19.589 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-21.051 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-18.795 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-18.619 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-18.573 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-19.729 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-19.823 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-19.079 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-19.396 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-19.796 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-18.246 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-19.558 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-18.758 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-19.611 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-18.754 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-19.241 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-19.488 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-18.378 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-18.981 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-18.847 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-17.934 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-19.247 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-18.256 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-18.595 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-17.408 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-18.503 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-18.330 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-17.899 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-17.975 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-16.916 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-18.202 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-18.250 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-17.207 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-17.781 total time= 1.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-17.615 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-18.537 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-18.408 total time= 1.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-17.359 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-17.888 total time= 1.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-17.190 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-18.301 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-17.949 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-17.565 total time= 1.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-17.768 total time= 1.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-16.940 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-18.389 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-18.819 total time= 1.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-17.545 total time= 1.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-18.091 total time= 1.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-16.739 total time= 1.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-18.578 total time= 1.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-18.342 total time= 1.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-18.015 total time= 1.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-18.050 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-17.952 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-16.518 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-17.940 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-16.862 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-17.644 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-16.440 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-17.993 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-18.030 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-16.749 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-17.627 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-16.392 total time= 1.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-17.648 total time= 1.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-17.681 total time= 1.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-16.486 total time= 1.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-16.893 total time= 1.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-16.600 total time= 1.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-17.826 total time= 1.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-17.204 total time= 1.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-17.082 total time= 1.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-17.166 total time= 1.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-16.253 total time= 1.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-17.665 total time= 1.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-16.709 total time= 1.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-16.852 total time= 1.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-17.940 total time= 1.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-16.406 total time= 1.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-17.483 total time= 1.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-17.534 total time= 1.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-17.032 total time= 1.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-33.367 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-32.227 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-31.991 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-32.282 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-16.839 total time= 1.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-31.155 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-29.658 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-35.548 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-32.139 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-17.653 total time= 1.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-32.780 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-16.061 total time= 2.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-17.225 total time= 1.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-28.692 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-16.552 total time= 1.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-31.775 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-28.596 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-31.422 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-31.599 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-27.522 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-28.741 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-30.195 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-30.579 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-31.013 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-37.174 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-30.097 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-35.585 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-28.715 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-33.846 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-31.890 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-30.264 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-32.137 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-32.769 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-30.350 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-31.635 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-30.911 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-34.436 total time= 0.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.075, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-17.284 total time= 1.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-33.117 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-33.491 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-30.221 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-28.160 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-27.430 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-26.177 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-26.511 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-26.487 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-26.138 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-26.111 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-29.179 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-25.975 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-26.010 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-26.058 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-26.962 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-26.477 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-25.917 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-26.132 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-26.359 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-26.274 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-27.184 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-26.533 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-26.154 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-25.546 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-26.688 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-25.523 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-26.683 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-26.086 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-27.694 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-26.586 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-27.001 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-25.501 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-25.843 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-25.307 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-28.365 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-26.974 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-26.057 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-25.403 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-23.482 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-24.787 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-23.963 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-24.177 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-24.536 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-22.509 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-25.652 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-24.683 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-25.323 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-23.905 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-23.915 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-25.607 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-24.981 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-24.526 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-23.114 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-24.983 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-24.260 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-24.664 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-23.859 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-24.677 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-24.283 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-24.931 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-25.246 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-22.126 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-26.040 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-24.148 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-23.212 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-23.805 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-25.097 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-23.549 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-24.754 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-25.255 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-23.357 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-24.323 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-24.362 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-22.695 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-22.970 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-22.992 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-21.813 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-24.116 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-23.857 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-22.462 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-23.709 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-21.538 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-23.643 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-22.743 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-23.485 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-22.801 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-23.743 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-24.235 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-23.829 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-23.182 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-22.998 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-23.792 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-22.705 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-22.341 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-22.590 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-25.271 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-24.022 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-23.525 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-23.946 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-22.736 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-22.826 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-22.315 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-26.287 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-23.916 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-22.085 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-23.795 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-29.201 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-28.476 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-28.614 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-25.912 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-22.614 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-22.322 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-26.463 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-23.146 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-27.685 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-28.847 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-29.468 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-27.028 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-28.955 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-26.593 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-26.834 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-27.416 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-26.387 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-27.925 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-28.041 total time= 0.2s[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-30.062 total time= 0.2s\n", + "\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-29.316 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-26.037 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-29.047 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-27.267 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-28.434 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-25.846 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-25.332 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-26.724 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-25.681 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-28.682 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-27.864 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-26.578 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-27.906 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-27.062 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-28.386 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-28.238 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-27.306 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-23.709 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-23.437 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-22.496 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-24.941 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-24.328 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-23.902 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-23.963 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-25.324 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-23.622 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-23.953 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-24.571 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-24.180 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-24.997 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-23.163 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-25.905 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-23.961 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-23.948 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-23.793 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-23.775 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-23.947 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-23.776 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-25.241 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-23.609 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-23.296 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-23.583 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-22.996 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-24.364 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-24.266 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-24.762 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-24.125 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-24.093 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-24.469 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-25.061 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-24.006 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-23.679 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-23.411 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-22.996 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-22.348 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-22.405 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-23.739 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-24.080 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-22.388 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-23.134 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-23.020 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-21.824 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-22.382 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-21.916 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-22.521 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-22.113 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-23.536 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-22.169 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-22.011 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-22.525 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-21.083 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-22.967 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-22.947 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-22.041 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-22.782 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-21.627 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-23.055 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-22.807 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-21.395 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-22.411 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-22.206 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-23.017 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-23.655 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-22.425 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-21.782 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-23.096 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-22.827 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-21.487 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-21.379 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-22.233 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-22.792 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-20.121 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-20.922 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-23.238 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-21.327 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-21.224 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-22.543 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-21.163 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-21.472 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-21.379 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-22.446 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-20.244 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-21.046 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-20.711 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-22.288 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-21.417 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-21.270 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-19.759 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-21.703 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-21.536 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-22.054 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-21.399 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-20.247 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-21.096 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-22.099 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-21.015 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-21.941 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-21.821 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-21.950 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-25.674 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-26.674 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-29.300 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-20.762 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-28.305 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-29.067 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-26.781 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-21.461 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-26.673 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-26.936 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-28.709 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-29.336 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-26.740 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-22.170 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-25.810 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-26.815 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-26.651 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-27.272 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-26.565 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-28.411 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-27.829 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-32.292 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-28.396 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-27.136 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-29.067 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-27.904 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-29.716 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-26.370 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-26.203 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-25.945 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-28.409 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-26.802 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-26.122 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-28.188 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-28.192 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-27.014 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-28.236 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-25.688 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-24.017 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-22.766 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-24.745 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-24.520 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-23.425 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-22.098 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-23.570 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-24.203 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-23.094 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-23.605 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-22.587 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-25.055 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-22.908 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-24.497 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-23.769 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-23.217 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-22.222 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-25.049 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-22.942 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-22.315 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-22.444 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-24.017 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-24.233 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-23.487 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-24.034 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-23.927 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-23.040 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-23.787 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-23.341 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-21.182 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-21.817 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-23.109 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-22.953 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-22.609 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-22.350 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-20.216 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-21.653 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-20.893 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-20.708 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-21.671 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-21.330 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-21.521 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-22.719 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-22.108 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-21.622 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-20.996 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-22.467 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-22.072 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-21.183 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-21.485 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-21.279 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-20.606 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-22.972 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-20.615 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-21.242 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-20.080 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-21.355 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-22.777 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-21.449 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-21.988 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-19.966 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-20.539 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-21.244 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-20.599 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-21.732 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-22.427 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-22.054 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-20.903 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-20.537 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-20.862 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-19.331 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-20.338 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-20.978 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-19.882 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-19.825 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-20.082 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-20.555 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-19.918 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-20.436 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-22.369 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-19.631 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-20.264 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-20.956 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-20.041 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-21.100 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-19.362 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-20.557 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-20.769 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-19.663 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-19.146 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-21.105 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-20.982 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-19.964 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-20.181 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-20.351 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-19.896 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-21.242 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-20.164 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-20.390 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-23.363 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-20.640 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-23.633 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-20.408 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-21.276 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-20.984 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-24.637 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-24.648 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-20.305 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-24.052 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-19.531 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-24.101 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-22.380 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-24.442 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-23.875 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-24.317 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-25.081 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-23.857 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-23.694 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-25.686 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-23.677 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-24.320 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-25.087 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-24.901 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-23.062 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-25.556 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-24.874 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-24.016 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-23.413 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-23.277 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-23.927 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-25.653 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-23.310 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-24.912 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-23.301 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-25.681 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-23.574 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-23.160 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-23.535 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-23.015 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-22.622 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-20.163 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-20.980 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-20.992 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-20.719 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-20.599 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-20.126 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-21.666 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-21.107 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-21.495 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-20.326 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-21.748 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-21.072 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-21.412 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-21.766 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-21.229 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-20.527 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-20.700 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-20.827 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-21.146 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-20.915 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-20.944 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-20.497 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-21.336 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-20.641 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-21.364 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-20.313 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-20.897 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-21.185 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-20.360 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-21.233 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-20.826 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-20.873 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-22.431 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-20.554 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-20.859 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-20.282 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-20.414 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-19.477 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-20.007 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-20.297 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-18.783 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-20.049 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-20.081 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-19.875 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-19.353 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-19.422 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-19.784 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-19.560 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-19.510 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-20.258 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-18.893 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-20.332 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-19.975 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-19.259 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-21.550 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-19.576 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-19.506 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-19.816 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-19.431 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-19.074 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-19.230 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-20.219 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-19.082 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-19.930 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-18.840 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-19.924 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-19.606 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-19.808 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-19.792 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-19.208 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-18.121 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-19.168 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-19.451 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-19.987 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-19.228 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-18.536 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-19.031 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-18.720 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-19.144 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-19.293 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-17.998 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-19.014 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-18.617 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-18.195 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-18.639 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-18.239 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-18.921 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-18.654 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-18.769 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-18.052 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-17.592 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-18.692 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-18.763 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-18.215 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-17.772 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-18.232 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-18.897 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-17.571 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-18.790 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-23.114 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-23.607 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-17.990 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-26.134 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-19.141 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-22.617 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-24.739 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-17.585 total time= 1.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-18.790 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-21.956 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-24.600 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-24.330 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-18.037 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-23.657 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-23.885 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-18.613 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-24.415 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-23.846 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-22.794 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-25.364 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-24.029 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-22.144 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-23.623 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-23.274 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-24.357 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-23.359 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-24.409 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-22.412 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-23.241 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-21.558 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-23.534 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-23.598 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-22.644 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-24.336 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-24.050 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-21.370 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-23.869 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-24.769 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-23.699 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-21.852 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-23.022 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-20.657 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-20.630 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-21.528 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-20.022 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-20.305 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-19.563 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-20.039 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-21.058 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-18.957 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-19.005 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-21.531 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-20.457 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-20.025 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-19.465 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-20.604 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-20.519 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-19.780 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-20.683 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-21.065 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-19.929 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-18.842 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-20.340 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-19.643 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-20.230 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-18.788 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-19.102 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-19.655 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-19.884 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-19.813 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-20.256 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-19.473 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-20.073 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-20.630 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-20.236 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-20.028 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-18.363 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-18.894 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-19.167 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-19.743 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-19.609 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-18.404 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-19.309 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-20.194 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-18.818 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-18.567 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-18.396 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-19.587 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-19.411 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-18.273 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-18.658 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-17.545 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-18.923 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-19.494 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-17.930 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-18.043 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-17.302 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-18.949 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-18.303 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-18.211 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-19.412 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-19.428 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-17.564 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-18.996 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-18.504 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-18.785 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-18.688 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-18.986 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-17.628 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-18.765 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-18.327 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-17.913 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-18.349 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-18.729 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-18.112 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-19.138 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-17.907 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-17.653 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-17.570 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-18.026 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-17.849 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-16.580 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-18.120 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-18.035 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-17.325 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-17.721 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-17.005 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-17.898 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-18.184 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-17.608 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-17.593 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-16.899 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-18.476 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-17.752 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-18.397 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-16.957 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-16.982 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-17.922 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-17.660 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-17.799 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-17.194 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-17.251 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-20.051 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-17.729 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-22.617 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-18.257 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-21.575 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-21.561 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-20.942 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-20.868 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-21.059 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-22.325 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-21.690 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-18.119 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-20.897 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-20.992 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-17.842 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-20.932 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-20.225 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-20.515 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-20.876 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-21.005 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-20.782 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-19.707 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-21.356 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-20.773 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-21.749 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-20.880 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-19.836 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-20.054 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-21.396 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-19.586 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-21.431 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-21.138 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-19.331 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-20.798 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-21.190 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-19.856 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-20.082 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-20.627 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-20.424 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-18.184 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-19.205 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-19.411 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-18.865 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-19.080 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-18.771 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-18.086 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-19.118 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-18.113 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-18.123 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-17.456 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-18.438 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-18.730 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-18.552 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-18.327 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-17.732 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-18.402 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-18.427 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-17.972 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-19.627 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-17.569 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-18.934 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-18.355 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-17.948 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-18.324 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-17.615 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-18.744 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-18.318 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-18.207 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-18.848 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-18.287 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-17.114 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-18.073 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-18.040 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-19.088 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-17.966 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-16.995 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-17.669 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-16.996 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-18.353 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-17.079 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-18.004 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-17.813 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-17.029 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-17.611 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-16.127 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-17.655 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-17.695 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-17.008 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-17.373 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-18.103 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-16.381 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-17.578 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-16.872 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-17.172 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-16.339 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-17.906 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-17.784 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-16.972 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-16.891 total time= 1.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-16.386 total time= 1.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-17.346 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-17.617 total time= 1.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-16.402 total time= 1.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-17.236 total time= 1.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-16.309 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-17.785 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-18.103 total time= 1.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-17.024 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-17.333 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-16.216 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-17.749 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-17.442 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-16.775 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-17.240 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-16.080 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-17.311 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-16.504 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-17.390 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-16.720 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-15.651 total time= 1.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-17.382 total time= 1.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-16.994 total time= 1.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-16.233 total time= 1.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-16.324 total time= 1.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-16.003 total time= 1.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-17.272 total time= 1.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-16.899 total time= 1.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-16.505 total time= 1.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-16.543 total time= 1.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-15.730 total time= 1.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-17.148 total time= 1.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-16.995 total time= 1.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-16.359 total time= 1.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-16.010 total time= 1.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-16.335 total time= 1.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-17.098 total time= 1.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-16.926 total time= 1.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-28.640 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-16.095 total time= 1.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-15.981 total time= 1.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-26.821 total time= 0.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-15.791 total time= 1.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-32.527 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-27.588 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-29.465 total time= 0.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-28.748 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-28.384 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-27.260 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-33.848 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-17.077 total time= 1.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-27.013 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-31.604 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-28.055 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-27.466 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-28.993 total time= 0.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-32.223 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-26.563 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-27.415 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-17.162 total time= 1.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-26.974 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-30.288 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-27.640 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-28.377 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-16.058 total time= 1.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-30.763 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-26.245 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-27.483 total time= 0.2s[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-27.479 total time= 0.2s\n", + "\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-26.908 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-25.930 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-29.956 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.1, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-16.719 total time= 1.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-28.435 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-29.116 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-27.472 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-30.168 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-33.775 total time= 0.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-32.374 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-27.992 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-25.360 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-24.799 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-26.243 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-25.463 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-23.991 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-25.008 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-24.815 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-26.557 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-24.552 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-24.793 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-23.616 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-23.951 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-25.029 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-24.079 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-26.459 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-23.939 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-23.771 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-24.438 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-25.892 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-24.900 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-23.082 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-25.032 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-26.141 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-24.266 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-25.413 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-23.513 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-24.198 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-23.301 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-24.415 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-23.721 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-24.352 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-23.896 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-23.905 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-24.678 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-24.155 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-23.513 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-22.091 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-23.672 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-23.293 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-22.527 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-24.121 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-22.774 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-22.596 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-22.510 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-22.543 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-22.736 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-23.976 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-22.240 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-21.482 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-22.929 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-23.885 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-23.076 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-23.654 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-23.050 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-22.667 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-22.718 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-23.057 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-22.164 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-24.576 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-23.332 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-23.045 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-22.743 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-21.757 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-21.467 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-22.088 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-23.094 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-22.445 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-23.786 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-23.352 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-23.738 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-21.974 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-22.587 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-20.128 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-21.828 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-23.319 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-22.853 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-21.317 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-22.056 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-21.908 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-23.379 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-21.306 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-20.550 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-22.334 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-20.694 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-20.939 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-21.922 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-21.414 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-22.072 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-21.643 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-21.507 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-20.474 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-22.104 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-22.100 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-21.492 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-20.725 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-20.072 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-22.241 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-21.417 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-20.828 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-24.259 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-22.434 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-24.636 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-23.315 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-26.516 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-21.613 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-21.875 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-25.003 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-25.279 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-25.566 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-23.229 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-25.383 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-24.685 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-21.994 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-24.983 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-25.436 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-24.825 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-24.429 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-25.117 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-25.909 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-24.816 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-24.420 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-24.925 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-25.542 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-25.340 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-24.507 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-26.342 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-24.865 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-26.660 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-24.147 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-24.830 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-24.475 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-25.347 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-25.025 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-25.329 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-23.819 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-27.205 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-25.671 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-25.053 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-26.123 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-24.699 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-22.465 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-22.972 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-22.420 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-23.311 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-22.110 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-23.259 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-21.622 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-21.854 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-22.853 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-23.056 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-23.970 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-22.271 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-22.188 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-21.198 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-24.647 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-22.319 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-21.626 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-23.815 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-24.167 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-21.912 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-21.441 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-22.133 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-23.065 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-22.592 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-22.053 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-22.198 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-22.708 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-23.225 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-21.726 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-22.322 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-22.411 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-22.421 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-22.447 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-21.464 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-21.333 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-20.689 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-20.755 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-20.918 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-21.172 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-21.781 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-22.329 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-21.743 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-19.957 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-19.954 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-22.074 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-20.491 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-20.655 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-20.440 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-21.501 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-20.783 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-21.854 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-22.304 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-21.238 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-21.431 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-20.994 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-20.074 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-20.971 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-21.046 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-21.155 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-21.273 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-19.910 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-22.468 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-20.752 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-21.729 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-21.458 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-21.092 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-20.968 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-21.407 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-21.226 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-22.402 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-20.325 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-21.252 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-20.899 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-19.355 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-19.584 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-20.496 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-20.680 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-20.143 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-20.616 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-21.144 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-20.282 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-19.848 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-21.133 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-19.176 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-20.760 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-19.122 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-20.597 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-19.540 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-20.469 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-22.248 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-20.415 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-20.964 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-20.635 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-19.317 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-19.820 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-20.373 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-19.103 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-19.512 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-26.586 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-20.310 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-19.432 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-19.839 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-20.955 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-19.620 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-23.737 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-26.434 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-24.468 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-24.587 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-23.521 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-24.689 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-19.903 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-20.268 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-24.197 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-26.192 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-24.331 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-23.576 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-23.711 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-26.000 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-24.671 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-24.423 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-24.959 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-23.477 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-26.778 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-25.143 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-24.189 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-24.659 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-27.656 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-26.053 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-23.805 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-23.925 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-23.745 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-24.360 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-24.137 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-24.947 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-24.987 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-24.484 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-22.671 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-24.782 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-25.467 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-24.524 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-22.507 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-21.439 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-20.171 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-20.930 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-22.505 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-21.816 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-20.471 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-21.425 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-22.014 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-21.261 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-21.128 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-20.550 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-21.747 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-22.013 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-22.508 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-20.807 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-20.848 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-23.078 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-21.786 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-20.359 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-21.813 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-20.583 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-20.786 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-20.874 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-21.099 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-21.672 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-19.860 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-22.011 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-21.761 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-21.188 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-21.777 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-22.132 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-21.774 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-20.896 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-24.089 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-20.385 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-21.386 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-20.665 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-21.338 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-21.073 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-19.654 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-20.185 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-19.684 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-19.611 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-20.807 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-19.850 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-18.781 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-19.914 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-19.341 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-20.299 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-20.334 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-19.662 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-20.469 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-18.481 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-19.061 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-21.503 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-19.750 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-20.947 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-18.748 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-19.902 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-19.316 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-19.557 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-21.114 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-19.781 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-19.772 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-19.611 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-20.002 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-19.053 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-19.237 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-19.942 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-19.079 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-21.141 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-19.510 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-19.262 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-18.524 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-19.232 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-18.485 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-19.720 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-19.325 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-19.775 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-18.200 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-19.491 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-19.903 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-19.723 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-19.711 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-17.368 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-19.265 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-19.251 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-19.223 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-18.559 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-19.459 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-19.181 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-18.981 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-18.743 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-19.227 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-19.044 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-20.496 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-19.936 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-19.215 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-21.052 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-22.942 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-20.094 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-17.752 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-19.595 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-23.552 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-20.413 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-21.866 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-22.075 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-19.341 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-18.729 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-21.934 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-23.731 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-19.026 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-22.179 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-21.725 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-21.418 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-22.731 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-21.671 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-22.303 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-24.852 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-21.993 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-21.868 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-23.091 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-22.348 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-22.227 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-22.230 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-22.351 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-21.845 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-23.536 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-24.519 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-22.433 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-22.423 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-21.387 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-23.339 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-21.881 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-23.085 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-21.491 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-23.037 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-21.893 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-22.905 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-20.435 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-20.548 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-19.297 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-20.537 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-20.631 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-19.412 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-19.952 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-20.751 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-18.345 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-20.525 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-19.681 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-20.023 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-18.271 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-19.698 total time= 0.6s[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-19.808 total time= 0.5s\n", + "\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-18.934 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-19.953 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-18.451 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-19.864 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-20.645 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-19.236 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-20.511 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-19.192 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-20.256 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-18.749 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-19.616 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-19.764 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-19.388 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-20.729 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-19.737 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-18.952 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-19.423 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-19.915 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-19.151 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-20.141 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-18.208 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-19.124 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-19.226 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-18.483 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-19.216 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-17.922 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-19.342 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-18.545 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-18.633 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-19.033 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-18.540 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-17.589 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-19.378 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-18.492 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-17.982 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-18.392 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-17.814 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-18.217 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-18.019 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-18.045 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-17.468 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-18.580 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-18.591 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-18.440 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-17.581 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-17.417 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-18.813 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-18.649 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-19.599 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-17.729 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-17.275 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-18.055 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-18.445 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-17.976 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-16.893 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-17.420 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-18.416 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-17.957 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-17.753 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-18.720 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-17.221 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-18.520 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-16.839 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-17.835 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-18.268 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-17.203 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-17.572 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-17.654 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-16.969 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-17.422 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-16.263 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-17.714 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-17.725 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-17.905 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-17.505 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-16.838 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-18.046 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-17.566 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-18.226 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-16.729 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-17.901 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-17.504 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-16.564 total time= 1.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-23.209 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-17.489 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-17.233 total time= 1.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-22.235 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-21.965 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-18.219 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-20.982 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-18.752 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-16.687 total time= 1.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-20.672 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-23.344 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-21.570 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-22.102 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-21.410 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-21.212 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-22.538 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-17.048 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-21.911 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-22.780 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-21.156 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-17.243 total time= 1.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-20.900 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-19.761 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-22.338 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-21.925 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-21.738 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-21.812 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-20.323 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-22.572 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-21.777 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-20.570 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-21.878 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-21.445 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-21.557 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-20.787 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-19.895 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-21.763 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-21.111 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-22.572 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-21.519 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-20.193 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-21.482 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-19.111 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-18.771 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-18.262 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-19.597 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-18.606 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-18.811 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-18.196 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-19.653 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-20.498 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-18.902 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-19.465 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-18.677 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-18.820 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-18.115 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-19.711 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-17.563 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-19.259 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-18.620 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-18.690 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-17.896 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-18.232 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-18.547 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-19.065 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-18.888 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-18.191 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-18.228 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-19.366 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-19.349 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-17.845 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-19.129 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-17.755 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-20.258 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-18.615 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-17.944 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-18.879 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-18.390 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-16.901 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-18.252 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-18.534 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-17.843 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-17.692 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-17.555 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-17.984 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-17.638 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-17.639 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-18.127 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-17.058 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-17.751 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-17.040 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-16.951 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-17.538 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-17.562 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-17.964 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-17.150 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-17.767 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-16.293 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-17.559 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-17.265 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-18.624 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-16.796 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-16.999 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-17.876 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-16.804 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-18.085 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-17.686 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-17.070 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-18.002 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-18.297 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-17.647 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-17.473 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-17.448 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-18.026 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-17.103 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-17.426 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-16.861 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-16.120 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-17.782 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-17.056 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-16.540 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-16.494 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-16.135 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-17.884 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-17.168 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-16.954 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-17.038 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-16.195 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-17.101 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-16.947 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-16.463 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-17.204 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-15.986 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-15.948 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-16.751 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-16.298 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-16.509 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-16.156 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-17.156 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-17.133 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-16.567 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-17.377 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-19.157 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-19.102 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-15.948 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-20.508 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-19.907 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-19.053 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-19.864 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-17.383 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-17.047 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-19.965 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-16.456 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-16.743 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-20.040 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-19.769 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-19.619 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-19.900 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-18.845 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-19.728 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-19.173 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-19.040 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-18.364 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-19.977 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-19.502 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-19.472 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-19.711 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-19.046 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-19.697 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-19.066 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-20.088 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-18.993 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-20.031 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-19.572 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-19.060 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-19.780 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-18.854 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-18.572 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-20.031 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-20.491 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-19.035 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-19.405 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-16.778 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-18.371 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-18.198 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-17.227 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-17.050 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-16.624 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-18.866 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-17.813 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-17.172 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-17.295 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-16.646 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-17.777 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-17.903 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-17.709 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-17.195 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-16.338 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-18.108 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-17.802 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-16.563 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-16.146 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-17.347 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-17.229 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-17.991 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-17.608 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-16.466 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-16.387 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-17.646 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-18.124 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-16.923 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-16.955 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-17.093 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-16.473 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-18.004 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-17.409 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-16.299 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-17.566 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-17.556 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-17.526 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-17.167 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-16.186 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-16.246 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-17.762 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-17.270 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-16.309 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-16.168 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-15.578 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-17.577 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-16.971 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-16.746 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-16.217 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-15.535 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-16.038 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-17.678 total time= 1.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-15.871 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-16.341 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-15.776 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-17.442 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-16.773 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-16.288 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-16.698 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-15.540 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-17.009 total time= 1.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-15.880 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-16.994 total time= 1.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-16.347 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-16.254 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-17.032 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-16.987 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-15.748 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-16.054 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-17.240 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-17.068 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-15.941 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-16.493 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-16.604 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-15.419 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-16.630 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-16.079 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-16.012 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-16.536 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-15.371 total time= 1.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-16.796 total time= 1.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-16.619 total time= 1.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-15.993 total time= 1.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-16.317 total time= 1.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-15.258 total time= 1.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-16.807 total time= 1.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-16.126 total time= 1.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-15.244 total time= 1.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-15.981 total time= 1.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-15.479 total time= 1.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-16.871 total time= 1.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-16.153 total time= 1.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-15.621 total time= 1.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-15.993 total time= 1.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-15.190 total time= 1.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-16.660 total time= 1.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-17.103 total time= 1.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-15.778 total time= 1.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-31.177 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-16.204 total time= 1.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-25.387 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-15.553 total time= 1.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-26.588 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-27.042 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-25.724 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-27.190 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-28.637 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-28.347 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-26.730 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-28.629 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-16.801 total time= 1.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-16.716 total time= 1.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-16.014 total time= 1.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-28.048 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-26.532 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-25.346 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-27.380 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-25.958 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-26.491 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-25.518 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-27.295 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-27.552 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-25.437 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.15, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-16.152 total time= 1.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-25.751 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-26.406 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-27.767 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-26.523 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-26.906 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-26.853 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-25.436 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-25.872 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-27.659 total time= 0.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-25.725 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-24.374 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-25.491 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-27.762 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-27.209 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-28.767 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-24.108 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-25.032 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-22.296 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-22.206 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-23.959 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-21.456 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-21.834 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-24.391 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-25.300 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-23.605 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-24.163 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-23.374 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-23.808 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-25.029 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-23.686 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-24.231 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-22.493 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-23.306 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-23.076 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-23.590 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-22.118 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-23.773 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-24.770 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-23.161 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-23.109 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-21.841 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-22.954 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-21.894 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-22.893 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-24.547 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-24.407 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-21.649 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-22.543 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-23.733 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-22.984 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-23.324 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-21.289 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-23.013 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-23.014 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-22.760 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-22.148 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-23.401 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-21.253 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-23.770 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-22.634 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-20.950 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-22.078 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-21.637 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-21.196 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-23.884 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-21.857 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-20.902 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-22.692 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-22.034 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-22.070 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-20.653 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-21.544 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-21.670 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-22.504 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-22.659 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-21.284 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-21.933 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-20.453 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-20.896 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-22.470 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-22.459 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-21.006 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-21.469 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-21.860 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-22.235 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-21.415 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-22.177 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-21.272 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-22.099 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-22.449 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-21.345 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-21.934 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-21.235 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-21.019 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-20.698 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-19.285 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-20.060 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-21.345 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-20.567 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-20.577 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-20.814 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-21.044 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-20.557 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-22.384 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-20.783 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-20.173 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-20.902 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-22.714 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-19.554 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-21.390 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-21.964 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-20.944 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-21.487 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-21.469 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-20.305 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-20.255 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-23.906 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-25.425 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-24.555 total time= 0.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-20.334 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-22.852 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-25.333 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-20.552 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-21.989 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-25.275 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-22.869 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-20.612 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-25.703 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-24.721 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-24.861 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-23.964 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-25.218 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-24.304 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-23.739 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-24.959 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-22.925 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-24.798 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-24.876 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-21.958 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-23.740 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-25.032 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-22.914 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-24.693 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-22.667 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-22.771 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-23.454 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-24.369 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-24.641 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-21.896 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-24.838 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-24.371 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-23.720 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-23.667 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-27.585 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-22.158 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-21.748 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-21.704 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-23.204 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-22.643 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-22.026 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-22.877 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-21.311 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-24.252 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-22.909 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-20.110 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-20.928 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-21.260 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-23.789 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-20.585 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-22.093 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-20.034 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-21.273 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-21.132 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-21.243 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-21.590 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-20.661 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-20.053 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-21.392 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-20.785 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-22.013 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-21.975 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-21.129 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-21.663 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-20.098 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-21.504 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-20.465 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-23.100 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-22.699 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-21.805 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-21.602 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-20.013 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-20.242 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-20.092 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-20.103 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-21.319 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-20.191 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-20.848 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-20.561 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-20.050 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-20.600 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-19.964 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-21.238 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-19.604 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-19.690 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-20.782 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-20.266 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-19.731 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-21.019 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-19.850 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-19.702 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-20.957 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-20.406 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-20.295 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-20.640 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-20.594 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-20.203 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-20.014 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-20.178 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-19.375 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-20.850 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-20.268 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-21.353 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-20.372 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-19.285 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-20.739 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-18.966 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-20.460 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-20.299 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-19.837 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-20.491 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-18.595 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-21.174 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-19.522 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-19.139 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-19.104 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-20.168 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-19.694 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-19.912 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-18.560 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-19.666 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-19.890 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-18.167 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-18.083 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-20.336 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-19.870 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-18.218 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-19.289 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-19.716 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-18.517 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-19.265 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-18.428 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-19.870 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-18.848 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-19.129 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-19.269 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-22.665 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-18.000 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-22.691 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-19.651 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-19.393 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-23.678 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-25.081 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-19.838 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-23.994 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=3, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-18.266 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-24.337 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-25.794 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-24.144 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-23.542 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-24.583 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-23.021 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-23.247 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-23.250 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-22.524 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-21.972 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-22.712 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-23.529 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-26.613 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-20.859 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-24.094 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-23.476 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-23.948 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-24.495 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-24.009 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-22.558 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-25.614 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-24.082 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-23.820 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-24.038 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-24.931 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-22.266 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-25.972 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-24.355 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-22.952 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-23.356 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-20.908 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-19.830 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-19.900 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-21.538 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-19.884 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-21.755 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-19.533 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-19.892 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-21.425 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-20.582 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-20.437 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-20.624 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-20.043 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-20.126 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-22.188 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-20.615 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-20.782 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-21.141 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-21.252 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-20.395 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-20.851 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-18.993 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-21.512 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-19.925 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-19.058 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-19.108 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-20.765 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-20.324 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-19.898 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-19.565 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-20.447 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-20.949 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-20.044 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-19.721 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-20.153 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-20.616 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-19.002 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-20.962 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-18.860 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-21.488 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-18.604 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-19.723 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-19.564 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-18.899 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-20.416 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-18.130 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-18.931 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-20.412 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-20.619 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-19.485 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-17.958 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-19.569 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-20.365 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-19.216 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-20.339 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-19.504 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-19.162 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-20.411 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-18.857 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-19.412 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-18.837 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-18.250 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-20.370 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-19.363 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-17.698 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-19.283 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-19.114 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-19.875 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-18.948 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-19.416 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-18.575 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-19.361 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-19.632 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-18.861 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-19.798 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-18.517 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-19.597 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-18.378 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-18.070 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-18.455 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-18.621 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-19.472 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-17.586 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-19.093 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-17.729 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-18.567 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-18.784 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-19.546 total time= 24.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-18.297 total time= 24.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-19.365 total time= 24.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-17.968 total time= 24.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-18.220 total time= 24.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-18.311 total time= 24.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-18.496 total time= 24.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-18.839 total time= 24.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-17.735 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-18.925 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-19.305 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-17.539 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-17.720 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-21.913 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-17.928 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-18.503 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-21.887 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-22.317 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-20.663 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-17.614 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-21.885 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-18.430 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-17.673 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-22.149 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-21.509 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-21.144 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-21.002 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-21.792 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-21.647 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-22.020 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-21.452 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-20.959 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-21.413 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-22.303 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-22.170 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-21.568 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-20.844 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-20.073 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-20.476 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-20.775 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-21.539 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-21.298 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-21.044 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-21.440 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-22.378 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-21.559 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-21.312 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-20.101 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-23.194 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-20.261 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-21.480 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-20.600 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-21.199 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-18.444 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-19.326 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-18.831 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-19.348 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-19.172 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-18.211 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-19.387 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-19.412 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-18.507 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-19.111 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-18.242 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-18.937 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-18.994 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-19.454 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-19.201 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-19.383 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-18.089 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-18.356 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-19.854 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-18.325 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-18.845 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-19.156 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-18.606 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-17.356 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-18.296 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-19.371 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-19.305 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-19.259 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-18.373 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-18.365 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-18.754 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-18.917 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-18.510 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-17.918 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-19.732 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-16.921 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-18.788 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-19.340 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-17.434 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-18.220 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-18.445 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-18.417 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-18.220 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-17.021 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-18.390 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-16.494 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-18.603 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-18.036 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-17.054 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-18.185 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-17.114 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-18.580 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-17.689 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-16.756 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-17.905 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-16.758 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-18.131 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-18.368 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-17.408 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-17.747 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-17.320 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-18.776 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-17.630 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-17.226 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-16.886 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-17.368 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-17.748 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-18.124 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-17.920 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-17.405 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-16.552 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-17.575 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-18.125 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-17.666 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-18.113 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-16.892 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-17.479 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-17.332 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-17.344 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-17.102 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-17.868 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-17.613 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-17.125 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-16.582 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-16.427 total time= 1.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-16.472 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-17.801 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-17.180 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-17.133 total time= 1.1s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-16.736 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-17.446 total time= 1.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-15.767 total time= 1.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-17.266 total time= 1.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-16.828 total time= 1.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-16.574 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-15.897 total time= 1.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-17.497 total time= 1.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-16.710 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-17.896 total time= 1.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-16.240 total time= 1.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-16.215 total time= 1.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-20.089 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-21.479 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-21.388 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-22.910 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.5;, score=-20.015 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-17.641 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-21.089 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-20.324 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-22.019 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-20.860 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-16.919 total time= 1.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.618;, score=-20.498 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-20.952 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-16.520 total time= 1.1s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-18.745 total time= 0.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-19.999 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-20.629 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=5, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-17.249 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.8;, score=-19.632 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-21.811 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-20.584 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-19.491 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-21.045 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-19.922 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.85;, score=-19.463 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-20.575 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-20.402 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-19.822 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-19.549 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.9;, score=-19.729 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-20.302 total time= 0.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-20.855 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-20.771 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-18.668 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=0.95;, score=-20.304 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-21.720 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-20.365 total time= 0.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-21.816 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=50, model1__subsample=1.0;, score=-19.611 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-16.872 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-19.410 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-18.787 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-18.167 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-17.087 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.5;, score=-18.946 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-18.090 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-18.850 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-17.629 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.618;, score=-18.301 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-17.527 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-18.324 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-18.447 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-17.955 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.8;, score=-18.907 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-17.756 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-18.918 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-17.355 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-18.505 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.85;, score=-17.398 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-19.006 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-17.570 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-19.175 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-17.798 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.9;, score=-18.168 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-17.368 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-17.660 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-18.448 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-17.300 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=0.95;, score=-17.767 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-18.322 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-18.336 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-18.277 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-18.436 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=100, model1__subsample=1.0;, score=-18.519 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-17.049 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-17.330 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-17.259 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-17.395 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.5;, score=-18.008 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-18.563 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-18.759 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-17.508 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-16.788 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.618;, score=-17.484 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-16.875 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-17.557 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-17.440 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-17.476 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.8;, score=-16.923 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-17.832 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-16.582 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-16.726 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-16.876 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.85;, score=-17.232 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-16.343 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-18.063 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-16.738 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-17.149 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.9;, score=-17.042 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-17.154 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-18.410 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-16.906 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-17.574 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=0.95;, score=-16.653 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-16.837 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-17.605 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-17.642 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-16.589 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=150, model1__subsample=1.0;, score=-16.535 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-16.853 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-17.406 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-16.934 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-17.200 total time= 0.6s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.5;, score=-17.212 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-16.236 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-17.501 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-17.584 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-16.623 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.618;, score=-16.413 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-17.275 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-16.983 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-15.768 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-16.005 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.8;, score=-16.255 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-15.421 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-17.067 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-17.159 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-15.976 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.85;, score=-16.567 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-16.101 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-17.112 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-17.069 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-16.620 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.9;, score=-16.912 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-15.875 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-16.858 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-15.931 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-16.579 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=0.95;, score=-15.571 total time= 1.1s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-19.046 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-16.116 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-19.398 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-16.983 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-19.048 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-18.628 total time= 0.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-18.299 total time= 0.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.5;, score=-19.605 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-19.361 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-18.207 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-17.438 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-16.731 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-17.990 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.618;, score=-18.230 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=log2, model1__n_estimators=200, model1__subsample=1.0;, score=-16.394 total time= 0.9s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-18.463 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-18.000 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-18.404 total time= 0.3s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-18.264 total time= 0.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.8;, score=-18.517 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-20.164 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-19.350 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-19.082 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-18.498 total time= 0.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.85;, score=-18.035 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-19.648 total time= 0.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-17.945 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-18.583 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-18.311 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.9;, score=-18.873 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-17.634 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-19.317 total time= 0.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-18.847 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-18.054 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=0.95;, score=-17.772 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-18.493 total time= 0.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-18.359 total time= 0.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-18.567 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-18.491 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=50, model1__subsample=1.0;, score=-18.602 total time= 0.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-16.540 total time= 0.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-17.905 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-18.621 total time= 0.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-16.371 total time= 0.5s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.5;, score=-17.664 total time= 0.5s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-17.735 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-16.456 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-16.241 total time= 0.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-17.616 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.618;, score=-16.920 total time= 0.5s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-16.589 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-17.718 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-17.243 total time= 0.5s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-16.845 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.8;, score=-16.693 total time= 0.6s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-16.087 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-16.803 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-17.833 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-16.099 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.85;, score=-16.895 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-16.060 total time= 0.7s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-17.655 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-16.907 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-16.840 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.9;, score=-16.917 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-16.204 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-17.014 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-16.008 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-17.255 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=0.95;, score=-16.659 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-16.507 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-17.528 total time= 0.7s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-16.797 total time= 0.7s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-16.774 total time= 0.7s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=100, model1__subsample=1.0;, score=-16.872 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-15.950 total time= 0.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-17.514 total time= 0.6s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-17.220 total time= 0.6s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-17.289 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.5;, score=-16.512 total time= 0.7s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-16.132 total time= 0.8s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-17.489 total time= 0.8s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-17.071 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-16.290 total time= 0.8s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.618;, score=-16.715 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-15.117 total time= 0.9s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-17.257 total time= 0.9s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-16.699 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-15.624 total time= 1.0s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.8;, score=-16.523 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-15.494 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-17.182 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-16.833 total time= 1.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-15.763 total time= 1.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.85;, score=-16.363 total time= 1.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-15.671 total time= 1.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-16.719 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-17.398 total time= 1.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-15.980 total time= 1.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.9;, score=-16.410 total time= 1.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-17.165 total time= 1.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-16.559 total time= 1.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-15.813 total time= 1.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-15.594 total time= 1.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=0.95;, score=-16.420 total time= 1.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-15.413 total time= 1.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-16.463 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-16.988 total time= 1.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-16.414 total time= 0.9s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-16.076 total time= 1.1s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-17.254 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=150, model1__subsample=1.0;, score=-16.670 total time= 1.1s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-16.561 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-16.570 total time= 0.8s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.5;, score=-16.262 total time= 0.8s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-14.915 total time= 1.0s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-16.578 total time= 1.0s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-16.617 total time= 0.9s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-16.567 total time= 1.0s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.618;, score=-15.417 total time= 1.0s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-15.474 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-16.980 total time= 1.2s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-16.383 total time= 1.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-16.658 total time= 1.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.8;, score=-16.071 total time= 1.2s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-15.455 total time= 1.2s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-16.539 total time= 1.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-16.162 total time= 1.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-15.336 total time= 1.3s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.85;, score=-16.263 total time= 1.3s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-15.428 total time= 1.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-16.856 total time= 1.3s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-16.516 total time= 1.3s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-15.464 total time= 1.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.9;, score=-15.622 total time= 1.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-15.290 total time= 1.5s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-16.766 total time= 1.6s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-16.314 total time= 1.4s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-15.581 total time= 1.4s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=0.95;, score=-16.311 total time= 1.4s\n", + "[CV 1/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-15.682 total time= 1.4s\n", + "[CV 2/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-16.456 total time= 1.4s\n", + "[CV 3/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-16.420 total time= 1.2s\n", + "[CV 4/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-16.117 total time= 1.2s\n", + "[CV 5/5] END model1__criterion=friedman_mse, model1__learning_rate=0.2, model1__max_depth=8, model1__max_features=sqrt, model1__n_estimators=200, model1__subsample=1.0;, score=-16.080 total time= 1.0s\n" + ] + }, + { + "data": { + "text/html": [ + "
GridSearchCV(cv=5,\n",
+       "             estimator=Pipeline(steps=[('Data_processing',\n",
+       "                                        Pipeline(steps=[('step1',\n",
+       "                                                         ColumnTransformer(remainder='passthrough',\n",
+       "                                                                           transformers=[('col_tnf',\n",
+       "                                                                                          OneHotEncoder(drop='first',\n",
+       "                                                                                                        sparse_output=False),\n",
+       "                                                                                          [0,\n",
+       "                                                                                           2])])),\n",
+       "                                                        ('step2',\n",
+       "                                                         StandardScaler())])),\n",
+       "                                       ('model1',\n",
+       "                                        GradientBoostingRegressor())]),\n",
+       "             n_jobs=-1,\n",
+       "             param_grid={'model1__criterion': ['friedman_mse'],\n",
+       "                         'model1__learning_rate': [0.01, 0.025, 0.05, 0.075,\n",
+       "                                                   0.1, 0.15, 0.2],\n",
+       "                         'model1__max_depth': [3, 5, 8],\n",
+       "                         'model1__max_features': ['log2', 'sqrt'],\n",
+       "                         'model1__n_estimators': [50, 100, 150, 200],\n",
+       "                         'model1__subsample': [0.5, 0.618, 0.8, 0.85, 0.9, 0.95,\n",
+       "                                               1.0]},\n",
+       "             scoring='neg_mean_absolute_error', verbose=3)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" + ], + "text/plain": [ + "GridSearchCV(cv=5,\n", + " estimator=Pipeline(steps=[('Data_processing',\n", + " Pipeline(steps=[('step1',\n", + " ColumnTransformer(remainder='passthrough',\n", + " transformers=[('col_tnf',\n", + " OneHotEncoder(drop='first',\n", + " sparse_output=False),\n", + " [0,\n", + " 2])])),\n", + " ('step2',\n", + " StandardScaler())])),\n", + " ('model1',\n", + " GradientBoostingRegressor())]),\n", + " n_jobs=-1,\n", + " param_grid={'model1__criterion': ['friedman_mse'],\n", + " 'model1__learning_rate': [0.01, 0.025, 0.05, 0.075,\n", + " 0.1, 0.15, 0.2],\n", + " 'model1__max_depth': [3, 5, 8],\n", + " 'model1__max_features': ['log2', 'sqrt'],\n", + " 'model1__n_estimators': [50, 100, 150, 200],\n", + " 'model1__subsample': [0.5, 0.618, 0.8, 0.85, 0.9, 0.95,\n", + " 1.0]},\n", + " scoring='neg_mean_absolute_error', verbose=3)" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model1 = GradientBoostingRegressor()\n", + "model1_pipe = Pipeline([('Data_processing' , data_pipeline) , ('model1' , model1)])\n", + "parameters = {\n", + " \"model1__learning_rate\": [0.01, 0.025, 0.05, 0.075, 0.1, 0.15, 0.2],\n", + " \"model1__max_depth\":[3,5,8],\n", + " \"model1__max_features\":[\"log2\",\"sqrt\"],\n", + " \"model1__criterion\": [\"friedman_mse\"],\n", + " \"model1__subsample\":[0.5, 0.618, 0.8, 0.85, 0.9, 0.95, 1.0],\n", + " \"model1__n_estimators\":[50, 100, 150, 200]\n", + "}\n", + "\n", + "gscv1 = GridSearchCV(model1_pipe , parameters , scoring='neg_mean_absolute_error' , cv = 5 , n_jobs=-1 , verbose = 3)\n", + "gscv1.fit(x_train , y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Pipeline(steps=[('Data_processing',\n", + " Pipeline(steps=[('step1',\n", + " ColumnTransformer(remainder='passthrough',\n", + " transformers=[('col_tnf',\n", + " OneHotEncoder(drop='first',\n", + " sparse_output=False),\n", + " [0, 2])])),\n", + " ('step2', StandardScaler())])),\n", + " ('model1',\n", + " GradientBoostingRegressor(learning_rate=0.15, max_depth=8,\n", + " max_features='sqrt',\n", + " n_estimators=200, subsample=0.85))])\n", + "--------------------\n", + "Best score :-15.883028237152882\n" + ] + } + ], + "source": [ + "print(gscv1.best_estimator_)\n", + "print('--'*10)\n", + "print(f'Best score :{gscv1.best_score_}')" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Fitting 5 folds for each of 84 candidates, totalling 420 fits\n", + "[CV 2/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=50;, score=-26.372 total time= 2.1s\n", + "[CV 5/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=50;, score=-27.088 total time= 2.1s\n", + "[CV 3/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=50;, score=-26.715 total time= 2.1s\n", + "[CV 1/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=50;, score=-25.348 total time= 2.2s\n", + "[CV 4/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=50;, score=-25.086 total time= 2.2s\n", + "[CV 2/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=100;, score=-26.744 total time= 4.0s\n", + "[CV 1/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=100;, score=-25.348 total time= 4.2s\n", + "[CV 3/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=100;, score=-26.622 total time= 4.3s\n", + "[CV 5/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=100;, score=-26.748 total time= 3.8s\n", + "[CV 4/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=100;, score=-25.202 total time= 4.0s\n", + "[CV 2/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=150;, score=-26.890 total time= 5.8s\n", + "[CV 3/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=150;, score=-26.645 total time= 5.9s\n", + "[CV 1/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=150;, score=-25.387 total time= 6.3s\n", + "[CV 4/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=150;, score=-24.894 total time= 6.1s\n", + "[CV 5/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=150;, score=-26.645 total time= 5.9s\n", + "[CV 1/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=50;, score=-24.991 total time= 1.9s\n", + "[CV 2/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=50;, score=-26.346 total time= 1.8s\n", + "[CV 3/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=50;, score=-26.766 total time= 1.8s\n", + "[CV 1/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=200;, score=-25.515 total time= 7.7s\n", + "[CV 4/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=50;, score=-25.298 total time= 1.9s\n", + "[CV 2/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=200;, score=-26.891 total time= 7.6s\n", + "[CV 3/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=200;, score=-26.532 total time= 7.6s\n", + "[CV 5/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=50;, score=-27.005 total time= 2.2s\n", + "[CV 1/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=100;, score=-25.314 total time= 3.7s\n", + "[CV 2/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=100;, score=-26.803 total time= 3.8s\n", + "[CV 5/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=200;, score=-26.698 total time= 7.8s\n", + "[CV 3/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=100;, score=-26.577 total time= 3.8s\n", + "[CV 4/5] END model2__learning_rate=0.01, model2__loss=linear, model2__n_estimators=200;, score=-24.803 total time= 8.2s\n", + "[CV 4/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=100;, score=-25.254 total time= 3.7s\n", + "[CV 5/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=100;, score=-26.913 total time= 4.0s\n", + "[CV 1/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=150;, score=-25.258 total time= 5.9s\n", + "[CV 2/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=150;, score=-26.809 total time= 6.5s\n", + "[CV 3/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=150;, score=-26.447 total time= 6.8s\n", + "[CV 4/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=150;, score=-24.951 total time= 7.1s\n", + "[CV 5/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=150;, score=-26.679 total time= 7.2s\n", + "[CV 1/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=50;, score=-25.386 total time= 2.4s\n", + "[CV 1/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=200;, score=-25.422 total time= 9.3s\n", + "[CV 2/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=50;, score=-26.250 total time= 2.5s\n", + "[CV 3/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=50;, score=-26.737 total time= 2.4s\n", + "[CV 2/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=200;, score=-26.686 total time= 9.2s\n", + "[CV 3/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=200;, score=-26.658 total time= 9.2s\n", + "[CV 4/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=50;, score=-25.580 total time= 1.9s\n", + "[CV 5/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=50;, score=-26.830 total time= 1.9s\n", + "[CV 4/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=200;, score=-25.116 total time= 9.0s\n", + "[CV 2/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=100;, score=-26.602 total time= 3.6s\n", + "[CV 1/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=100;, score=-25.356 total time= 4.1s\n", + "[CV 3/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=100;, score=-26.684 total time= 3.8s\n", + "[CV 5/5] END model2__learning_rate=0.01, model2__loss=square, model2__n_estimators=200;, score=-27.227 total time= 8.6s\n", + "[CV 4/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=100;, score=-25.274 total time= 4.0s\n", + "[CV 5/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=100;, score=-26.652 total time= 3.8s\n", + "[CV 1/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=150;, score=-25.268 total time= 5.7s\n", + "[CV 2/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=150;, score=-26.732 total time= 5.9s\n", + "[CV 3/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=150;, score=-26.630 total time= 5.9s\n", + "[CV 4/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=150;, score=-24.954 total time= 6.1s\n", + "[CV 5/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=150;, score=-26.748 total time= 6.1s\n", + "[CV 1/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=50;, score=-25.364 total time= 1.9s\n", + "[CV 2/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=50;, score=-26.787 total time= 1.8s\n", + "[CV 3/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=50;, score=-26.749 total time= 1.9s\n", + "[CV 1/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=200;, score=-25.473 total time= 7.9s\n", + "[CV 2/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=200;, score=-26.736 total time= 8.0s\n", + "[CV 3/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=200;, score=-26.548 total time= 8.2s\n", + "[CV 4/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=50;, score=-24.982 total time= 1.9s\n", + "[CV 5/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=50;, score=-26.811 total time= 2.0s\n", + "[CV 4/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=200;, score=-24.844 total time= 7.9s\n", + "[CV 1/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=100;, score=-25.591 total time= 3.9s\n", + "[CV 5/5] END model2__learning_rate=0.01, model2__loss=exponential, model2__n_estimators=200;, score=-26.769 total time= 7.4s\n", + "[CV 2/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=100;, score=-26.933 total time= 3.7s\n", + "[CV 3/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=100;, score=-26.444 total time= 3.8s\n", + "[CV 4/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=100;, score=-24.917 total time= 3.8s\n", + "[CV 5/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=100;, score=-26.747 total time= 3.9s\n", + "[CV 1/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=150;, score=-25.888 total time= 5.9s\n", + "[CV 2/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=150;, score=-27.203 total time= 6.1s\n", + "[CV 3/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=150;, score=-27.176 total time= 6.4s\n", + "[CV 4/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=150;, score=-25.419 total time= 6.2s\n", + "[CV 5/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=150;, score=-27.821 total time= 6.3s\n", + "[CV 2/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=50;, score=-26.879 total time= 2.0s\n", + "[CV 1/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=50;, score=-25.002 total time= 2.1s\n", + "[CV 3/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=50;, score=-26.390 total time= 1.9s\n", + "[CV 3/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=200;, score=-27.587 total time= 7.9s\n", + "[CV 2/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=200;, score=-27.336 total time= 8.0s\n", + "[CV 1/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=200;, score=-26.051 total time= 8.4s\n", + "[CV 5/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=50;, score=-26.822 total time= 2.0s\n", + "[CV 4/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=50;, score=-24.807 total time= 2.0s\n", + "[CV 4/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=200;, score=-25.302 total time= 7.9s\n", + "[CV 1/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=100;, score=-25.628 total time= 4.2s\n", + "[CV 2/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=100;, score=-26.727 total time= 4.1s\n", + "[CV 3/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=100;, score=-26.781 total time= 4.2s\n", + "[CV 4/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=100;, score=-25.207 total time= 4.1s\n", + "[CV 5/5] END model2__learning_rate=0.025, model2__loss=linear, model2__n_estimators=200;, score=-28.541 total time= 8.7s\n", + "[CV 5/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=100;, score=-27.716 total time= 4.0s\n", + "[CV 1/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=150;, score=-26.616 total time= 5.9s\n", + "[CV 2/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=150;, score=-27.046 total time= 6.2s\n", + "[CV 3/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=150;, score=-28.370 total time= 6.1s\n", + "[CV 4/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=150;, score=-26.414 total time= 6.2s\n", + "[CV 5/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=150;, score=-29.287 total time= 6.3s\n", + "[CV 1/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=50;, score=-25.198 total time= 2.0s\n", + "[CV 2/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=50;, score=-26.655 total time= 1.8s\n", + "[CV 1/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=200;, score=-26.720 total time= 7.8s\n", + "[CV 3/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=50;, score=-27.133 total time= 2.0s\n", + "[CV 2/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=200;, score=-28.136 total time= 8.0s\n", + "[CV 3/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=200;, score=-28.638 total time= 8.0s\n", + "[CV 4/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=50;, score=-25.101 total time= 2.0s\n", + "[CV 5/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=50;, score=-26.817 total time= 1.9s\n", + "[CV 4/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=200;, score=-26.590 total time= 7.5s\n", + "[CV 1/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=100;, score=-25.408 total time= 4.0s\n", + "[CV 5/5] END model2__learning_rate=0.025, model2__loss=square, model2__n_estimators=200;, score=-28.912 total time= 7.6s\n", + "[CV 3/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=100;, score=-26.572 total time= 3.6s\n", + "[CV 2/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=100;, score=-26.907 total time= 4.0s\n", + "[CV 4/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=100;, score=-24.833 total time= 3.8s\n", + "[CV 5/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=100;, score=-26.936 total time= 4.1s\n", + "[CV 1/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=150;, score=-25.826 total time= 5.9s\n", + "[CV 2/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=150;, score=-27.032 total time= 6.0s\n", + "[CV 4/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=150;, score=-24.995 total time= 5.7s\n", + "[CV 3/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=150;, score=-26.583 total time= 5.9s\n", + "[CV 5/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=150;, score=-26.968 total time= 6.1s\n", + "[CV 1/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=50;, score=-25.717 total time= 1.9s\n", + "[CV 2/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=50;, score=-27.099 total time= 2.0s\n", + "[CV 3/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=50;, score=-26.506 total time= 1.8s\n", + "[CV 1/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=200;, score=-26.097 total time= 8.0s\n", + "[CV 2/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=200;, score=-27.395 total time= 7.3s\n", + "[CV 3/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=200;, score=-27.245 total time= 7.5s\n", + "[CV 4/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=50;, score=-24.930 total time= 2.0s\n", + "[CV 5/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=50;, score=-26.646 total time= 1.9s\n", + "[CV 4/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=200;, score=-25.398 total time= 7.9s\n", + "[CV 1/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=100;, score=-26.074 total time= 3.7s\n", + "[CV 2/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=100;, score=-27.306 total time= 3.8s\n", + "[CV 5/5] END model2__learning_rate=0.025, model2__loss=exponential, model2__n_estimators=200;, score=-27.452 total time= 7.6s\n", + "[CV 3/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=100;, score=-27.591 total time= 3.9s\n", + "[CV 4/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=100;, score=-25.225 total time= 3.6s\n", + "[CV 5/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=100;, score=-28.105 total time= 3.8s\n", + "[CV 1/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=150;, score=-26.989 total time= 5.6s\n", + "[CV 2/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=150;, score=-28.638 total time= 5.1s\n", + "[CV 3/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=150;, score=-29.079 total time= 5.5s\n", + "[CV 4/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=150;, score=-26.515 total time= 5.4s\n", + "[CV 5/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=150;, score=-29.297 total time= 5.7s\n", + "[CV 1/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=50;, score=-25.436 total time= 1.9s\n", + "[CV 2/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=50;, score=-27.036 total time= 1.7s\n", + "[CV 1/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=200;, score=-26.971 total time= 7.1s\n", + "[CV 2/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=200;, score=-29.073 total time= 7.0s\n", + "[CV 3/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=50;, score=-26.669 total time= 2.1s\n", + "[CV 3/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=200;, score=-29.721 total time= 7.2s\n", + "[CV 4/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=50;, score=-25.134 total time= 2.0s\n", + "[CV 5/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=50;, score=-27.369 total time= 2.0s\n", + "[CV 4/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=200;, score=-26.742 total time= 7.5s\n", + "[CV 1/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=100;, score=-26.845 total time= 3.7s\n", + "[CV 2/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=100;, score=-28.270 total time= 3.7s\n", + "[CV 3/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=100;, score=-28.576 total time= 3.9s\n", + "[CV 5/5] END model2__learning_rate=0.05, model2__loss=linear, model2__n_estimators=200;, score=-29.225 total time= 7.6s\n", + "[CV 4/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=100;, score=-26.877 total time= 4.0s\n", + "[CV 5/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=100;, score=-29.187 total time= 3.9s\n", + "[CV 1/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=150;, score=-26.872 total time= 6.1s\n", + "[CV 2/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=150;, score=-28.735 total time= 6.1s\n", + "[CV 3/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=150;, score=-29.280 total time= 6.2s\n", + "[CV 4/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=150;, score=-26.721 total time= 6.2s\n", + "[CV 5/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=150;, score=-29.001 total time= 6.4s\n", + "[CV 1/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=50;, score=-25.659 total time= 2.3s\n", + "[CV 1/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=200;, score=-27.080 total time= 8.0s\n", + "[CV 2/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=50;, score=-26.975 total time= 2.5s\n", + "[CV 2/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=200;, score=-28.544 total time= 8.0s\n", + "[CV 3/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=50;, score=-26.439 total time= 2.3s\n", + "[CV 3/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=200;, score=-29.546 total time= 8.5s\n", + "[CV 4/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=50;, score=-24.858 total time= 2.2s\n", + "[CV 5/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=50;, score=-26.853 total time= 2.2s\n", + "[CV 4/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=200;, score=-26.514 total time= 8.0s\n", + "[CV 1/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=100;, score=-25.829 total time= 4.2s\n", + "[CV 2/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=100;, score=-27.257 total time= 4.2s\n", + "[CV 3/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=100;, score=-27.179 total time= 4.1s\n", + "[CV 5/5] END model2__learning_rate=0.05, model2__loss=square, model2__n_estimators=200;, score=-28.813 total time= 8.1s\n", + "[CV 4/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=100;, score=-25.305 total time= 4.3s\n", + "[CV 5/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=100;, score=-27.313 total time= 4.3s\n", + "[CV 1/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=150;, score=-26.909 total time= 6.4s\n", + "[CV 2/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=150;, score=-27.855 total time= 6.2s\n", + "[CV 3/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=150;, score=-27.931 total time= 6.1s\n", + "[CV 4/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=150;, score=-26.456 total time= 6.6s\n", + "[CV 5/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=150;, score=-29.084 total time= 6.4s\n", + "[CV 1/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=50;, score=-25.876 total time= 2.1s\n", + "[CV 1/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=200;, score=-27.229 total time= 8.2s\n", + "[CV 2/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=50;, score=-27.411 total time= 1.9s\n", + "[CV 3/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=50;, score=-27.004 total time= 2.1s\n", + "[CV 2/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=200;, score=-28.374 total time= 8.3s\n", + "[CV 3/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=200;, score=-29.248 total time= 8.3s\n", + "[CV 4/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=50;, score=-25.397 total time= 2.3s\n", + "[CV 5/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=50;, score=-26.989 total time= 2.3s\n", + "[CV 4/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=200;, score=-26.862 total time= 8.2s\n", + "[CV 1/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=100;, score=-26.618 total time= 4.0s\n", + "[CV 2/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=100;, score=-28.514 total time= 4.1s\n", + "[CV 5/5] END model2__learning_rate=0.05, model2__loss=exponential, model2__n_estimators=200;, score=-29.431 total time= 8.1s\n", + "[CV 3/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=100;, score=-29.250 total time= 4.1s\n", + "[CV 4/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=100;, score=-26.471 total time= 4.3s\n", + "[CV 5/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=100;, score=-28.832 total time= 4.1s\n", + "[CV 1/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=150;, score=-26.906 total time= 5.8s\n", + "[CV 2/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=150;, score=-29.573 total time= 6.0s\n", + "[CV 3/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=150;, score=-29.823 total time= 6.2s\n", + "[CV 4/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=150;, score=-26.744 total time= 6.2s\n", + "[CV 1/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=200;, score=-27.169 total time= 5.8s\n", + "[CV 5/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=150;, score=-29.435 total time= 6.5s\n", + "[CV 1/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=50;, score=-26.897 total time= 2.4s\n", + "[CV 2/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=50;, score=-26.937 total time= 2.3s\n", + "[CV 2/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=200;, score=-29.870 total time= 7.4s\n", + "[CV 3/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=50;, score=-28.102 total time= 2.5s\n", + "[CV 4/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=50;, score=-25.168 total time= 2.6s\n", + "[CV 4/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=200;, score=-26.520 total time= 6.0s\n", + "[CV 3/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=200;, score=-30.599 total time= 8.4s\n", + "[CV 5/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=50;, score=-29.373 total time= 2.4s\n", + "[CV 1/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=100;, score=-27.103 total time= 4.1s\n", + "[CV 2/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=100;, score=-28.695 total time= 4.1s\n", + "[CV 5/5] END model2__learning_rate=0.075, model2__loss=linear, model2__n_estimators=200;, score=-29.580 total time= 7.7s\n", + "[CV 3/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=100;, score=-29.037 total time= 4.0s\n", + "[CV 4/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=100;, score=-27.283 total time= 4.1s\n", + "[CV 5/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=100;, score=-29.050 total time= 4.2s\n", + "[CV 1/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=150;, score=-27.005 total time= 5.9s\n", + "[CV 2/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=150;, score=-28.830 total time= 6.1s\n", + "[CV 3/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=150;, score=-29.510 total time= 5.9s\n", + "[CV 4/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=150;, score=-27.172 total time= 6.3s\n", + "[CV 5/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=150;, score=-29.082 total time= 6.6s\n", + "[CV 1/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=50;, score=-25.923 total time= 2.5s\n", + "[CV 2/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=200;, score=-29.138 total time= 8.1s\n", + "[CV 2/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=50;, score=-27.028 total time= 2.4s\n", + "[CV 3/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=50;, score=-26.606 total time= 2.4s\n", + "[CV 1/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=200;, score=-27.365 total time= 9.2s\n", + "[CV 3/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=200;, score=-30.241 total time= 9.1s\n", + "[CV 4/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=50;, score=-24.863 total time= 2.9s\n", + "[CV 5/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=50;, score=-27.079 total time= 3.1s\n", + "[CV 4/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=200;, score=-26.523 total time= 9.9s\n", + "[CV 5/5] END model2__learning_rate=0.075, model2__loss=square, model2__n_estimators=200;, score=-29.318 total time= 9.9s\n", + "[CV 1/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=100;, score=-25.943 total time= 5.9s\n", + "[CV 2/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=100;, score=-27.944 total time= 5.7s\n", + "[CV 3/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=100;, score=-27.708 total time= 5.6s\n", + "[CV 4/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=100;, score=-26.430 total time= 6.0s\n", + "[CV 5/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=100;, score=-28.646 total time= 6.1s\n", + "[CV 1/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=150;, score=-27.389 total time= 7.7s\n", + "[CV 2/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=150;, score=-29.762 total time= 6.8s\n", + "[CV 3/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=150;, score=-29.792 total time= 6.7s\n", + "[CV 4/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=150;, score=-27.048 total time= 6.6s\n", + "[CV 5/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=150;, score=-29.571 total time= 7.1s\n", + "[CV 1/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=50;, score=-26.658 total time= 2.0s\n", + "[CV 2/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=50;, score=-27.466 total time= 1.9s\n", + "[CV 1/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=200;, score=-27.924 total time= 8.4s\n", + "[CV 2/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=200;, score=-30.876 total time= 7.5s\n", + "[CV 3/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=50;, score=-27.306 total time= 2.0s\n", + "[CV 4/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=50;, score=-25.437 total time= 2.1s\n", + "[CV 3/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=200;, score=-31.075 total time= 7.9s\n", + "[CV 5/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=50;, score=-28.778 total time= 2.2s\n", + "[CV 4/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=200;, score=-27.601 total time= 8.3s\n", + "[CV 2/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=100;, score=-29.409 total time= 4.2s\n", + "[CV 1/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=100;, score=-26.418 total time= 4.6s\n", + "[CV 5/5] END model2__learning_rate=0.075, model2__loss=exponential, model2__n_estimators=200;, score=-29.966 total time= 8.3s\n", + "[CV 3/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=100;, score=-29.512 total time= 4.4s\n", + "[CV 4/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=100;, score=-26.786 total time= 4.6s\n", + "[CV 5/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=100;, score=-29.130 total time= 4.6s\n", + "[CV 1/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=150;, score=-27.319 total time= 4.5s\n", + "[CV 4/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=150;, score=-26.593 total time= 4.7s\n", + "[CV 1/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=200;, score=-26.848 total time= 4.5s\n", + "[CV 2/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=150;, score=-29.988 total time= 5.3s\n", + "[CV 5/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=150;, score=-29.264 total time= 5.0s\n", + "[CV 3/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=150;, score=-30.200 total time= 6.3s\n", + "[CV 2/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=200;, score=-29.540 total time= 5.0s\n", + "[CV 4/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=200;, score=-26.805 total time= 4.9s\n", + "[CV 1/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=50;, score=-26.922 total time= 2.3s\n", + "[CV 2/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=50;, score=-28.483 total time= 2.4s\n", + "[CV 3/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=50;, score=-28.846 total time= 2.4s\n", + "[CV 3/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=200;, score=-30.674 total time= 6.6s\n", + "[CV 4/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=50;, score=-27.086 total time= 2.5s\n", + "[CV 5/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=50;, score=-29.395 total time= 2.4s\n", + "[CV 5/5] END model2__learning_rate=0.1, model2__loss=linear, model2__n_estimators=200;, score=-29.650 total time= 5.6s\n", + "[CV 1/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=100;, score=-27.133 total time= 4.6s\n", + "[CV 2/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=100;, score=-28.815 total time= 4.8s\n", + "[CV 3/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=100;, score=-28.877 total time= 4.9s\n", + "[CV 4/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=100;, score=-27.097 total time= 5.0s\n", + "[CV 5/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=100;, score=-28.623 total time= 5.0s\n", + "[CV 2/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=150;, score=-29.527 total time= 6.5s\n", + "[CV 1/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=150;, score=-27.396 total time= 6.5s\n", + "[CV 1/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=200;, score=-27.143 total time= 4.5s\n", + "[CV 3/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=150;, score=-30.140 total time= 6.9s\n", + "[CV 4/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=150;, score=-26.424 total time= 6.4s\n", + "[CV 5/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=150;, score=-29.732 total time= 6.7s\n", + "[CV 1/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=50;, score=-25.902 total time= 2.2s\n", + "[CV 2/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=50;, score=-27.178 total time= 2.2s\n", + "[CV 3/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=50;, score=-26.940 total time= 2.2s\n", + "[CV 2/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=200;, score=-30.017 total time= 8.1s\n", + "[CV 4/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=50;, score=-25.352 total time= 2.5s\n", + "[CV 5/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=50;, score=-27.355 total time= 2.4s\n", + "[CV 3/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=200;, score=-30.277 total time= 8.7s\n", + "[CV 1/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=100;, score=-27.081 total time= 4.6s\n", + "[CV 4/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=200;, score=-26.679 total time= 8.9s\n", + "[CV 5/5] END model2__learning_rate=0.1, model2__loss=square, model2__n_estimators=200;, score=-31.132 total time= 9.0s\n", + "[CV 2/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=100;, score=-29.336 total time= 4.8s\n", + "[CV 3/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=100;, score=-29.367 total time= 5.0s\n", + "[CV 4/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=100;, score=-26.544 total time= 4.9s\n", + "[CV 5/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=100;, score=-29.363 total time= 5.0s\n", + "[CV 1/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=150;, score=-28.340 total time= 7.0s\n", + "[CV 2/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=150;, score=-30.323 total time= 6.5s\n", + "[CV 4/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=150;, score=-27.793 total time= 6.4s\n", + "[CV 3/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=150;, score=-30.548 total time= 6.9s\n", + "[CV 5/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=150;, score=-30.186 total time= 7.0s\n", + "[CV 1/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=50;, score=-26.800 total time= 2.4s\n", + "[CV 2/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=50;, score=-28.015 total time= 2.1s\n", + "[CV 3/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=50;, score=-29.107 total time= 2.2s\n", + "[CV 1/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=200;, score=-29.185 total time= 8.7s\n", + "[CV 2/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=200;, score=-31.752 total time= 8.5s\n", + "[CV 3/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=200;, score=-32.065 total time= 8.5s\n", + "[CV 4/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=50;, score=-26.944 total time= 2.1s\n", + "[CV 5/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=50;, score=-29.014 total time= 2.1s\n", + "[CV 1/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=100;, score=-26.938 total time= 3.2s\n", + "[CV 4/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=200;, score=-28.113 total time= 8.4s\n", + "[CV 2/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=100;, score=-29.185 total time= 3.3s\n", + "[CV 4/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=100;, score=-26.793 total time= 3.0s\n", + "[CV 1/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=150;, score=-27.100 total time= 2.9s\n", + "[CV 3/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=100;, score=-30.317 total time= 4.0s\n", + "[CV 5/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=100;, score=-29.459 total time= 3.4s\n", + "[CV 5/5] END model2__learning_rate=0.1, model2__loss=exponential, model2__n_estimators=200;, score=-30.882 total time= 8.3s\n", + "[CV 2/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=150;, score=-29.733 total time= 3.2s\n", + "[CV 4/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=150;, score=-26.855 total time= 3.0s\n", + "[CV 3/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=150;, score=-30.200 total time= 3.8s\n", + "[CV 1/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=200;, score=-27.234 total time= 2.9s\n", + "[CV 5/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=150;, score=-29.424 total time= 3.5s\n", + "[CV 4/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=200;, score=-26.725 total time= 3.4s\n", + "[CV 3/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=200;, score=-29.931 total time= 4.0s\n", + "[CV 1/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=50;, score=-26.711 total time= 2.2s\n", + "[CV 2/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=50;, score=-28.741 total time= 1.9s\n", + "[CV 2/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=200;, score=-30.120 total time= 4.4s\n", + "[CV 3/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=50;, score=-29.135 total time= 2.1s\n", + "[CV 4/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=50;, score=-27.871 total time= 2.1s\n", + "[CV 5/5] END model2__learning_rate=0.15, model2__loss=linear, model2__n_estimators=200;, score=-29.226 total time= 3.4s\n", + "[CV 5/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=50;, score=-28.892 total time= 2.1s\n", + "[CV 2/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=100;, score=-28.994 total time= 3.9s\n", + "[CV 1/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=100;, score=-27.825 total time= 4.1s\n", + "[CV 3/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=100;, score=-29.971 total time= 4.0s\n", + "[CV 5/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=100;, score=-29.868 total time= 4.1s\n", + "[CV 4/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=100;, score=-27.004 total time= 4.3s\n", + "[CV 1/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=150;, score=-28.126 total time= 5.1s\n", + "[CV 2/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=150;, score=-31.275 total time= 5.4s\n", + "[CV 3/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=150;, score=-30.378 total time= 5.8s\n", + "[CV 1/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=200;, score=-27.669 total time= 3.3s\n", + "[CV 2/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=50;, score=-28.071 total time= 1.9s\n", + "[CV 1/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=50;, score=-26.720 total time= 2.1s\n", + "[CV 4/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=150;, score=-26.776 total time= 5.6s\n", + "[CV 5/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=150;, score=-31.601 total time= 5.6s\n", + "[CV 3/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=50;, score=-27.730 total time= 2.1s\n", + "[CV 2/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=200;, score=-35.911 total time= 7.0s\n", + "[CV 4/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=50;, score=-25.381 total time= 2.2s\n", + "[CV 4/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=200;, score=-26.689 total time= 5.8s\n", + "[CV 5/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=50;, score=-28.791 total time= 2.2s\n", + "[CV 3/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=200;, score=-30.667 total time= 7.3s\n", + "[CV 5/5] END model2__learning_rate=0.15, model2__loss=square, model2__n_estimators=200;, score=-34.106 total time= 7.2s\n", + "[CV 1/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=100;, score=-28.081 total time= 4.3s\n", + "[CV 2/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=100;, score=-30.827 total time= 4.1s\n", + "[CV 3/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=100;, score=-30.774 total time= 4.4s\n", + "[CV 4/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=100;, score=-27.432 total time= 4.5s\n", + "[CV 5/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=100;, score=-29.845 total time= 4.5s\n", + "[CV 2/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=150;, score=-33.362 total time= 6.1s\n", + "[CV 1/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=150;, score=-29.644 total time= 6.4s\n", + "[CV 3/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=150;, score=-32.834 total time= 6.1s\n", + "[CV 4/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=150;, score=-29.157 total time= 6.4s\n", + "[CV 5/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=150;, score=-31.698 total time= 6.0s\n", + "[CV 1/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=50;, score=-27.303 total time= 2.0s\n", + "[CV 2/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=50;, score=-29.153 total time= 2.0s\n", + "[CV 2/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=200;, score=-38.467 total time= 7.6s\n", + "[CV 3/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=50;, score=-29.147 total time= 2.1s\n", + "[CV 1/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=200;, score=-31.899 total time= 7.9s\n", + "[CV 4/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=50;, score=-26.414 total time= 2.2s\n", + "[CV 3/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=200;, score=-37.271 total time= 7.8s\n", + "[CV 5/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=50;, score=-29.346 total time= 2.1s\n", + "[CV 5/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=200;, score=-35.352 total time= 7.6s\n", + "[CV 1/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=100;, score=-27.731 total time= 2.2s\n", + "[CV 4/5] END model2__learning_rate=0.15, model2__loss=exponential, model2__n_estimators=200;, score=-31.143 total time= 7.9s\n", + "[CV 4/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=100;, score=-26.814 total time= 2.2s\n", + "[CV 2/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=100;, score=-29.735 total time= 2.6s\n", + "[CV 5/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=100;, score=-29.852 total time= 2.4s\n", + "[CV 1/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=150;, score=-27.222 total time= 2.0s\n", + "[CV 3/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=100;, score=-29.899 total time= 3.1s\n", + "[CV 4/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=150;, score=-27.079 total time= 2.0s\n", + "[CV 2/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=150;, score=-29.628 total time= 2.5s\n", + "[CV 5/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=150;, score=-29.230 total time= 2.1s\n", + "[CV 3/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=150;, score=-30.047 total time= 2.5s\n", + "[CV 1/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=200;, score=-27.010 total time= 2.3s\n", + "[CV 4/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=200;, score=-26.844 total time= 2.3s\n", + "[CV 3/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=200;, score=-30.440 total time= 2.9s\n", + "[CV 2/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=200;, score=-29.900 total time= 3.3s\n", + "[CV 2/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=50;, score=-28.398 total time= 2.0s\n", + "[CV 3/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=50;, score=-30.276 total time= 2.0s\n", + "[CV 1/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=50;, score=-26.829 total time= 2.2s\n", + "[CV 5/5] END model2__learning_rate=0.2, model2__loss=linear, model2__n_estimators=200;, score=-29.852 total time= 2.8s\n", + "[CV 4/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=50;, score=-26.690 total time= 2.1s\n", + "[CV 5/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=50;, score=-28.866 total time= 2.1s\n", + "[CV 1/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=100;, score=-26.860 total time= 2.2s\n", + "[CV 2/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=100;, score=-30.215 total time= 3.7s\n", + "[CV 3/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=100;, score=-30.178 total time= 4.3s\n", + "[CV 4/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=100;, score=-26.595 total time= 4.3s\n", + "[CV 5/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=100;, score=-30.584 total time= 4.2s\n", + "[CV 1/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=150;, score=-28.027 total time= 4.4s\n", + "[CV 2/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=150;, score=-33.914 total time= 5.9s\n", + "[CV 3/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=150;, score=-30.750 total time= 6.2s\n", + "[CV 4/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=150;, score=-27.549 total time= 6.3s\n", + "[CV 1/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=200;, score=-28.548 total time= 4.3s\n", + "[CV 5/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=150;, score=-33.242 total time= 5.9s\n", + "[CV 1/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=50;, score=-27.374 total time= 2.1s\n", + "[CV 2/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=50;, score=-29.672 total time= 2.2s\n", + "[CV 4/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=200;, score=-27.443 total time= 5.3s\n", + "[CV 3/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=50;, score=-29.363 total time= 2.2s\n", + "[CV 2/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=200;, score=-46.436 total time= 6.8s\n", + "[CV 4/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=50;, score=-26.355 total time= 2.0s\n", + "[CV 5/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=50;, score=-29.277 total time= 2.2s\n", + "[CV 3/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=200;, score=-31.668 total time= 7.7s\n", + "[CV 5/5] END model2__learning_rate=0.2, model2__loss=square, model2__n_estimators=200;, score=-42.953 total time= 7.4s\n", + "[CV 1/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=100;, score=-29.277 total time= 4.2s\n", + "[CV 2/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=100;, score=-31.727 total time= 4.1s\n", + "[CV 3/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=100;, score=-32.275 total time= 4.1s\n", + "[CV 5/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=100;, score=-31.129 total time= 4.0s\n", + "[CV 4/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=100;, score=-28.799 total time= 4.4s\n", + "[CV 1/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=150;, score=-31.904 total time= 5.8s\n", + "[CV 2/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=150;, score=-37.566 total time= 5.4s\n", + "[CV 3/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=150;, score=-36.363 total time= 5.5s\n", + "[CV 5/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=150;, score=-33.962 total time= 5.4s\n", + "[CV 4/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=150;, score=-31.493 total time= 5.7s\n", + "[CV 2/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=200;, score=-52.550 total time= 6.0s\n", + "[CV 1/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=200;, score=-34.798 total time= 6.3s\n", + "[CV 3/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=200;, score=-39.547 total time= 6.0s\n", + "[CV 4/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=200;, score=-33.937 total time= 4.8s\n", + "[CV 5/5] END model2__learning_rate=0.2, model2__loss=exponential, model2__n_estimators=200;, score=-42.545 total time= 4.8s\n" + ] + }, + { + "data": { + "text/html": [ + "
GridSearchCV(cv=5,\n",
+       "             estimator=Pipeline(steps=[('Data_processing',\n",
+       "                                        Pipeline(steps=[('step1',\n",
+       "                                                         ColumnTransformer(remainder='passthrough',\n",
+       "                                                                           transformers=[('col_tnf',\n",
+       "                                                                                          OneHotEncoder(drop='first',\n",
+       "                                                                                                        sparse_output=False),\n",
+       "                                                                                          [0,\n",
+       "                                                                                           2])])),\n",
+       "                                                        ('step2',\n",
+       "                                                         StandardScaler())])),\n",
+       "                                       ('model2', AdaBoostRegressor())]),\n",
+       "             n_jobs=-1,\n",
+       "             param_grid={'model2__learning_rate': [0.01, 0.025, 0.05, 0.075,\n",
+       "                                                   0.1, 0.15, 0.2],\n",
+       "                         'model2__loss': ['linear', 'square', 'exponential'],\n",
+       "                         'model2__n_estimators': [50, 100, 150, 200]},\n",
+       "             scoring='neg_mean_absolute_error', verbose=3)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" + ], + "text/plain": [ + "GridSearchCV(cv=5,\n", + " estimator=Pipeline(steps=[('Data_processing',\n", + " Pipeline(steps=[('step1',\n", + " ColumnTransformer(remainder='passthrough',\n", + " transformers=[('col_tnf',\n", + " OneHotEncoder(drop='first',\n", + " sparse_output=False),\n", + " [0,\n", + " 2])])),\n", + " ('step2',\n", + " StandardScaler())])),\n", + " ('model2', AdaBoostRegressor())]),\n", + " n_jobs=-1,\n", + " param_grid={'model2__learning_rate': [0.01, 0.025, 0.05, 0.075,\n", + " 0.1, 0.15, 0.2],\n", + " 'model2__loss': ['linear', 'square', 'exponential'],\n", + " 'model2__n_estimators': [50, 100, 150, 200]},\n", + " scoring='neg_mean_absolute_error', verbose=3)" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model2 = AdaBoostRegressor()\n", + "model2_pipe = Pipeline([('Data_processing' , data_pipeline) , ('model2' , model2)])\n", + "parameters = {\n", + " \"model2__learning_rate\": [0.01, 0.025, 0.05, 0.075, 0.1, 0.15, 0.2],\n", + " 'model2__loss' : ['linear', 'square', 'exponential'],\n", + " \"model2__n_estimators\":[50, 100, 150, 200]\n", + "}\n", + "\n", + "gscv2 = GridSearchCV(model2_pipe , parameters , scoring='neg_mean_absolute_error' , cv = 5 , n_jobs=-1 , verbose = 3)\n", + "gscv2.fit(x_train , y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Pipeline(steps=[('Data_processing',\n", + " Pipeline(steps=[('step1',\n", + " ColumnTransformer(remainder='passthrough',\n", + " transformers=[('col_tnf',\n", + " OneHotEncoder(drop='first',\n", + " sparse_output=False),\n", + " [0, 2])])),\n", + " ('step2', StandardScaler())])),\n", + " ('model2',\n", + " AdaBoostRegressor(learning_rate=0.025, loss='square'))])\n", + "--------------------\n", + "Best score :-25.98007300710056\n" + ] + } + ], + "source": [ + "print(gscv2.best_estimator_)\n", + "print('--'*10)\n", + "print(f'Best score :{gscv2.best_score_}')" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(12.311008461717156, 12.823689637660669)" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mean_absolute_error(gscv1.best_estimator_.predict(x_test) , y_test) , mean_absolute_error(pipeline.predict(x_test) , y_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [], + "source": [ + "# lets save the Gradient boosting model\n", + "with open('GradientBoostingRegressor.pkl' , 'wb') as file:\n", + " pickle.dump(gscv1.best_estimator_ , file)" + ] + }, + { + "cell_type": "code", + "execution_count": 105, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/Bingumalla Likith/Library/Python/3.9/lib/python/site-packages/sklearn/svm/_classes.py:31: FutureWarning: The default value of `dual` will change from `True` to `'auto'` in 1.5. Set the value of `dual` explicitly to suppress the warning.\n", + " warnings.warn(\n", + "/Users/Bingumalla Likith/Library/Python/3.9/lib/python/site-packages/sklearn/svm/_base.py:1237: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "text/html": [ + "
Pipeline(steps=[('Data_pipeline',\n",
+       "                 Pipeline(steps=[('step1',\n",
+       "                                  ColumnTransformer(remainder='passthrough',\n",
+       "                                                    transformers=[('col_tnf',\n",
+       "                                                                   OneHotEncoder(drop='first',\n",
+       "                                                                                 sparse_output=False),\n",
+       "                                                                   [0, 2])])),\n",
+       "                                 ('step2', StandardScaler())])),\n",
+       "                ('stacking_model',\n",
+       "                 StackingRegressor(estimators=[('xgbr',\n",
+       "                                                XGBRegressor(base_score=0.5,\n",
+       "                                                             booster='gbtree',\n",
+       "                                                             callbacks=None,\n",
+       "                                                             colsample_bylevel=1,\n",
+       "                                                             c...\n",
+       "                                                             max_delta_step=0,\n",
+       "                                                             max_depth=6,\n",
+       "                                                             max_leaves=0,\n",
+       "                                                             min_child_weight=1,\n",
+       "                                                             missing=nan,\n",
+       "                                                             monotone_constraints='()',\n",
+       "                                                             n_estimators=100,\n",
+       "                                                             n_jobs=0,\n",
+       "                                                             num_parallel_tree=1,\n",
+       "                                                             predictor='auto',\n",
+       "                                                             random_state=0,\n",
+       "                                                             reg_alpha=0,\n",
+       "                                                             reg_lambda=1, ...)),\n",
+       "                                               ('gbr',\n",
+       "                                                GradientBoostingRegressor(learning_rate=0.15,\n",
+       "                                                                          max_depth=8,\n",
+       "                                                                          max_features='sqrt',\n",
+       "                                                                          n_estimators=200,\n",
+       "                                                                          subsample=0.85))],\n",
+       "                                   final_estimator=LinearSVR()))])
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" + ], + "text/plain": [ + "Pipeline(steps=[('Data_pipeline',\n", + " Pipeline(steps=[('step1',\n", + " ColumnTransformer(remainder='passthrough',\n", + " transformers=[('col_tnf',\n", + " OneHotEncoder(drop='first',\n", + " sparse_output=False),\n", + " [0, 2])])),\n", + " ('step2', StandardScaler())])),\n", + " ('stacking_model',\n", + " StackingRegressor(estimators=[('xgbr',\n", + " XGBRegressor(base_score=0.5,\n", + " booster='gbtree',\n", + " callbacks=None,\n", + " colsample_bylevel=1,\n", + " c...\n", + " max_delta_step=0,\n", + " max_depth=6,\n", + " max_leaves=0,\n", + " min_child_weight=1,\n", + " missing=nan,\n", + " monotone_constraints='()',\n", + " n_estimators=100,\n", + " n_jobs=0,\n", + " num_parallel_tree=1,\n", + " predictor='auto',\n", + " random_state=0,\n", + " reg_alpha=0,\n", + " reg_lambda=1, ...)),\n", + " ('gbr',\n", + " GradientBoostingRegressor(learning_rate=0.15,\n", + " max_depth=8,\n", + " max_features='sqrt',\n", + " n_estimators=200,\n", + " subsample=0.85))],\n", + " final_estimator=LinearSVR()))])" + ] + }, + "execution_count": 105, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Now as Gradient Boosting is performing well lets create a stacking model using GradientBoosting and Xgboost Model that was used earlier\n", + "xgbr = pipeline.steps[-1][1]\n", + "gbr = gscv1.best_estimator_.steps[-1][1]\n", + "\n", + "from sklearn.svm import LinearSVR\n", + "\n", + "estimators = [('xgbr', xgbr), ('gbr', gbr)]\n", + "stacking_model = StackingRegressor(estimators = estimators , final_estimator = LinearSVR())\n", + "stacking_model_pipeline = Pipeline([\n", + " ('Data_pipeline' , data_pipeline),\n", + " ('stacking_model' , stacking_model)\n", + " ])\n", + "stacking_model_pipeline.fit(x_train , y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 106, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "18.38473245692642" + ] + }, + "execution_count": 106, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mean_absolute_error(stacking_model_pipeline.predict(x_test) , y_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Fitting 5 folds for each of 100 candidates, totalling 500 fits\n" + ] + } + ], + "source": [ + "param_grid = {\n", + " 'stacking_model__final_estimator__C': [0.01, 0.1, 1, 10, 100], \n", + " 'stacking_model__final_estimator__epsilon': [0.01, 0.1, 0.2, 0.5, 1], \n", + " 'stacking_model__final_estimator__tol': [1e-4, 1e-3, 1e-2, 1e-1], \n", + "}\n", + "\n", + "gscv3 = GridSearchCV(stacking_model_pipeline , param_grid , n_jobs = -1 , scoring = 'neg_mean_squared_error' , verbose = 3)\n", + "gscv3.fit(x_train , y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.6" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Hedging with Real Estate/New_Upgrade_Bengaluru_House_Price_Predition/StackingModel.png b/Hedging with Real Estate/New_Upgrade_Bengaluru_House_Price_Predition/StackingModel.png new file mode 100644 index 00000000..bd785a5c Binary files /dev/null and b/Hedging with Real Estate/New_Upgrade_Bengaluru_House_Price_Predition/StackingModel.png differ