auto-feature-selection-in-house-price-predictions.ipynb

{"cells":[{"source":"<a href=\"https://www.kaggle.com/code/rmeades/auto-feature-selection-in-house-price-predictions?scriptVersionId=119902027\" target=\"_blank\"><img align=\"left\" alt=\"Kaggle\" title=\"Open in Kaggle\" src=\"https://kaggle.com/static/images/open-in-kaggle.svg\"></a>","metadata":{},"cell_type":"markdown","outputs":[],"execution_count":0},{"cell_type":"markdown","id":"46ad2a82","metadata":{"papermill":{"duration":0.006574,"end_time":"2023-02-21T22:20:43.224048","exception":false,"start_time":"2023-02-21T22:20:43.217474","status":"completed"},"tags":[]},"source":["# INTRODUCTION\n","\n","The following code demonstrates auto feature selection using the SULOV method (Searching for Uncorrelated List of Variables) and recursive XGBoost feature selection as implemented in FeatureWiz. I was curious to see how this would perform in the competition vs manual methods. Trained model is an XGBoost regressor with early stopping to avoid overfitting.\n","\n","This resulted in a leaderboard score of 0.14679 (RMSE). By comparison, my other, rather simple attempt wihtout Featurewiz scored 0.17528 (RMSE), see notebook here https://www.kaggle.com/code/rmeades/ames-house-price-predictions?kernelSessionId=119034247\n","\n","See Final Remarks at the end.\n","\n","Without further ado, let's crack on and load the preliminaries............."]},{"cell_type":"code","execution_count":1,"id":"8cff0b1c","metadata":{"_kg_hide-output":true,"execution":{"iopub.execute_input":"2023-02-21T22:20:43.237411Z","iopub.status.busy":"2023-02-21T22:20:43.236484Z","iopub.status.idle":"2023-02-21T22:21:24.333795Z","shell.execute_reply":"2023-02-21T22:21:24.332324Z"},"papermill":{"duration":41.107082,"end_time":"2023-02-21T22:21:24.336524","exception":false,"start_time":"2023-02-21T22:20:43.229442","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\r\n","beatrix-jupyterlab 3.1.7 requires google-cloud-bigquery-storage, which is not installed.\r\n","tfx-bsl 1.9.0 requires google-api-python-client<2,>=1.7.11, but you have google-api-python-client 2.52.0 which is incompatible.\r\n","tfx-bsl 1.9.0 requires pyarrow<6,>=1, but you have pyarrow 7.0.0 which is incompatible.\r\n","tfx-bsl 1.9.0 requires tensorflow!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,<3,>=1.15.5, but you have tensorflow 2.6.4 which is incompatible.\r\n","tensorflow-transform 1.9.0 requires pyarrow<6,>=1, but you have pyarrow 7.0.0 which is incompatible.\r\n","tensorflow-transform 1.9.0 requires tensorflow!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,<2.10,>=1.15.5, but you have tensorflow 2.6.4 which is incompatible.\r\n","pandas-profiling 3.1.0 requires joblib~=1.0.1, but you have joblib 1.2.0 which is incompatible.\r\n","pandas-profiling 3.1.0 requires markupsafe~=2.0.1, but you have markupsafe 2.1.2 which is incompatible.\r\n","apache-beam 2.40.0 requires dill<0.3.2,>=0.3.1.1, but you have dill 0.3.6 which is incompatible.\u001b[0m\u001b[31m\r\n","\u001b[0m\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\r\n","\u001b[0m\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\r\n","\u001b[0m"]},{"data":{"text/html":["<style type='text/css'>\n",".datatable table.frame { margin-bottom: 0; }\n",".datatable table.frame thead { border-bottom: none; }\n",".datatable table.frame tr.coltypes td {  color: #FFFFFF;  line-height: 6px;  padding: 0 0.5em;}\n",".datatable .bool    { background: #DDDD99; }\n",".datatable .object  { background: #565656; }\n",".datatable .int     { background: #5D9E5D; }\n",".datatable .float   { background: #4040CC; }\n",".datatable .str     { background: #CC4040; }\n",".datatable .time    { background: #40CC40; }\n",".datatable .row_index {  background: var(--jp-border-color3);  border-right: 1px solid var(--jp-border-color0);  color: var(--jp-ui-font-color3);  font-size: 9px;}\n",".datatable .frame tbody td { text-align: left; }\n",".datatable .frame tr.coltypes .row_index {  background: var(--jp-border-color0);}\n",".datatable th:nth-child(2) { padding-left: 12px; }\n",".datatable .hellipsis {  color: var(--jp-cell-editor-border-color);}\n",".datatable .vellipsis {  background: var(--jp-layout-color0);  color: var(--jp-cell-editor-border-color);}\n",".datatable .na {  color: var(--jp-cell-editor-border-color);  font-size: 80%;}\n",".datatable .sp {  opacity: 0.25;}\n",".datatable .footer { font-size: 9px; }\n",".datatable .frame_dimensions {  background: var(--jp-border-color3);  border-top: 1px solid var(--jp-border-color0);  color: var(--jp-ui-font-color3);  display: inline-block;  opacity: 0.6;  padding: 1px 10px 1px 5px;}\n","</style>\n"],"text/plain":["<IPython.core.display.HTML object>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["Imported 0.2.04 version. Select nrows to a small number when running on huge datasets.\n","output = featurewiz(dataname, target, corr_limit=0.90, verbose=2, sep=',', \n","\t\theader=0, test_data='',feature_engg='', category_encoders='',\n","\t\tdask_xgboost_flag=False, nrows=None, skip_sulov=False)\n","Create new features via 'feature_engg' flag : ['interactions','groupby','target']\n","\n","/kaggle/input/house-prices-advanced-regression-techniques/sample_submission.csv\n","/kaggle/input/house-prices-advanced-regression-techniques/data_description.txt\n","/kaggle/input/house-prices-advanced-regression-techniques/train.csv\n","/kaggle/input/house-prices-advanced-regression-techniques/test.csv\n"]}],"source":["import numpy as np\n","import pandas as pd\n","import matplotlib.pyplot as plt\n","from matplotlib.pyplot import figure\n","import seaborn as sns\n","!pip install featurewiz -q\n","!pip install featurewiz --upgrade --quiet\n","from featurewiz import featurewiz as FW\n","from sklearn.model_selection import cross_val_score,train_test_split\n","from xgboost import XGBRegressor\n","from sklearn.metrics import mean_squared_error\n","%matplotlib inline\n","\n","import os\n","for dirname, _, filenames in os.walk('/kaggle/input'):\n","    for filename in filenames:\n","        print(os.path.join(dirname, filename))"]},{"cell_type":"markdown","id":"5bd44371","metadata":{"papermill":{"duration":0.005775,"end_time":"2023-02-21T22:21:24.348417","exception":false,"start_time":"2023-02-21T22:21:24.342642","status":"completed"},"tags":[]},"source":["# DATA PREPROCESSING\n","Let's read in the train and test datasets into dataframes using pandas and take a look at a summary of what they consist of..."]},{"cell_type":"code","execution_count":2,"id":"70124ffe","metadata":{"execution":{"iopub.execute_input":"2023-02-21T22:21:24.362703Z","iopub.status.busy":"2023-02-21T22:21:24.361736Z","iopub.status.idle":"2023-02-21T22:21:24.430293Z","shell.execute_reply":"2023-02-21T22:21:24.429354Z"},"papermill":{"duration":0.078772,"end_time":"2023-02-21T22:21:24.432888","exception":false,"start_time":"2023-02-21T22:21:24.354116","status":"completed"},"tags":[]},"outputs":[],"source":["train = pd.read_csv(\"/kaggle/input/house-prices-advanced-regression-techniques/train.csv\")\n","test = pd.read_csv(\"/kaggle/input/house-prices-advanced-regression-techniques/test.csv\")"]},{"cell_type":"code","execution_count":3,"id":"be31980c","metadata":{"execution":{"iopub.execute_input":"2023-02-21T22:21:24.446356Z","iopub.status.busy":"2023-02-21T22:21:24.44596Z","iopub.status.idle":"2023-02-21T22:21:24.479024Z","shell.execute_reply":"2023-02-21T22:21:24.477221Z"},"papermill":{"duration":0.042606,"end_time":"2023-02-21T22:21:24.481575","exception":false,"start_time":"2023-02-21T22:21:24.438969","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 1460 entries, 0 to 1459\n","Data columns (total 81 columns):\n"," #   Column         Non-Null Count  Dtype  \n","---  ------         --------------  -----  \n"," 0   Id             1460 non-null   int64  \n"," 1   MSSubClass     1460 non-null   int64  \n"," 2   MSZoning       1460 non-null   object \n"," 3   LotFrontage    1201 non-null   float64\n"," 4   LotArea        1460 non-null   int64  \n"," 5   Street         1460 non-null   object \n"," 6   Alley          91 non-null     object \n"," 7   LotShape       1460 non-null   object \n"," 8   LandContour    1460 non-null   object \n"," 9   Utilities      1460 non-null   object \n"," 10  LotConfig      1460 non-null   object \n"," 11  LandSlope      1460 non-null   object \n"," 12  Neighborhood   1460 non-null   object \n"," 13  Condition1     1460 non-null   object \n"," 14  Condition2     1460 non-null   object \n"," 15  BldgType       1460 non-null   object \n"," 16  HouseStyle     1460 non-null   object \n"," 17  OverallQual    1460 non-null   int64  \n"," 18  OverallCond    1460 non-null   int64  \n"," 19  YearBuilt      1460 non-null   int64  \n"," 20  YearRemodAdd   1460 non-null   int64  \n"," 21  RoofStyle      1460 non-null   object \n"," 22  RoofMatl       1460 non-null   object \n"," 23  Exterior1st    1460 non-null   object \n"," 24  Exterior2nd    1460 non-null   object \n"," 25  MasVnrType     1452 non-null   object \n"," 26  MasVnrArea     1452 non-null   float64\n"," 27  ExterQual      1460 non-null   object \n"," 28  ExterCond      1460 non-null   object \n"," 29  Foundation     1460 non-null   object \n"," 30  BsmtQual       1423 non-null   object \n"," 31  BsmtCond       1423 non-null   object \n"," 32  BsmtExposure   1422 non-null   object \n"," 33  BsmtFinType1   1423 non-null   object \n"," 34  BsmtFinSF1     1460 non-null   int64  \n"," 35  BsmtFinType2   1422 non-null   object \n"," 36  BsmtFinSF2     1460 non-null   int64  \n"," 37  BsmtUnfSF      1460 non-null   int64  \n"," 38  TotalBsmtSF    1460 non-null   int64  \n"," 39  Heating        1460 non-null   object \n"," 40  HeatingQC      1460 non-null   object \n"," 41  CentralAir     1460 non-null   object \n"," 42  Electrical     1459 non-null   object \n"," 43  1stFlrSF       1460 non-null   int64  \n"," 44  2ndFlrSF       1460 non-null   int64  \n"," 45  LowQualFinSF   1460 non-null   int64  \n"," 46  GrLivArea      1460 non-null   int64  \n"," 47  BsmtFullBath   1460 non-null   int64  \n"," 48  BsmtHalfBath   1460 non-null   int64  \n"," 49  FullBath       1460 non-null   int64  \n"," 50  HalfBath       1460 non-null   int64  \n"," 51  BedroomAbvGr   1460 non-null   int64  \n"," 52  KitchenAbvGr   1460 non-null   int64  \n"," 53  KitchenQual    1460 non-null   object \n"," 54  TotRmsAbvGrd   1460 non-null   int64  \n"," 55  Functional     1460 non-null   object \n"," 56  Fireplaces     1460 non-null   int64  \n"," 57  FireplaceQu    770 non-null    object \n"," 58  GarageType     1379 non-null   object \n"," 59  GarageYrBlt    1379 non-null   float64\n"," 60  GarageFinish   1379 non-null   object \n"," 61  GarageCars     1460 non-null   int64  \n"," 62  GarageArea     1460 non-null   int64  \n"," 63  GarageQual     1379 non-null   object \n"," 64  GarageCond     1379 non-null   object \n"," 65  PavedDrive     1460 non-null   object \n"," 66  WoodDeckSF     1460 non-null   int64  \n"," 67  OpenPorchSF    1460 non-null   int64  \n"," 68  EnclosedPorch  1460 non-null   int64  \n"," 69  3SsnPorch      1460 non-null   int64  \n"," 70  ScreenPorch    1460 non-null   int64  \n"," 71  PoolArea       1460 non-null   int64  \n"," 72  PoolQC         7 non-null      object \n"," 73  Fence          281 non-null    object \n"," 74  MiscFeature    54 non-null     object \n"," 75  MiscVal        1460 non-null   int64  \n"," 76  MoSold         1460 non-null   int64  \n"," 77  YrSold         1460 non-null   int64  \n"," 78  SaleType       1460 non-null   object \n"," 79  SaleCondition  1460 non-null   object \n"," 80  SalePrice      1460 non-null   int64  \n","dtypes: float64(3), int64(35), object(43)\n","memory usage: 924.0+ KB\n"]}],"source":["train.info()"]},{"cell_type":"code","execution_count":4,"id":"a684d2f5","metadata":{"execution":{"iopub.execute_input":"2023-02-21T22:21:24.49537Z","iopub.status.busy":"2023-02-21T22:21:24.494535Z","iopub.status.idle":"2023-02-21T22:21:24.513527Z","shell.execute_reply":"2023-02-21T22:21:24.512318Z"},"papermill":{"duration":0.028401,"end_time":"2023-02-21T22:21:24.515989","exception":false,"start_time":"2023-02-21T22:21:24.487588","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 1459 entries, 0 to 1458\n","Data columns (total 80 columns):\n"," #   Column         Non-Null Count  Dtype  \n","---  ------         --------------  -----  \n"," 0   Id             1459 non-null   int64  \n"," 1   MSSubClass     1459 non-null   int64  \n"," 2   MSZoning       1455 non-null   object \n"," 3   LotFrontage    1232 non-null   float64\n"," 4   LotArea        1459 non-null   int64  \n"," 5   Street         1459 non-null   object \n"," 6   Alley          107 non-null    object \n"," 7   LotShape       1459 non-null   object \n"," 8   LandContour    1459 non-null   object \n"," 9   Utilities      1457 non-null   object \n"," 10  LotConfig      1459 non-null   object \n"," 11  LandSlope      1459 non-null   object \n"," 12  Neighborhood   1459 non-null   object \n"," 13  Condition1     1459 non-null   object \n"," 14  Condition2     1459 non-null   object \n"," 15  BldgType       1459 non-null   object \n"," 16  HouseStyle     1459 non-null   object \n"," 17  OverallQual    1459 non-null   int64  \n"," 18  OverallCond    1459 non-null   int64  \n"," 19  YearBuilt      1459 non-null   int64  \n"," 20  YearRemodAdd   1459 non-null   int64  \n"," 21  RoofStyle      1459 non-null   object \n"," 22  RoofMatl       1459 non-null   object \n"," 23  Exterior1st    1458 non-null   object \n"," 24  Exterior2nd    1458 non-null   object \n"," 25  MasVnrType     1443 non-null   object \n"," 26  MasVnrArea     1444 non-null   float64\n"," 27  ExterQual      1459 non-null   object \n"," 28  ExterCond      1459 non-null   object \n"," 29  Foundation     1459 non-null   object \n"," 30  BsmtQual       1415 non-null   object \n"," 31  BsmtCond       1414 non-null   object \n"," 32  BsmtExposure   1415 non-null   object \n"," 33  BsmtFinType1   1417 non-null   object \n"," 34  BsmtFinSF1     1458 non-null   float64\n"," 35  BsmtFinType2   1417 non-null   object \n"," 36  BsmtFinSF2     1458 non-null   float64\n"," 37  BsmtUnfSF      1458 non-null   float64\n"," 38  TotalBsmtSF    1458 non-null   float64\n"," 39  Heating        1459 non-null   object \n"," 40  HeatingQC      1459 non-null   object \n"," 41  CentralAir     1459 non-null   object \n"," 42  Electrical     1459 non-null   object \n"," 43  1stFlrSF       1459 non-null   int64  \n"," 44  2ndFlrSF       1459 non-null   int64  \n"," 45  LowQualFinSF   1459 non-null   int64  \n"," 46  GrLivArea      1459 non-null   int64  \n"," 47  BsmtFullBath   1457 non-null   float64\n"," 48  BsmtHalfBath   1457 non-null   float64\n"," 49  FullBath       1459 non-null   int64  \n"," 50  HalfBath       1459 non-null   int64  \n"," 51  BedroomAbvGr   1459 non-null   int64  \n"," 52  KitchenAbvGr   1459 non-null   int64  \n"," 53  KitchenQual    1458 non-null   object \n"," 54  TotRmsAbvGrd   1459 non-null   int64  \n"," 55  Functional     1457 non-null   object \n"," 56  Fireplaces     1459 non-null   int64  \n"," 57  FireplaceQu    729 non-null    object \n"," 58  GarageType     1383 non-null   object \n"," 59  GarageYrBlt    1381 non-null   float64\n"," 60  GarageFinish   1381 non-null   object \n"," 61  GarageCars     1458 non-null   float64\n"," 62  GarageArea     1458 non-null   float64\n"," 63  GarageQual     1381 non-null   object \n"," 64  GarageCond     1381 non-null   object \n"," 65  PavedDrive     1459 non-null   object \n"," 66  WoodDeckSF     1459 non-null   int64  \n"," 67  OpenPorchSF    1459 non-null   int64  \n"," 68  EnclosedPorch  1459 non-null   int64  \n"," 69  3SsnPorch      1459 non-null   int64  \n"," 70  ScreenPorch    1459 non-null   int64  \n"," 71  PoolArea       1459 non-null   int64  \n"," 72  PoolQC         3 non-null      object \n"," 73  Fence          290 non-null    object \n"," 74  MiscFeature    51 non-null     object \n"," 75  MiscVal        1459 non-null   int64  \n"," 76  MoSold         1459 non-null   int64  \n"," 77  YrSold         1459 non-null   int64  \n"," 78  SaleType       1458 non-null   object \n"," 79  SaleCondition  1459 non-null   object \n","dtypes: float64(11), int64(26), object(43)\n","memory usage: 912.0+ KB\n"]}],"source":["test.info()"]},{"cell_type":"markdown","id":"5cc56025","metadata":{"papermill":{"duration":0.005957,"end_time":"2023-02-21T22:21:24.528125","exception":false,"start_time":"2023-02-21T22:21:24.522168","status":"completed"},"tags":[]},"source":["Now let's use featurewiz to select the independant variables that are most useful. I have set the correlation limit to 0.7. THis is the value above which pairs of intercorrelated variables are chosen for one of them to be removed (the one with the lowest mutual information score with respects to the target variable)."]},{"cell_type":"code","execution_count":5,"id":"6ad98f98","metadata":{"execution":{"iopub.execute_input":"2023-02-21T22:21:24.541871Z","iopub.status.busy":"2023-02-21T22:21:24.541268Z","iopub.status.idle":"2023-02-21T22:21:28.740011Z","shell.execute_reply":"2023-02-21T22:21:28.73895Z"},"papermill":{"duration":4.210917,"end_time":"2023-02-21T22:21:28.744948","exception":false,"start_time":"2023-02-21T22:21:24.534031","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["############################################################################################\n","############       F A S T   F E A T U R E  E N G G    A N D    S E L E C T I O N ! ########\n","# Be judicious with featurewiz. Don't use it to create too many un-interpretable features! #\n","############################################################################################\n","featurewiz has selected 0.7 as the correlation limit. Change this limit to fit your needs...\n","Skipping feature engineering since no feature_engg input...\n","Skipping category encoding since no category encoders specified in input...\n","#### Single_Label Regression problem ####\n","    Loaded train data. Shape = (1460, 81)\n","#### Single_Label Regression problem ####\n","loading the entire test dataframe - there is no nrows limit applicable #########\n","    Loaded test data. Shape = (1459, 80)\n","#######################################################################################\n","######################## C L A S S I F Y I N G  V A R I A B L E S  ####################\n","#######################################################################################\n","        4 variable(s) to be removed since ID or low-information variables\n","    \tvariables removed = ['Id', 'Alley', 'PoolQC', 'MiscFeature']\n","train data shape before dropping 3 columns = (1460, 81)\n","\ttrain data shape after dropping columns = (1460, 78)\n","Caution: Since there are date-time variables in dataset, it is best to load them using pandas\n","#### Single_Label Regression problem ####\n","No GPU active on this device\n","    Tuning XGBoost using CPU hyper-parameters. This will take time...\n","Processing YearRemodAdd column for date time features....\n","        Adding same time series features to test data...\n","Processing YrSold column for date time features....\n","        Adding same time series features to test data...\n","    After removing redundant variables from further processing, features left = 74\n","No interactions created for categorical vars since feature engg does not specify it\n","#######################################################################################\n","#####  Searching for Uncorrelated List Of Variables (SULOV) in 34 features ############\n","#######################################################################################\n","    there are no null values in dataset...\n","    Removing (3) highly correlated variables:\n","    ['1stFlrSF', 'GarageArea', 'TotRmsAbvGrd']\n"]},{"data":{"image/png":"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\n","text/plain":["<Figure size 1080x360 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["Time taken for SULOV method = 1 seconds\n","    Adding 40 categorical variables to reduced numeric variables  of 31\n","Finally 71 vars selected after SULOV\n","Converting all features to numeric before sending to XGBoost...\n","    there were no mixed data types or object columns that errored. Data is all numeric...\n","Shape of train data after adding missing values flags = (1460, 75)\n","    Shape of test data after adding missing values flags  = (1459, 74)\n","#######################################################################################\n","#####    R E C U R S I V E   X G B O O S T : F E A T U R E   S E L E C T I O N  #######\n","#######################################################################################\n","    using regular XGBoost\n","Current number of predictors before recursive XGBoost = 74 \n","    Taking top 11 features per iteration...\n","    XGBoost version using 1.6.2 as tree method: hist\n","Number of booster rounds = 100\n","        using 74 variables...\n","            selecting 34 features in this iteration\n","            Time taken for regular XGBoost feature selection = 1 seconds\n","        using 59 variables...\n","            selecting 27 features in this iteration\n","            Time taken for regular XGBoost feature selection = 0 seconds\n","        using 44 variables...\n","            selecting 20 features in this iteration\n","            Time taken for regular XGBoost feature selection = 0 seconds\n","        using 29 variables...\n","            selecting 13 features in this iteration\n","            Time taken for regular XGBoost feature selection = 0 seconds\n","        using 14 variables...\n","            selecting 6 features in this iteration\n","            Time taken for regular XGBoost feature selection = 0 seconds\n"]},{"data":{"image/png":"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\n","text/plain":["<Figure size 720x1080 with 6 Axes>"]},"metadata":{"needs_background":"light"},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["    Completed XGBoost feature selection in 1 seconds\n","    Alert: No ID variables ['Id'] are included in selected features\n","#######################################################################################\n","#####          F E A T U R E   S E L E C T I O N   C O M P L E T E D            #######\n","#######################################################################################\n","Alert: Dont forget to add a missing flag to GarageYrBlt to create GarageYrBlt_Missing_Flag column\n","Selected 45 important features. Too many to print...\n","Total Time taken for featurewiz selection = 4 seconds\n","Output contains two dataframes: train and test with 45 important features.\n","There are special chars in column names. Please remove them and try again.\n"]}],"source":["train_select, test_select = FW(train, \"SalePrice\", corr_limit=0.7, test_data=test, category_encoders=\"\", verbose=2)"]},{"cell_type":"markdown","id":"e5d0eceb","metadata":{"papermill":{"duration":0.008933,"end_time":"2023-02-21T22:21:28.764185","exception":false,"start_time":"2023-02-21T22:21:28.755252","status":"completed"},"tags":[]},"source":["It has reduced he number of features from 80 to 45! Let's see what it has selected.......\n"]},{"cell_type":"code","execution_count":6,"id":"cf9e2d9d","metadata":{"execution":{"iopub.execute_input":"2023-02-21T22:21:28.78489Z","iopub.status.busy":"2023-02-21T22:21:28.783773Z","iopub.status.idle":"2023-02-21T22:21:28.799956Z","shell.execute_reply":"2023-02-21T22:21:28.79893Z"},"papermill":{"duration":0.029635,"end_time":"2023-02-21T22:21:28.802499","exception":false,"start_time":"2023-02-21T22:21:28.772864","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 1460 entries, 0 to 1459\n","Data columns (total 44 columns):\n"," #   Column         Non-Null Count  Dtype  \n","---  ------         --------------  -----  \n"," 0   OverallQual    1460 non-null   int64  \n"," 1   GarageCars     1460 non-null   int64  \n"," 2   BsmtQual       1460 non-null   int64  \n"," 3   KitchenQual    1460 non-null   int64  \n"," 4   GrLivArea      1460 non-null   int64  \n"," 5   CentralAir     1460 non-null   int64  \n"," 6   KitchenAbvGr   1460 non-null   int64  \n"," 7   TotalBsmtSF    1460 non-null   int64  \n"," 8   LandContour    1460 non-null   int64  \n"," 9   MSZoning       1460 non-null   int64  \n"," 10  LandSlope      1460 non-null   int64  \n"," 11  GarageType     1460 non-null   int64  \n"," 12  ExterQual      1460 non-null   int64  \n"," 13  BsmtFinSF1     1460 non-null   int64  \n"," 14  BsmtFullBath   1460 non-null   int64  \n"," 15  OverallCond    1460 non-null   int64  \n"," 16  LotShape       1460 non-null   int64  \n"," 17  YearBuilt      1460 non-null   int64  \n"," 18  Fireplaces     1460 non-null   int64  \n"," 19  SaleType       1460 non-null   int64  \n"," 20  GarageQual     1460 non-null   int64  \n"," 21  ScreenPorch    1460 non-null   int64  \n"," 22  BsmtExposure   1460 non-null   int64  \n"," 23  Neighborhood   1460 non-null   int64  \n"," 24  Functional     1460 non-null   int64  \n"," 25  SaleCondition  1460 non-null   int64  \n"," 26  LotArea        1460 non-null   int64  \n"," 27  OpenPorchSF    1460 non-null   int64  \n"," 28  ExterCond      1460 non-null   int64  \n"," 29  GarageYrBlt    1460 non-null   float64\n"," 30  HeatingQC      1460 non-null   int64  \n"," 31  2ndFlrSF       1460 non-null   int64  \n"," 32  PoolArea       1460 non-null   int64  \n"," 33  LotFrontage    1460 non-null   float64\n"," 34  RoofMatl       1460 non-null   int64  \n"," 35  FireplaceQu    1460 non-null   int64  \n"," 36  BsmtFinType1   1460 non-null   int64  \n"," 37  BldgType       1460 non-null   int64  \n"," 38  HouseStyle     1460 non-null   int64  \n"," 39  Foundation     1460 non-null   int64  \n"," 40  BsmtFinType2   1460 non-null   int64  \n"," 41  RoofStyle      1460 non-null   int64  \n"," 42  GarageCond     1460 non-null   int64  \n"," 43  MasVnrType     1460 non-null   int64  \n","dtypes: float64(2), int64(42)\n","memory usage: 502.0 KB\n"]}],"source":["train_select.info()"]},{"cell_type":"code","execution_count":7,"id":"64354aa3","metadata":{"execution":{"iopub.execute_input":"2023-02-21T22:21:28.822376Z","iopub.status.busy":"2023-02-21T22:21:28.821822Z","iopub.status.idle":"2023-02-21T22:21:29.900986Z","shell.execute_reply":"2023-02-21T22:21:29.900235Z"},"papermill":{"duration":1.091565,"end_time":"2023-02-21T22:21:29.903505","exception":false,"start_time":"2023-02-21T22:21:28.81194","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<AxesSubplot:>"]},"execution_count":7,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 1008x1008 with 2 Axes>"]},"metadata":{"needs_background":"light"},"output_type":"display_data"}],"source":["plt.figure(figsize=(14, 14))\n","sns.heatmap(train_select.corr())"]},{"cell_type":"markdown","id":"c88b7943","metadata":{"papermill":{"duration":0.010146,"end_time":"2023-02-21T22:21:29.924368","exception":false,"start_time":"2023-02-21T22:21:29.914222","status":"completed"},"tags":[]},"source":["OK. Not only has it selected the variables correlated the most with SalePrice whilst eliminateing highly correlated features, it has also encoded the catagorical variables (no 'object' data types) and handled all the missing values.\n","\n","Let's check distribution of target...."]},{"cell_type":"code","execution_count":8,"id":"8cdf5c26","metadata":{"execution":{"iopub.execute_input":"2023-02-21T22:21:29.947288Z","iopub.status.busy":"2023-02-21T22:21:29.946236Z","iopub.status.idle":"2023-02-21T22:21:30.320853Z","shell.execute_reply":"2023-02-21T22:21:30.320105Z"},"papermill":{"duration":0.388312,"end_time":"2023-02-21T22:21:30.322885","exception":false,"start_time":"2023-02-21T22:21:29.934573","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["count      1460.000000\n","mean     180921.195890\n","std       79442.502883\n","min       34900.000000\n","25%      129975.000000\n","50%      163000.000000\n","75%      214000.000000\n","max      755000.000000\n","Name: SalePrice, dtype: float64"]},"execution_count":8,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAWAAAAFgCAYAAACFYaNMAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAAAYcUlEQVR4nO3df7DddX3n8eerQdAqJtBEN4u4AYvMCmOjXlDrj8VoNTjUHx1/hOm4LBWjW3EK7tgV6ajbGWe6/lissmojsmhXERSpuuuKLFi126oERJJIQMBYE7LkBjbi1i4l+N4/zjfk3OQkuQn3nM+59z4fM3fu93zO93zPKyc3r/vN53y/35OqQpI0er/WOoAkzVcWsCQ1YgFLUiMWsCQ1YgFLUiOHtQ7wSKxcubK+/vWvt44hSQeSQYOzeg94+/btrSNI0iGb1QUsSbOZBSxJjVjAktSIBSxJjVjAktSIBSxJjVjAktSIBSxJjVjAktSIBSxJjVjAktSIBSxJjVjAktTI0C5HmeRS4AxgW1Wd3I1dAZzYrbII2FFVy5MsA24Fbuvu+25VvWVY2cbBOeeez5btO/YaP2bxIi65+KLRB5I0csO8HvBlwMXAZ3YNVNXrdy0n+RDw877176yq5UPMM1a2bN/BwhWr9x6/fk2DNJJaGFoBV9W3uz3bvSQJ8DpgxbCeX5LGXas54BcA91TVj/vGjkvygyTfSvKCfT0wyeoka5OsnZycHH5SSRqSVgV8JnB53+2twJOr6hnA24HPJXn8oAdW1ZqqmqiqiSVLlowgqiQNx8gLOMlhwO8BV+waq6oHqurebvlG4E7gqaPOJkmj1GIP+CXAxqravGsgyZIkC7rl44ETgLsaZJOkkRlaASe5HPg74MQkm5O8sbtrFVOnHwBeCNyS5IfAF4G3VNV9w8omSeNgmEdBnLmP8X8zYOwq4KphZZGkceSZcJLUyDBPxNAh2LB+HaevOnvKmGfHSXOTBTxmHqwFe50h59lx0tzkFIQkNWIBS1IjFrAkNWIBS1IjFrAkNWIBS1IjFrAkNWIBS1IjFrAkNWIBS1IjFrAkNWIBS1IjFrAkNWIBS1IjFrAkNWIBS1IjFrAkNWIBS1IjFrAkNWIBS1IjFrAkNWIBS1IjFrAkNWIBS1IjFrAkNWIBS1IjFrAkNWIBS1IjFrAkNTK0Ak5yaZJtSdb3jb03yZYkN3dfL++774IkdyS5LcnLhpVLksbFMPeALwNWDhi/qKqWd19fA0jyNGAVcFL3mI8lWTDEbJLU3NAKuKq+Ddw3zdVfCXy+qh6oqp8AdwCnDiubJI2DFnPA5ya5pZuiOKobOwb4Wd86m7sxSZqzRl3AHweeAiwHtgIf6sYzYN0atIEkq5OsTbJ2cnJyKCElaRRGWsBVdU9VPVRVvwI+ye5phs3AsX2rPgm4ex/bWFNVE1U1sWTJkuEGlqQhGmkBJ1nad/PVwK4jJL4CrEpyRJLjgBOA748ymySN2mHD2nCSy4HTgMVJNgPvAU5Lspze9MIm4M0AVbUhyZXAj4CdwFur6qFhZZOkcTC0Aq6qMwcMf2o/678PeN+w8kjSuPFMOElqxAKWpEYsYElqZGhzwBq+c849ny3bd0wZO2bxIi65+KI2gSQdFAt4FtuyfQcLV6yeOnb9mkZpJB0spyAkqRELWJIasYAlqRELWJIasYAlqRELWJIasYAlqRELWJIasYAlqRELWJIasYAlqRELWJIasYAlqRELWJIasYAlqRELWJIasYAlqRELWJIasYAlqRELWJIasYAlqRELWJIasYAlqRELWJIaOax1AB3YhvXrOH3V2XuN37rxdp6zokEgSTPCAp4FHqwFLFyxeq/xB9adN/owkmaMUxCS1IgFLEmNDK2Ak1yaZFuS9X1jH0iyMcktSa5OsqgbX5bkH5Pc3H19Yli5JGlcDHMP+DJg5R5j1wInV9XTgduBC/ruu7OqlndfbxliLkkaC0Mr4Kr6NnDfHmPfqKqd3c3vAk8a1vNL0rhreRTEHwBX9N0+LskPgPuBP6mq7wx6UJLVwGqAJz/5yUMPORPOOfd8tmzfMWXMQ8gkNSngJBcCO4HPdkNbgSdX1b1JngX8VZKTqur+PR9bVWuANQATExM1qsyPxJbtO/Y6jMxDyCSN/CiIJGcBZwC/X1UFUFUPVNW93fKNwJ3AU0edTZJGaaQFnGQl8O+BV1TVL/vGlyRZ0C0fD5wA3DXKbJI0akObgkhyOXAasDjJZuA99I56OAK4NgnAd7sjHl4I/GmSncBDwFuq6r6BG5akOWJoBVxVZw4Y/tQ+1r0KuGpYWSRpHHkmnCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiOHtQ6gmbVh/TpOX3X2XuPHLF7EJRdf1CCRpH2xgOeYB2sBC1es3mt8y/VrGqSRtD9Dm4JIcmmSbUnW940dneTaJD/uvh/Vd98FSe5IcluSlw0rlySNi2HOAV8GrNxj7J3AdVV1AnBdd5skTwNWASd1j/lYkgVDzCZJzQ2tgKvq28B9ewy/Evh0t/xp4FV945+vqgeq6ifAHcCpw8omSeNgWgWc5HnTGZuGJ1bVVoDu+xO68WOAn/Wtt7kbG5RldZK1SdZOTk4eQgRJGg/T3QP+6DTHDlUGjNWgFatqTVVNVNXEkiVLZjCCJI3Wfo+CSPJc4LeBJUne3nfX44FDmaO9J8nSqtqaZCmwrRvfDBzbt96TgLsPYfuSNGscaA/4cOBx9Ir6yL6v+4HXHMLzfQU4q1s+C/hy3/iqJEckOQ44Afj+IWxfkmaN/e4BV9W3gG8luayqfnowG05yOXAasDjJZuA9wJ8BVyZ5I/D3wGu759mQ5ErgR8BO4K1V9dDB/mEkaTaZ7okYRyRZAyzrf0xVrdjXA6rqzH3c9eJ9rP8+4H3TzCNJs950C/gLwCeASwD3TCVpBky3gHdW1ceHmkSS5pnpHob21SR/mGRpdzrx0UmOHmoySZrjprsHvOvIhXf0jRVw/MzGkaT5Y1oFXFXHDTuIJM030yrgJP960HhVfWZm40jS/DHdKYhT+pYfTe9QspsAC1iSDtF0pyDe1n87yULgL4eSSJLmiUO9HOUv6Z0uLEk6RNOdA/4qu69OtgD4l8CVwwolSfPBdOeAP9i3vBP4aVVtHkIeSZo3pjUF0V2UZyO9K6EdBfzTMENJ0nww3U/EeB29y0O+Fngd8L0kh3I5SklSZ7pTEBcCp1TVNoAkS4D/CXxxWMEkaa6b7lEQv7arfDv3HsRjJUkDTHcP+OtJrgEu726/HvjacCJJ0vxwoM+E+016n2T8jiS/Bzyf3gdo/h3w2RHkk6Q560DTCB8GfgFQVV+qqrdX1fn09n4/PNxokjS3HaiAl1XVLXsOVtVaeh9PJEk6RAcq4Efv577HzGQQSZpvDlTANyR5056D3aca3zicSJI0PxzoKIjzgKuT/D67C3cCOBx49RBzSdKct98Crqp7gN9O8iLg5G74v1fV9UNPJklz3HSvB/xN4JtDziJJ84pns0lSIxawJDViAUtSIxawJDViAUtSIxawJDViAUtSIxawJDViAUtSI9P9RIwZk+RE4Iq+oeOBdwOLgDcBk934u6rKT92QNGeNvICr6jZgOUCSBcAW4GrgbOCiqvrgqDNJUgutpyBeDNxZVT9tnEOSRq51Aa9i9wd9Apyb5JYklyY5atADkqxOsjbJ2snJyUGrSNKs0KyAkxwOvAL4Qjf0ceAp9KYntgIfGvS4qlpTVRNVNbFkyZJRRJWkoWi5B3w6cFN3zWGq6p6qeqiqfgV8Eji1YTZJGrqWBXwmfdMPSZb23fdqYP3IE0nSCI38KAiAJL8O/A7w5r7h9ydZDhSwaY/7JGnOaVLAVfVL4Df2GHtDiyyS1ErroyAkad6ygCWpkSZTEBq9DevXcfqqs6eMHbN4EZdcfFGjRJIs4HniwVrAwhWrp4xtuX5NozSSwCkISWrGPWDt5Zxzz2fL9h1TxpyukGaeBay9bNm+w+kKaQQs4EMwaA8R3EuUdHAs4EMwaA8R3EuUdHAs4Bk06FAvgFs33s5zVjQIJGmsWcAzaNChXgAPrDtv9GGmwV8YUlsW8Dw2235hSHONxwFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ10uRDOZNsAn4BPATsrKqJJEcDVwDLgE3A66rq/7TIJ0mj0HIP+EVVtbyqJrrb7wSuq6oTgOu625I0Z43TFMQrgU93y58GXtUuiiQNX6sCLuAbSW5Msrobe2JVbQXovj9h0AOTrE6yNsnaycnJEcWVpJnXZA4YeF5V3Z3kCcC1STZO94FVtQZYAzAxMVHDCihJw9ZkD7iq7u6+bwOuBk4F7kmyFKD7vq1FNkkalZEXcJLHJjly1zLwUmA98BXgrG61s4AvjzqbJI1SiymIJwJXJ9n1/J+rqq8nuQG4Mskbgb8HXtsgmySNzMgLuKruAn5rwPi9wItHnUeSWhmnw9AkaV6xgCWpEQtYkhqxgCWpEQtYkhqxgCWpEQtYkhqxgCWpEQtYkhqxgCWpEQtYkhppdT1gzRHnnHs+W7bvmDJ2zOJFXHLxRW0CSbOIBaxHZMv2HSxcsXrq2PVrGqWRZhenICSpEfeANS0b1q/j9FVn7zV+68bbec6KBoGkOcAC1rQ8WAv2mmoAeGDdeaMPI80RTkFIUiMWsCQ1YgFLUiMWsCQ1YgFLUiMWsCQ14mFomnH7OmbYU5SlqSxgzbh9HTPsKcrSVE5BSFIjFrAkNWIBS1IjFrAkNWIBS1IjFrAkNWIBS1IjFrAkNTLyEzGSHAt8BvhnwK+ANVX150neC7wJmOxWfVdVfW3U+TQeBn3YJ3g2neaWFmfC7QT+XVXdlORI4MYk13b3XVRVH2yQSWNm0Id9gmfTaW4ZeQFX1VZga7f8iyS3AseMOocktdZ0DjjJMuAZwPe6oXOT3JLk0iRH7eMxq5OsTbJ2cnJy0CqSNCs0K+AkjwOuAs6rqvuBjwNPAZbT20P+0KDHVdWaqpqoqoklS5aMKq4kzbgmBZzkUfTK97NV9SWAqrqnqh6qql8BnwRObZFNkkZl5AWcJMCngFur6j/1jS/tW+3VwPpRZ5OkUWpxFMTzgDcA65Lc3I29CzgzyXKggE3Amxtkk6SRaXEUxN8AGXCXx/xKmlc8E06SGrGAJakRC1iSGrGAJakRC1iSGrGAJamRFscBa57asH4dp686e8qYl5fUfGYBa2QerAV7XWLSy0tqPrOA1dSgvWKAWzfeznNWNAgkjZAFrKYG7RUDPLDuvNGHkUbMN+EkqRELWJIasYAlqRELWJIa8U24Axj08ei+Q9+OxxJrLrGAD2DQx6P7Dn07HkusucQpCElqxAKWpEacgugMmusF53vnmn39PTuPrBYs4M6guV5wvneu2dffs/PIasEpCElqxAKWpEYsYElqxDlgzVmeRKNxZwFrzjqYk2g8w04tWMASnmGnNixgzXp+qoZmKwtYs56fqqHZal4WsG/OaDr2tWft3LBmyrwsYK9wpunY1571Nz7ytr2KedOPb2fZCU/da13LWvszLwtYeiQGFfOOded5irMOmgUsjZgXBNIuFrA0YuNyQaBBvwj8JbDbKF6fsSvgJCuBPwcWAJdU1Z81jiTNSYN+EThlstsoXp+xKuAkC4D/DPwOsBm4IclXqupHbZNJh2bQkRT7OuJm0Loz8ebeTFzr+mD2Bget65uUg41VAQOnAndU1V0AST4PvBKwgDUrDXrDbl9H3Azrzb2ZuNb1wewNDlrXNykHS1W1zvCwJK8BVlbVOd3tNwDPrqpz+9ZZDez6mzwRuBfYPuqsB7CY8csE5joY45gJzHUwxinT9qpauefguO0BZ8DYlN8QVbUGePjXZpK1VTUx7GAHYxwzgbkOxjhmAnMdjHHMtKdxux7wZuDYvttPAu5ulEWShmrcCvgG4IQkxyU5HFgFfKVxJkkairGagqiqnUnOBa6hdxjapVW14QAPG8dZ/HHMBOY6GOOYCcx1MMYx0xRj9SacJM0n4zYFIUnzhgUsSa1U1az8AlYCtwF3AO+coW1eCmwD1veNHQ1cC/y4+35U330XdM9/G/CyvvFnAeu6+z7C7qmeI4AruvHvAcv6HnNW9xw/Bs7aI9exwDeBW4ENwB+1zgY8Gvg+8MMu039onWmP12wB8APgv41LLmBTt72bgbXjkAtYBHwR2Ejv5+u5Y5DpxO412vV1P3Be61xD6bFhbnxooXv/uO4EjgcOp1cCT5uB7b4QeCZTC/j9dAUPvBP4j93y07rnPQI4rsuzoLvv+90PcoD/AZzejf8h8IlueRVwRd8/wru670d1y/0/XEuBZ3bLRwK3d8/fLFv3+Md16zyq+yF+zji8Xt06bwc+x+4Cbp6LXgEv3iNn01zAp4FzuuXD6RVy89dqj3/r/xv4F+OUa8a6bJTFOWOhey/oNX23LwAumKFtL2NqAd8GLO2WlwK3DXpOekduPLdbZ2Pf+JnAX/Sv0y0fRu8snfSv0933F8CZ+8n4ZXrXyxiLbMCvAzcBzx6HTPSOH78OWMHuAh6HXJvYu4Cb5QIeD/yEbq9wHDIN+Fl/KfC/xi3XTH3N1jngY4Cf9d3e3I0NwxOraitA9/0JB8hwTLc8KNvDj6mqncDPgd/Yz7b2kmQZ8Ax6e5xNsyVZkORmetM211ZV80ydDwN/DPyqb2wcchXwjSQ3dqfUt851PDAJ/JckP0hySZLHjslrtcsq4PJueZxyzYjZWsAHPGW5YYb9ZTuUx+x+wuRxwFXAeVV1f+tsVfVQVS2nt8d5apKTW2dKcgawrapu3E+WkefqPK+qngmcDrw1yQsb5zqM3pTbx6vqGcA/0PuvfctMu5+sdzLWK4Av7CfTyHPNpNlawKM8ZfmeJEsBuu/bDpBhc7c8KNvDj0lyGLAQuG8/23pYkkfRK9/PVtWXxilbVe0A/preG6OtMz0PeEWSTcDngRVJ/usY5KKq7u6+bwOupnf1v5a5NgObu/+5QO/NuGeOw2vVOR24qaru6W6PS66ZM6y5jWF+0fvNfRe9Cfddb8KdNEPbXsbUOeAPMHXi//3d8klMnfi/i90T/zfQe0Nq18T/y7vxtzJ14v/KbvloenNxR3VfPwGO7ssQ4DPAh/fI2iwbsARY1K3zGOA7wBnj8Hr1vT6nsXsOuGku4LHAkX3Lf0vvF1brXN8BTuyW39vlGYu/Q3q/QM8eh5/3oXXZKApzKMHh5fSOBrgTuHCGtnk5sBV4kN5vwjfSmxe6jt4hKdcxtRgv7J7/Nrp3V7vxCWB9d9/F7D705dH0/jt1B713Z4/ve8wfdON39P/Qdfc9n95/g25h96E5L2+ZDXg6vcO8bum29+5uvPnr1bfOaewu4Ka56M23/pDdh+1dOCa5lgNru7/Hv6JXOs3/Dum9sXsvsLBvrHmumf7yVGRJamS2zgFL0qxnAUtSIxawJDViAUtSIxawJDViAWvWSnJhkg1Jbklyc5Jn72fdy7pP3d7f9i5L8pNuWzclee4+1vvTJC95pPmlsfpIImm6unI8g95V4h5IspjeSTmP1Duq6otJXkrvQixP3+N5F1TVu2fgeST3gDVrLQW2V9UDAFW1varuTvLuJDckWZ9kTZK9zu1P8qwk3+ouinPNrtNb9/Bt4De79Td12/0b4LX9e9NJTknyt0l+mOT7SY7sLlL0gS7HLUnePLyXQbOZBazZ6hvAsUluT/KxJP+qG7+4qk6pqpPpnSJ9Rv+DumtqfBR4TVU9i95F+N83YPu/S+9C3rv8v6p6flV9vm9bh9O7qPcfVdVvAS8B/pHeGZQ/r6pTgFOANyU5bgb+zJpjnILQrFRV/zfJs4AXAC8CrkjyTuAXSf6Y3qmsR9M77ferfQ89ETgZuLbbOV5A7/TzXT6Q5E/oXabxjX3jVwyIcSKwtapu6DLdD9BNXzy9b855IXACvesKSA+zgDVrVdVD9K7C9tdJ1gFvpjdnO1FVP0vyXnrn/PcLsKGqBr7BRjcHPGD8HwaMhcGXKgzwtqq65sB/Cs1nTkFoVkpyYpIT+oaW07sQC8D27trJg456uA1YsusIhySPSnLSIcbYCPzzJKd02zqyu7ThNcC/7aY7SPLU7kLn0hTuAWu2ehzw0SSLgJ30rly1GthBb+52E71LEU5RVf/UTQ18JMlCev8GPkxvquKgdNt6fZfjMfTmf18CXELvsqY3dW8CTgKvOtjta+7zamiS1IhTEJLUiAUsSY1YwJLUiAUsSY1YwJLUiAUsSY1YwJLUyP8HUCQEw1Q+ez0AAAAASUVORK5CYII=\n","text/plain":["<Figure size 360x360 with 1 Axes>"]},"metadata":{"needs_background":"light"},"output_type":"display_data"}],"source":["sns.displot(train['SalePrice']);\n","train['SalePrice'].describe()"]},{"cell_type":"code","execution_count":9,"id":"4fb0ce96","metadata":{"execution":{"iopub.execute_input":"2023-02-21T22:21:30.346217Z","iopub.status.busy":"2023-02-21T22:21:30.345331Z","iopub.status.idle":"2023-02-21T22:21:30.689315Z","shell.execute_reply":"2023-02-21T22:21:30.688006Z"},"papermill":{"duration":0.358087,"end_time":"2023-02-21T22:21:30.6917","exception":false,"start_time":"2023-02-21T22:21:30.333613","status":"completed"},"tags":[]},"outputs":[{"data":{"image/png":"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\n","text/plain":["<Figure size 360x360 with 1 Axes>"]},"metadata":{"needs_background":"light"},"output_type":"display_data"}],"source":["sns.displot(np.log(train[\"SalePrice\"]));"]},{"cell_type":"markdown","id":"fc419bae","metadata":{"papermill":{"duration":0.010282,"end_time":"2023-02-21T22:21:30.712818","exception":false,"start_time":"2023-02-21T22:21:30.702536","status":"completed"},"tags":[]},"source":["Log transforming it does a good job of making it more Gaussian (normal) so let's log transform y before training"]},{"cell_type":"code","execution_count":10,"id":"1398e346","metadata":{"execution":{"iopub.execute_input":"2023-02-21T22:21:30.735799Z","iopub.status.busy":"2023-02-21T22:21:30.735428Z","iopub.status.idle":"2023-02-21T22:21:30.740749Z","shell.execute_reply":"2023-02-21T22:21:30.739634Z"},"papermill":{"duration":0.01948,"end_time":"2023-02-21T22:21:30.742843","exception":false,"start_time":"2023-02-21T22:21:30.723363","status":"completed"},"tags":[]},"outputs":[],"source":["y = np.log(train[\"SalePrice\"])"]},{"cell_type":"markdown","id":"94e7dab8","metadata":{"papermill":{"duration":0.010259,"end_time":"2023-02-21T22:21:30.763674","exception":false,"start_time":"2023-02-21T22:21:30.753415","status":"completed"},"tags":[]},"source":["# MODEL TRAINING\n","Now let's see how the XGBoost algorithm performs in cross validation on th train data using these selected features"]},{"cell_type":"code","execution_count":11,"id":"b61d70cb","metadata":{"execution":{"iopub.execute_input":"2023-02-21T22:21:30.787196Z","iopub.status.busy":"2023-02-21T22:21:30.786189Z","iopub.status.idle":"2023-02-21T22:21:33.083801Z","shell.execute_reply":"2023-02-21T22:21:33.082301Z"},"papermill":{"duration":2.313689,"end_time":"2023-02-21T22:21:33.088096","exception":false,"start_time":"2023-02-21T22:21:30.774407","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["RMSE = [-0.12669964 -0.15375259 -0.14261944 -0.12175825 -0.12115651]\n","Mean RMSE = -0.13\n","StDev RMSE = 0.01\n"]}],"source":["XGB_model = XGBRegressor(random_state=0)\n","\n","XGB_scores = cross_val_score(XGB_model, train_select, y, cv=5, scoring=\"neg_root_mean_squared_error\")\n","XGB_mean_score = XGB_scores.mean()\n","XGB_std_score = XGB_scores.std()\n","print(f\"RMSE = {XGB_scores}\")\n","print(f\"Mean RMSE = {XGB_mean_score:.2f}\")\n","print(f\"StDev RMSE = {XGB_std_score:.2f}\")"]},{"cell_type":"markdown","id":"5dd44388","metadata":{"papermill":{"duration":0.01088,"end_time":"2023-02-21T22:21:33.112724","exception":false,"start_time":"2023-02-21T22:21:33.101844","status":"completed"},"tags":[]},"source":["Now we'll take a look at if it is overfitting and implement early stopping to prevent this"]},{"cell_type":"code","execution_count":12,"id":"6c819d4e","metadata":{"execution":{"iopub.execute_input":"2023-02-21T22:21:33.137107Z","iopub.status.busy":"2023-02-21T22:21:33.136709Z","iopub.status.idle":"2023-02-21T22:21:34.100845Z","shell.execute_reply":"2023-02-21T22:21:34.099438Z"},"papermill":{"duration":0.978688,"end_time":"2023-02-21T22:21:34.103275","exception":false,"start_time":"2023-02-21T22:21:33.124587","status":"completed"},"tags":[]},"outputs":[{"data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"needs_background":"light"},"output_type":"display_data"}],"source":["XGB_model = XGBRegressor(random_state=0)\n","\n","X_train, X_test, y_train, y_test = train_test_split(train_select, y, test_size=0.33, random_state=0)\n","\n","eval_set = [(X_train, y_train), (X_test, y_test)]\n","XGB_model.fit(X_train, y_train, eval_metric=\"rmse\", eval_set=eval_set, verbose=False)\n","results = XGB_model.evals_result()\n","\n","epochs = len(results['validation_0']['rmse'])\n","x_axis = range(0, epochs)\n","fig, ax = plt.subplots()\n","ax.plot(x_axis, results['validation_0']['rmse'], label='Train')\n","ax.plot(x_axis, results['validation_1']['rmse'], label='Test')\n","ax.legend()\n","plt.ylabel('RMSE')\n","plt.title('XGBoost RMSE')\n","plt.show()"]},{"cell_type":"code","execution_count":13,"id":"10ccb996","metadata":{"execution":{"iopub.execute_input":"2023-02-21T22:21:34.129394Z","iopub.status.busy":"2023-02-21T22:21:34.128637Z","iopub.status.idle":"2023-02-21T22:21:34.51893Z","shell.execute_reply":"2023-02-21T22:21:34.517894Z"},"papermill":{"duration":0.407152,"end_time":"2023-02-21T22:21:34.521886","exception":false,"start_time":"2023-02-21T22:21:34.114734","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["[0]\tvalidation_0-rmse:8.07524\n","[1]\tvalidation_0-rmse:5.65944\n","[2]\tvalidation_0-rmse:3.97442\n","[3]\tvalidation_0-rmse:2.79185\n","[4]\tvalidation_0-rmse:1.96170\n","[5]\tvalidation_0-rmse:1.38532\n","[6]\tvalidation_0-rmse:0.98054\n","[7]\tvalidation_0-rmse:0.70117\n","[8]\tvalidation_0-rmse:0.50715\n","[9]\tvalidation_0-rmse:0.37409\n","[10]\tvalidation_0-rmse:0.28290\n","[11]\tvalidation_0-rmse:0.22315\n","[12]\tvalidation_0-rmse:0.18618\n","[13]\tvalidation_0-rmse:0.16322\n","[14]\tvalidation_0-rmse:0.14943\n","[15]\tvalidation_0-rmse:0.14093\n","[16]\tvalidation_0-rmse:0.13640\n","[17]\tvalidation_0-rmse:0.13404\n","[18]\tvalidation_0-rmse:0.13070\n","[19]\tvalidation_0-rmse:0.12889\n","[20]\tvalidation_0-rmse:0.12818\n","[21]\tvalidation_0-rmse:0.12774\n","[22]\tvalidation_0-rmse:0.12701\n","[23]\tvalidation_0-rmse:0.12632\n","[24]\tvalidation_0-rmse:0.12571\n","[25]\tvalidation_0-rmse:0.12559\n","[26]\tvalidation_0-rmse:0.12522\n","[27]\tvalidation_0-rmse:0.12524\n","[28]\tvalidation_0-rmse:0.12537\n","[29]\tvalidation_0-rmse:0.12541\n","[30]\tvalidation_0-rmse:0.12505\n","[31]\tvalidation_0-rmse:0.12486\n","[32]\tvalidation_0-rmse:0.12485\n","[33]\tvalidation_0-rmse:0.12459\n","[34]\tvalidation_0-rmse:0.12457\n","[35]\tvalidation_0-rmse:0.12463\n","[36]\tvalidation_0-rmse:0.12461\n","[37]\tvalidation_0-rmse:0.12459\n","[38]\tvalidation_0-rmse:0.12471\n","[39]\tvalidation_0-rmse:0.12476\n","[40]\tvalidation_0-rmse:0.12478\n","[41]\tvalidation_0-rmse:0.12464\n","[42]\tvalidation_0-rmse:0.12458\n"]},{"data":{"text/plain":["XGBRegressor(base_score=0.5, booster='gbtree', callbacks=None,\n","             colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1,\n","             early_stopping_rounds=None, enable_categorical=False,\n","             eval_metric=None, gamma=0, gpu_id=-1, grow_policy='depthwise',\n","             importance_type=None, interaction_constraints='',\n","             learning_rate=0.300000012, max_bin=256, max_cat_to_onehot=4,\n","             max_delta_step=0, max_depth=6, max_leaves=0, min_child_weight=1,\n","             missing=nan, monotone_constraints='()', n_estimators=100, n_jobs=0,\n","             num_parallel_tree=1, predictor='auto', random_state=0, reg_alpha=0,\n","             reg_lambda=1, ...)"]},"execution_count":13,"metadata":{},"output_type":"execute_result"}],"source":["eval_set = [(X_test, y_test)]\n","XGB_model.fit(X_train, y_train, early_stopping_rounds=8, eval_metric=\"rmse\", eval_set=eval_set, verbose=True)"]},{"cell_type":"markdown","id":"dd88ed41","metadata":{"papermill":{"duration":0.014711,"end_time":"2023-02-21T22:21:34.551279","exception":false,"start_time":"2023-02-21T22:21:34.536568","status":"completed"},"tags":[]},"source":["# PREDICTIONS AND OUTPUT\n","\n","Finally we'll make predictons on the test data using the FeatureWiz selected features nad the trained model"]},{"cell_type":"code","execution_count":14,"id":"c71366ba","metadata":{"execution":{"iopub.execute_input":"2023-02-21T22:21:34.582878Z","iopub.status.busy":"2023-02-21T22:21:34.582466Z","iopub.status.idle":"2023-02-21T22:21:34.604083Z","shell.execute_reply":"2023-02-21T22:21:34.603132Z"},"papermill":{"duration":0.040436,"end_time":"2023-02-21T22:21:34.6068","exception":false,"start_time":"2023-02-21T22:21:34.566364","status":"completed"},"tags":[]},"outputs":[],"source":["test_pred = np.exp(XGB_model.predict(test_select))\n","pred = pd.concat([test[\"Id\"],pd.Series(test_pred,name='SalePrice')],axis=1)\n","pred['Id'] = pred['Id'].astype('int')\n","pred.to_csv('/kaggle/working/submission.csv', index=False)"]},{"cell_type":"markdown","id":"6897ce03","metadata":{"papermill":{"duration":0.014207,"end_time":"2023-02-21T22:21:34.636426","exception":false,"start_time":"2023-02-21T22:21:34.622219","status":"completed"},"tags":[]},"source":["# FINAL REMARKS\n","\n","It seems to perform OK in the competion but not spectacularly although I have only implemented it very simply here fr demonstrations purposes.\n","\n","I like the output expalnation and visualisations that FeatureWiz produces however I think I would prefer to dig into the data and have more control over the feature processing myslef. In particualar how each column's NaN values are dalt  with as well as the opprotunity for feature engineering based on common sense knowledge of the data. \n","\n","Fun expereiment though! I hope you enjoyed and learned something. Upvotes and comments welcomed."]}],"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":"3.7.12"},"papermill":{"default_parameters":{},"duration":61.350035,"end_time":"2023-02-21T22:21:35.573292","environment_variables":{},"exception":null,"input_path":"__notebook__.ipynb","output_path":"__notebook__.ipynb","parameters":{},"start_time":"2023-02-21T22:20:34.223257","version":"2.3.4"}},"nbformat":4,"nbformat_minor":5}