PCA_XGBOOST.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "63cfa1a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 利用XGBOOST进行多变量时序预测欺骗干扰\n",
    "\n",
    "# 导入库\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.image as mpimg\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "10607cf1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              count       gpsPdop      gpsNumSv       gpsWeek          itow  \\\n",
      "count  13828.000000  13828.000000  13828.000000  13828.000000  1.382800e+04   \n",
      "mean     116.196722      4.452366     18.793002   2181.948076  3.646376e+08   \n",
      "std       72.814751     19.907183     10.137855      6.920760  9.116327e+07   \n",
      "min        0.000000      1.000000      0.000000   2176.000000  1.888924e+08   \n",
      "25%       49.000000      1.000000     10.000000   2176.000000  2.900716e+08   \n",
      "50%      115.000000      2.500000     16.000000   2176.000000  4.385198e+08   \n",
      "75%      181.000000      2.500000     30.000000   2190.000000  4.389778e+08   \n",
      "max      255.000000    200.000000     32.000000   2190.000000  4.397520e+08   \n",
      "\n",
      "             gpsSec  P_Sol_Status      Pos_Type  AvionicsTemp    MainPowerV  \\\n",
      "count  13828.000000  13828.000000  13828.000000  13828.000000  13828.000000   \n",
      "mean    3544.104525      2.156499     30.114692     36.704917     24.583977   \n",
      "std     2520.235719      4.748022     16.554109      7.101426      0.549781   \n",
      "min        0.000000      0.000000     16.000000     20.000000      0.300000   \n",
      "25%      978.200000      0.000000     16.000000     30.000000     24.600000   \n",
      "50%     2707.100000      0.000000     16.000000     38.000000     24.700000   \n",
      "75%     6121.750000      0.000000     50.000000     43.000000     24.800000   \n",
      "max     6552.600000     13.000000     50.000000     48.000000     25.400000   \n",
      "\n",
      "       ...  rcState  Failure_ad  leftRPM     AirHeight       Failure  \\\n",
      "count  ...  13828.0     13828.0  13828.0  13828.000000  1.382800e+04   \n",
      "mean   ...      1.0        64.0      0.0     83.079227  8.037859e+06   \n",
      "std    ...      0.0         0.0      0.0     85.313009  5.101565e+07   \n",
      "min    ...      1.0        64.0      0.0    -22.200000  3.145920e+06   \n",
      "25%    ...      1.0        64.0      0.0      9.300000  3.145920e+06   \n",
      "50%    ...      1.0        64.0      0.0     30.751469  3.145920e+06   \n",
      "75%    ...      1.0        64.0      0.0    180.200000  3.145920e+06   \n",
      "max    ...      1.0        64.0      0.0    210.800000  5.400168e+08   \n",
      "\n",
      "              WWest        WSouth    Event  Capacity        Jammer  \n",
      "count  13828.000000  13828.000000  13828.0   13828.0  13828.000000  \n",
      "mean       0.849273      0.411852      0.0       0.0      0.500000  \n",
      "std        3.086522      3.364082      0.0       0.0      0.500018  \n",
      "min       -7.470000     -9.080000      0.0       0.0      0.000000  \n",
      "25%       -1.134904     -1.910000      0.0       0.0      0.000000  \n",
      "50%        0.350000      0.360000      0.0       0.0      0.500000  \n",
      "75%        3.404866      2.483067      0.0       0.0      1.000000  \n",
      "max        9.190000     10.730000      0.0       0.0      1.000000  \n",
      "\n",
      "[8 rows x 65 columns]\n"
     ]
    }
   ],
   "source": [
    "# 导入数据集\n",
    "dataset = pd.read_csv('./data/SMOTE数据拆分/0在第一位.csv')\n",
    "#dataset = pd.read_csv('./data/SMOTE数据拆分/1在第一位.csv')\n",
    "#dataset = pd.read_csv('./data/SMOTE数据拆分/2在第一位.csv')\n",
    "#dataset = pd.read_csv('./data/SMOTE数据拆分/3在第一位.csv')\n",
    "#dataset = pd.read_csv('./data/SMOTE数据拆分/4在第一位.csv')\n",
    "#dataset = pd.read_csv('./data/SMOTE数据拆分/5在第一位.csv')\n",
    "#dataset = pd.read_csv('./data/SMOTE数据拆分/6在第一位.csv')\n",
    "#dataset = pd.read_csv('./data/SMOTE数据拆分/7在第一位.csv')\n",
    "#dataset = pd.read_csv('./data/SMOTE数据拆分/8在第一位.csv')\n",
    "#dataset = pd.read_csv('./data/SMOTE数据拆分/9在第一位.csv')\n",
    " \n",
    "print(dataset.describe())#查看数据概述"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e3fb22dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>gpsPdop</th>\n",
       "      <th>gpsNumSv</th>\n",
       "      <th>gpsWeek</th>\n",
       "      <th>itow</th>\n",
       "      <th>gpsSec</th>\n",
       "      <th>P_Sol_Status</th>\n",
       "      <th>Pos_Type</th>\n",
       "      <th>AvionicsTemp</th>\n",
       "      <th>MainPowerV</th>\n",
       "      <th>...</th>\n",
       "      <th>rcState</th>\n",
       "      <th>Failure_ad</th>\n",
       "      <th>leftRPM</th>\n",
       "      <th>AirHeight</th>\n",
       "      <th>Failure</th>\n",
       "      <th>WWest</th>\n",
       "      <th>WSouth</th>\n",
       "      <th>Event</th>\n",
       "      <th>Capacity</th>\n",
       "      <th>Jammer</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>157.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2176.0</td>\n",
       "      <td>438825400.0</td>\n",
       "      <td>6287.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>24.7</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.1</td>\n",
       "      <td>3145920.0</td>\n",
       "      <td>-3.46</td>\n",
       "      <td>2.11</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>161.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>2190.0</td>\n",
       "      <td>289780800.0</td>\n",
       "      <td>1422.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>24.7</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>181.0</td>\n",
       "      <td>3145920.0</td>\n",
       "      <td>1.50</td>\n",
       "      <td>-1.53</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>2190.0</td>\n",
       "      <td>289912800.0</td>\n",
       "      <td>1554.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>24.7</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>181.2</td>\n",
       "      <td>3145920.0</td>\n",
       "      <td>2.33</td>\n",
       "      <td>-1.54</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>170.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2176.0</td>\n",
       "      <td>438838400.0</td>\n",
       "      <td>6300.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>24.7</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.5</td>\n",
       "      <td>3145920.0</td>\n",
       "      <td>-3.50</td>\n",
       "      <td>2.47</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>124.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>2190.0</td>\n",
       "      <td>289743600.0</td>\n",
       "      <td>1385.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>24.9</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>178.3</td>\n",
       "      <td>3145920.0</td>\n",
       "      <td>2.43</td>\n",
       "      <td>-1.39</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 65 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   count  gpsPdop  gpsNumSv  gpsWeek         itow  gpsSec  P_Sol_Status  \\\n",
       "0  157.0      2.5      11.0   2176.0  438825400.0  6287.8           0.0   \n",
       "1  161.0      1.0      31.0   2190.0  289780800.0  1422.4           0.0   \n",
       "2   37.0      1.0      31.0   2190.0  289912800.0  1554.4           0.0   \n",
       "3  170.0      2.5      11.0   2176.0  438838400.0  6300.8           0.0   \n",
       "4  124.0      1.0      31.0   2190.0  289743600.0  1385.2           0.0   \n",
       "\n",
       "   Pos_Type  AvionicsTemp  MainPowerV  ...  rcState  Failure_ad  leftRPM  \\\n",
       "0      16.0          41.0        24.7  ...      1.0        64.0      0.0   \n",
       "1      50.0          29.0        24.7  ...      1.0        64.0      0.0   \n",
       "2      50.0          30.0        24.7  ...      1.0        64.0      0.0   \n",
       "3      16.0          41.0        24.7  ...      1.0        64.0      0.0   \n",
       "4      50.0          29.0        24.9  ...      1.0        64.0      0.0   \n",
       "\n",
       "   AirHeight    Failure  WWest  WSouth  Event  Capacity  Jammer  \n",
       "0        9.1  3145920.0  -3.46    2.11    0.0       0.0       1  \n",
       "1      181.0  3145920.0   1.50   -1.53    0.0       0.0       0  \n",
       "2      181.2  3145920.0   2.33   -1.54    0.0       0.0       0  \n",
       "3        8.5  3145920.0  -3.50    2.47    0.0       0.0       1  \n",
       "4      178.3  3145920.0   2.43   -1.39    0.0       0.0       0  \n",
       "\n",
       "[5 rows x 65 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#查看数据集的前5个值\n",
    "dataset.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2cd7694d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#将数据集拆分为独立变量和因变量\n",
    "X = dataset[dataset.columns[:-1]]   #从0到倒数第一列\n",
    "y = dataset.Jammer                  #只包括data的y这一列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9d290d25",
   "metadata": {},
   "outputs": [],
   "source": [
    "#将数据集分割为训练集和测试集\n",
    "from sklearn.model_selection import train_test_split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.30, random_state = 34)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "839e8553",
   "metadata": {},
   "outputs": [],
   "source": [
    "#功能缩放，使变量在单个缩放\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "sc = StandardScaler()\n",
    "X_train = sc.fit_transform(X_train)\n",
    "X_test = sc.transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c9655318",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 0.81415647 -0.09689669 -0.76446413 ...  0.68142973  0.\n",
      "   0.        ]\n",
      " [ 1.6745845  -0.09689669 -0.17302073 ...  0.22885598  0.\n",
      "   0.        ]\n",
      " [-1.33817966 -0.17330128  1.10843997 ... -0.53998726  0.\n",
      "   0.        ]\n",
      " ...\n",
      " [ 1.28939091 -0.17330128  1.10843997 ... -0.98526328  0.\n",
      "   0.        ]\n",
      " [-1.29690892 -0.07142849 -1.15875973 ...  0.0151235   0.\n",
      "   0.        ]\n",
      " [ 0.43124901 -0.09689669 -0.76446413 ...  0.2932567   0.\n",
      "   0.        ]]\n",
      "[2.33678490e+01 3.18725787e+00 3.03194230e+00 2.51087245e+00\n",
      " 2.08711708e+00 1.91180891e+00 1.72409460e+00 1.55472582e+00\n",
      " 1.47879104e+00 1.30063764e+00 1.18260495e+00 1.08997130e+00\n",
      " 1.06476709e+00 1.01020145e+00 9.90861306e-01 8.75162663e-01\n",
      " 8.54478701e-01 7.89884302e-01 7.35038442e-01 6.91760564e-01\n",
      " 6.25664898e-01 5.89849803e-01 5.15159979e-01 4.70747447e-01\n",
      " 4.68835051e-01 4.06773562e-01 3.76937198e-01 3.53897849e-01\n",
      " 3.37002812e-01 3.28773425e-01 2.99186854e-01 2.82829954e-01\n",
      " 2.71790674e-01 2.35498667e-01 2.29580275e-01 1.62486428e-01\n",
      " 1.44659916e-01 9.03284495e-02 8.62687453e-02 6.79442602e-02\n",
      " 4.19267443e-02 3.09647042e-02 2.38853672e-02 2.35073090e-02\n",
      " 2.02411199e-02 1.95629393e-02 1.46835916e-02 1.33727316e-02\n",
      " 1.06742425e-02 8.28699667e-03 5.24572203e-03 4.03952635e-03\n",
      " 3.16287636e-03 2.09494455e-03 2.30336391e-04 7.00874251e-05\n",
      " 1.36374361e-31 1.36374361e-31 1.36374361e-31 1.36374361e-31\n",
      " 1.36374361e-31 1.36374361e-31 1.36374361e-31 1.36374361e-31]\n",
      "[4.02852323e-01 5.49470443e-02 5.22694663e-02 4.32864317e-02\n",
      " 3.59810594e-02 3.29588171e-02 2.97226977e-02 2.68028482e-02\n",
      " 2.54937631e-02 2.24224701e-02 2.03876340e-02 1.87906669e-02\n",
      " 1.83561566e-02 1.74154669e-02 1.70820506e-02 1.50874525e-02\n",
      " 1.47308693e-02 1.36172878e-02 1.26717672e-02 1.19256740e-02\n",
      " 1.07862113e-02 1.01687735e-02 8.88115094e-03 8.11549674e-03\n",
      " 8.08252781e-03 7.01261269e-03 6.49824576e-03 6.10105664e-03\n",
      " 5.80979301e-03 5.66792167e-03 5.15786109e-03 4.87587471e-03\n",
      " 4.68556196e-03 4.05990235e-03 3.95787165e-03 2.80120069e-03\n",
      " 2.49387879e-03 1.55722616e-03 1.48723849e-03 1.17133173e-03\n",
      " 7.22800217e-04 5.33819052e-04 4.11774128e-04 4.05256558e-04\n",
      " 3.48948770e-04 3.37257209e-04 2.53139216e-04 2.30540517e-04\n",
      " 1.84019650e-04 1.42864491e-04 9.04341390e-05 6.96398104e-05\n",
      " 5.45267169e-05 3.61160019e-05 3.97090679e-06 1.20827903e-06\n",
      " 2.35103915e-33 2.35103915e-33 2.35103915e-33 2.35103915e-33\n",
      " 2.35103915e-33 2.35103915e-33 2.35103915e-33 2.35103915e-33]\n",
      "0.9999999999999998\n"
     ]
    }
   ],
   "source": [
    "#PCA分析\n",
    "from sklearn.decomposition import PCA\n",
    "pca = PCA(n_components=64)#改写为自变量的维度值\n",
    "\n",
    "\n",
    "#数据的标准化\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "X_norm = StandardScaler().fit_transform(X_train)\n",
    "print(X_norm)\n",
    "\n",
    "X_train_pca = pca.fit_transform(X_norm)\n",
    "#计算分析后各成分的方差以及方差比例\n",
    "var = pca.explained_variance_\n",
    "var_ratio = pca.explained_variance_ratio_\n",
    "print(var)\n",
    "print(var_ratio)\n",
    "print(sum(var_ratio))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "06b99de6",
   "metadata": {},
   "outputs": [],
   "source": [
    "##可视化方差比例\n",
    "#fig2 = plt.figure(figsize=(10,5))\n",
    "##plt.bar([1,2,3,4,5,6,7,8,9,10,11,12,13,14],var_ratio)\n",
    "#var=range(1,65,1)\n",
    "#plt.bar(var,var_ratio)\n",
    "#plt.xlabel('Components')\n",
    "#plt.xlabel('Components')\n",
    "#plt.ylabel('Variance ratio')\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0cdfd73c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(9679, 25) (9679, 64)\n",
      "[0.40285232 0.05494704 0.05226947 0.04328643 0.03598106 0.03295882\n",
      " 0.0297227  0.02680285 0.02549376 0.02242247 0.02038761 0.01879066\n",
      " 0.01835615 0.01741546 0.01708201 0.01508744 0.01473085 0.01361684\n",
      " 0.01267174 0.01192535 0.01078613 0.01016828 0.00887858 0.00811432\n",
      " 0.00808217]\n",
      "<class 'numpy.ndarray'>\n",
      "0.933\n"
     ]
    },
    {
     "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": [
    "# 训练集数据降维到25维\n",
    "pca = PCA(n_components=25)\n",
    "X_train_pca = pca.fit_transform(X_norm)\n",
    "#var_ratio2 = pca.fit_transform(X_norm)\n",
    "print(X_train_pca.shape,X_norm.shape)\n",
    "\n",
    "# 计算方差比例\n",
    "var_ratio2 = pca.explained_variance_ratio_\n",
    "print(var_ratio2)\n",
    "print(type(var_ratio2))\n",
    "\n",
    "var = list(range(1, 26))\n",
    "\n",
    "#var_ratio2='{:.4f}'.format(var_ratio2[0])\n",
    "\n",
    "#var_ratio2=int(var_ratio2)\n",
    "\n",
    "var_ratio2 = np.around(var_ratio2,decimals=4)# 保留4位小数\n",
    "A=np.sum(var_ratio2)\n",
    "print(A)\n",
    "\n",
    "# 绘制图像\n",
    "\n",
    "#plt.bar(var,var_ratio2)\n",
    "plt.bar(var,var_ratio2,tick_label=[\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\n",
    "                                   \"16\",\"17\",\"18\",\"19\",\"20\",\"21\",\"22\",\"23\",\"24\",\"25\"])\n",
    "\n",
    "plt.xlabel('Components')\n",
    "plt.ylabel('Variance ratio')\n",
    "\n",
    "\n",
    "#for i in range(len(var)):\n",
    "#    plt.text(x = i-0.1, y = var_ratio2[i]+1,s = var_ratio2[i] ) # s表示注释内容\n",
    "\n",
    "for var,var_ratio2 in zip(var,var_ratio2):   #柱子上的数字显示\n",
    " plt.text(var,var_ratio2,'%.4f'%var_ratio2,ha='center',va='bottom',fontsize=7);\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "856b405a",
   "metadata": {},
   "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": [
    "#降维数据的可视化\n",
    "fig3 = plt.figure()\n",
    "plt.scatter(X_train_pca[:,0][y_train==0],X_train_pca[:,1][y_train==0],marker='x',label='negative')\n",
    "plt.scatter(X_train_pca[:,0][y_train==1],X_train_pca[:,1][y_train==1],marker='*',label='positive')\n",
    "plt.xlabel('PC1')\n",
    "plt.ylabel('PC2')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7d44621b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:48:18] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n",
       "              colsample_bynode=1, colsample_bytree=0.8,\n",
       "              enable_categorical=False, gamma=0, gpu_id=-1,\n",
       "              importance_type=None, interaction_constraints='',\n",
       "              learning_rate=0.1, max_delta_step=0, max_depth=5,\n",
       "              min_child_weight=1, missing=nan, monotone_constraints='()',\n",
       "              n_estimators=1000, n_jobs=4, nthread=4, num_parallel_tree=1,\n",
       "              predictor='auto', random_state=27, reg_alpha=0, reg_lambda=1,\n",
       "              scale_pos_weight=1, seed=27, subsample=0.8, tree_method='exact',\n",
       "              validate_parameters=1, verbosity=None)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#降维后的模型建立与训练\n",
    "\n",
    "import xgboost as xgb\n",
    "from xgboost.sklearn import XGBClassifier\n",
    "\n",
    "\n",
    "model = XGBClassifier(\n",
    "     learning_rate =0.1,\n",
    "     n_estimators=1000,\n",
    "     max_depth=5,\n",
    "     min_child_weight=1,\n",
    "     gamma=0,\n",
    "     subsample=0.8,\n",
    "     colsample_bytree=0.8,\n",
    "     objective= 'binary:logistic',\n",
    "     nthread=4,\n",
    "     scale_pos_weight=1,\n",
    "     seed=27)\n",
    "\n",
    "\n",
    "param_grid = {\n",
    " 'max_depth':range(3,10,2),\n",
    " 'min_child_weight':range(1,6,2)\n",
    "}\n",
    "\n",
    "\n",
    "#model2 = KNeighborsClassifier(n_neighbors=1,weights='uniform')\n",
    "model.fit(X_train_pca,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8453adcf",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:48:52] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:48:53] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:48:53] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:48:53] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:48:54] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:48:54] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:48:55] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:48:55] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:48:56] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:48:56] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:48:57] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:48:57] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:48:57] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:48:58] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:48:58] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:48:59] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:48:59] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:48:59] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:00] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:00] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:01] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:01] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:01] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:02] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:02] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:03] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:03] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:03] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:04] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:04] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:05] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:05] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:06] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:06] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:07] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:08] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:08] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:09] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:09] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:10] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:10] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:11] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:11] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:12] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:12] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:13] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:13] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:14] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:14] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:15] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:15] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:16] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:16] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:17] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:17] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:18] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:18] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:19] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:19] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:20] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:20] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:21] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:21] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:22] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:23] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:23] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:24] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:25] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:25] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:26] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:26] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:27] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:28] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:28] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:29] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:29] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:30] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:30] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:31] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:31] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:32] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:32] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:33] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:33] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:34] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:34] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:35] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:35] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:36] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:36] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:37] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:38] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:38] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:39] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:40] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:40] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:41] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:42] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:42] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:43] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:44] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:44] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:45] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:45] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:46] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:46] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:47] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:48] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:48] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:49] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:49] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:50] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:50] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:51] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:51] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:52] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:52] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:53] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:54] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:54] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:49:55] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n",
      "{'max_depth': 5, 'min_child_weight': 1} 0.9960740596716435\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "gsearch = GridSearchCV(estimator = XGBClassifier(\n",
    "       learning_rate =0.1, n_estimators=140, max_depth=9,\n",
    "       min_child_weight=1, gamma=0, subsample=0.8,colsample_bytree=0.8,\n",
    "       objective= 'binary:logistic', nthread=4,scale_pos_weight=1, seed=27),\n",
    "       param_grid=param_grid,cv=10)\n",
    "gsearch.fit(X_train_pca,y_train)\n",
    "print(gsearch1.best_params_,gsearch1.best_score_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c0235790",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:51:49] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n",
       "              colsample_bynode=1, colsample_bytree=0.8,\n",
       "              enable_categorical=False, gamma=0, gpu_id=-1,\n",
       "              importance_type=None, interaction_constraints='',\n",
       "              learning_rate=0.1, max_delta_step=0, max_depth=5,\n",
       "              min_child_weight=1, missing=nan, monotone_constraints='()',\n",
       "              n_estimators=1000, n_jobs=4, nthread=4, num_parallel_tree=1,\n",
       "              predictor='auto', random_state=27, reg_alpha=0, reg_lambda=1,\n",
       "              scale_pos_weight=1, seed=27, subsample=0.8, tree_method='exact',\n",
       "              validate_parameters=1, verbosity=None)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PCA_XGB = XGBClassifier(\n",
    "     learning_rate =0.1,\n",
    "     n_estimators=1000,\n",
    "     max_depth=5,\n",
    "     min_child_weight=1,\n",
    "     gamma=0,\n",
    "     subsample=0.8,\n",
    "     colsample_bytree=0.8,\n",
    "     objective= 'binary:logistic',\n",
    "     nthread=4,\n",
    "     scale_pos_weight=1,\n",
    "     seed=27)\n",
    "PCA_XGB.fit(X_train_pca,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "aff8f900",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 3.81409779 -0.65702324 -0.76557071 ... -0.2527326  -1.394315\n",
      "  -0.55807676]\n",
      " [ 5.36095085  1.87807236  0.74462987 ...  0.51079064  1.1000759\n",
      "   0.2198836 ]\n",
      " [ 5.12458606  1.3172413  -0.32712823 ...  1.28479536 -0.42858202\n",
      "   0.22547031]\n",
      " ...\n",
      " [-4.60335854 -2.88270681  2.27562931 ...  0.07544946 -1.30485688\n",
      "  -0.438487  ]\n",
      " [-4.24007725  1.13403645 -0.7506259  ...  0.2953474  -0.26845506\n",
      "  -0.04867779]\n",
      " [ 5.32647779  1.82341097  1.96751973 ... -0.63234445  0.78141431\n",
      "   0.7624296 ]]\n",
      "(4149, 25)\n"
     ]
    }
   ],
   "source": [
    "#测试集数据降维到25维\n",
    "pca = PCA(n_components=25)\n",
    "\n",
    "X_norm = StandardScaler().fit_transform(X_test)\n",
    "X_test_pca = pca.fit_transform(X_norm)\n",
    "\n",
    "print(X_test_pca)\n",
    "print(X_test_pca.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "afda5315",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 0 0 ... 1 1 0]\n",
      "(4149,)\n",
      "PCA测试集准确率: 0.9670\n",
      "\n",
      "\n",
      "PCA测试集精确率: 0.9477\n",
      "\n",
      "\n",
      "PCA测试集召回率: 0.9878\n",
      "\n",
      "\n",
      "PCA测试集F1值: 0.9674\n"
     ]
    }
   ],
   "source": [
    "#模型预测\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.metrics import precision_score\n",
    "from sklearn.metrics import recall_score\n",
    "from sklearn.metrics import f1_score\n",
    "\n",
    "y_predict_pca = PCA_XGB.predict(X_test_pca)\n",
    "print(y_predict_pca)\n",
    "print(y_predict_pca.shape)\n",
    "accuracy_pca = accuracy_score(y_test,y_predict_pca)\n",
    "print(\"PCA测试集准确率: {0:.4f}\".format(accuracy_pca))\n",
    "\n",
    "precision_pca =precision_score(y_test,y_predict_pca)\n",
    "print(\"\\n\\nPCA测试集精确率: {0:.4f}\".format(precision_pca))\n",
    "\n",
    "recall_pca =recall_score(y_test,y_predict_pca)\n",
    "print(\"\\n\\nPCA测试集召回率: {0:.4f}\".format(recall_pca))\n",
    "\n",
    "f1_pca =f1_score(y_test,y_predict_pca)\n",
    "print(\"\\n\\nPCA测试集F1值: {0:.4f}\".format(f1_pca))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "47b2b8ca",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1982  112]\n",
      " [  25 2030]]\n"
     ]
    }
   ],
   "source": [
    "#制作PCA混淆矩阵\n",
    "from sklearn.metrics import confusion_matrix\n",
    "cm = confusion_matrix(y_test, y_predict_pca)\n",
    "print(cm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "06138214",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "正确预测值的数量:  4012\n",
      "错误预测值的数量:  137\n"
     ]
    }
   ],
   "source": [
    "#从混淆矩阵中寻找准确性。\n",
    "a = cm.shape\n",
    "corrPred = 0\n",
    "falsePred = 0\n",
    "\n",
    "for row in range(a[0]):\n",
    "    for c in range(a[1]):\n",
    "        if row == c:\n",
    "            corrPred +=cm[row,c]\n",
    "        else:\n",
    "            falsePred += cm[row,c]\n",
    "print('正确预测值的数量: ', corrPred)\n",
    "print('错误预测值的数量: ', falsePred)\n",
    "#print ('\\n\\nKNN分类器的准确率为: ', corrPred/(cm.sum()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f54925d4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0     0.9875    0.9465    0.9666      2094\n",
      "           1     0.9477    0.9878    0.9674      2055\n",
      "\n",
      "    accuracy                         0.9670      4149\n",
      "   macro avg     0.9676    0.9672    0.9670      4149\n",
      "weighted avg     0.9678    0.9670    0.9670      4149\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score,f1_score,confusion_matrix,classification_report\n",
    "\n",
    "print(classification_report(y_test, y_predict_pca,digits=4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d02fcdf0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "classes = list(set(y))\n",
    "classes.sort()\n",
    "confusion = confusion_matrix(y_predict_pca, y_test)\n",
    "plt.imshow(confusion, cmap=plt.cm.Blues)\n",
    "indices = range(len(confusion))\n",
    "plt.xticks(indices, classes, fontsize=20)\n",
    "plt.yticks(indices, classes, fontsize=20)\n",
    "plt.colorbar().ax.tick_params(labelsize=20)\n",
    "plt.xlabel('Predicted label', fontsize=20)\n",
    "plt.ylabel('True label', fontsize=20)\n",
    "for first_index in range(len(confusion)):\n",
    "    for second_index in range(len(confusion[first_index])):\n",
    "        plt.text(first_index, second_index, confusion[first_index][second_index],\n",
    "                 va='center', ha='center',fontsize=20, )\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "25c126c4",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:54:45] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:54:46] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:54:47] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:54:48] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:54:49] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:54:50] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:54:51] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:54:52] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:54:53] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:54:54] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n",
      "10折交叉验证准确率： [0.9928 0.9855 0.9928 0.9976 0.9952 0.9952 0.9952 1.     0.9855 1.    ]\n",
      "\n",
      "\n",
      "10折交叉验证平均准确率： 0.994\n"
     ]
    }
   ],
   "source": [
    "# K折交叉验证模块 \n",
    "from sklearn.model_selection import cross_val_score \n",
    "#使用K折交叉验证模块  \n",
    "#scores = cross_val_score(nvclassifier, X_test, y_test, cv=10, scoring='accuracy')  \n",
    "scores = cross_val_score(PCA_XGB, X_test_pca, y_test, cv=10,scoring='accuracy')  \n",
    "\n",
    "scores = np.around(scores,decimals=4)\n",
    "\n",
    "#将10次的预测准确率打印出  \n",
    "print('10折交叉验证准确率：',scores)  \n",
    "# [0.92 1.   0.83 0.88 0.91 0.96 1.   1.   0.78 0.74]\n",
    "#将10次的预测准确平均率打印出0.901630434782608  \n",
    "\n",
    "scoresmean = np.around(scores.mean(),decimals=4)\n",
    "\n",
    "print('\\n\\n10折交叉验证平均准确率：',scoresmean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "e42e0ef7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:04] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:05] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:06] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:07] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:08] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:09] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:10] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:11] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:12] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:13] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n",
      "10折交叉验证精确率： [1.     0.9901 0.9903 1.     1.     0.9951 0.9904 1.     0.9808 1.    ]\n",
      "\n",
      "\n",
      "10折交叉验证平均精确率： 0.9947\n"
     ]
    }
   ],
   "source": [
    "precision = cross_val_score(PCA_XGB, X_test_pca, y_test, cv=10,scoring='precision') \n",
    "\n",
    "precision = np.around(precision,decimals=4)\n",
    "\n",
    "print('10折交叉验证精确率：',precision)\n",
    "\n",
    "precisionmean = np.around(precision.mean(),decimals=4)\n",
    "\n",
    "print('\\n\\n10折交叉验证平均精确率：',precisionmean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "08376479",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:19] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:20] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:21] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:22] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:23] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:24] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:25] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:26] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:27] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:28] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n",
      "10折交叉验证精确率： [0.9854 0.9805 0.9951 0.9951 0.9903 0.9951 1.     1.     0.9903 1.    ]\n",
      "\n",
      "\n",
      "10折交叉验证平均召回率： 0.9932\n"
     ]
    }
   ],
   "source": [
    "recall = cross_val_score(PCA_XGB, X_test_pca, y_test, cv=10,scoring='recall') \n",
    "\n",
    "recall = np.around(recall,decimals=4)\n",
    "\n",
    "print('10折交叉验证精确率：',recall)\n",
    "\n",
    "recallmean = np.around(recall.mean(),decimals=4)\n",
    "\n",
    "print('\\n\\n10折交叉验证平均召回率：',recallmean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "e11a7acc",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:40] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:41] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:42] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:43] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:44] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:45] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:46] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:47] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:48] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:55:48] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n",
      "10折交叉验证f1值： [0.9926 0.9853 0.9927 0.9976 0.9951 0.9951 0.9952 1.     0.9855 1.    ]\n",
      "\n",
      "\n",
      "10折交叉验证平均f1值： 0.9939\n"
     ]
    }
   ],
   "source": [
    "f1 = cross_val_score(PCA_XGB, X_test_pca, y_test, cv=10,scoring='f1') \n",
    "\n",
    "f1 = np.around(f1,decimals=4)\n",
    "\n",
    "print('10折交叉验证f1值：',f1)\n",
    "\n",
    "f1mean = np.around(f1.mean(),decimals=4)\n",
    "\n",
    "print('\\n\\n10折交叉验证平均f1值：',f1mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "801539fa",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:56:00] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:56:01] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:56:02] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:56:03] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:56:04] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:56:05] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:56:06] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:56:07] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:56:08] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUN\\anaconda3\\envs\\LSTM\\lib\\site-packages\\xgboost\\sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22:56:09] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.5.1/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n",
      "10折交叉验证roc_auc值： [0.9999 0.9995 0.9999 1.     1.     0.9995 0.9999 1.     0.999  1.    ]\n",
      "\n",
      "\n",
      "10折交叉验证平均ROC_AUC值： 0.9998\n"
     ]
    }
   ],
   "source": [
    "roc_auc = cross_val_score(PCA_XGB,  X_test_pca, y_test, cv=10,scoring='roc_auc') \n",
    "\n",
    "roc_auc = np.around(roc_auc,decimals=4)\n",
    "\n",
    "print('10折交叉验证roc_auc值：',roc_auc)\n",
    "\n",
    "roc_auc = np.around(roc_auc.mean(),decimals=4)\n",
    "\n",
    "print('\\n\\n10折交叉验证平均ROC_AUC值：',roc_auc.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "d957c5af",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 1]\n"
     ]
    },
    {
     "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": [
    "from sklearn.metrics import precision_recall_curve\n",
    "precision, recall, t =precision_recall_curve(y_test, y_predict_pca) #y_score是预测的概率值，y_test是真实值标签值\n",
    "print(t) #t是阈值\n",
    "plt.xlabel('Recall')\n",
    "plt.ylabel('Precision')\n",
    "plt.ylim([0.0, 1.0])\n",
    "plt.xlim([0.0, 1.0])\n",
    "plt.plot(recall, precision)\n",
    "plt.title(\"Precision-Recall\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "971c23c8",
   "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": "3.6.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}