PP+ML.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "f57d1d4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as patches\n",
    "import matplotlib.ticker as ticker\n",
    "import os \n",
    "import sys\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.linear_model import LogisticRegression \n",
    "from sklearn.svm import SVC\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.inspection import permutation_importance\n",
    "import collections\n",
    "\n",
    "from shutil import get_terminal_size"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53583942",
   "metadata": {},
   "source": [
    "# Preprocessing\n",
    "\n",
    "**Start by looking at the data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "d6c49fa4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               ID  CountDeposit  CountWithdrawal  TotalDeposits  \\\n",
      "0       100001096            86               17           3218   \n",
      "1       100002057            26                0            300   \n",
      "2       100009325            76                9            558   \n",
      "3       100014865            21                0            475   \n",
      "4       100018655            45                3            915   \n",
      "...           ...           ...              ...            ...   \n",
      "207393  899973616            38                2            715   \n",
      "207394  899987209           192               31           3882   \n",
      "207395  899994536             1                1            100   \n",
      "207396  899994603             1                0             10   \n",
      "207397  899998254             5                0           1400   \n",
      "\n",
      "        TotalWithdrawal  CountPaymentMethod  DifferentMethodWithdrawals  \n",
      "0                  2622                   1                      2359.8  \n",
      "1                     0                   1                         0.0  \n",
      "2                   315                   1                         0.0  \n",
      "3                     0                   1                         0.0  \n",
      "4                   690                   1                         0.0  \n",
      "...                 ...                 ...                         ...  \n",
      "207393              601                   2                       601.0  \n",
      "207394             3573                   2                         0.0  \n",
      "207395               79                   2                        79.0  \n",
      "207396                0                   1                         0.0  \n",
      "207397                0                   1                         0.0  \n",
      "\n",
      "[207398 rows x 7 columns]\n",
      "               ID  Multi_Device  IP_Counts   e_11234   e_23456   e_34454  \\\n",
      "0       100001096             1          3   5599.89    986.36    283.05   \n",
      "1       100002057             1          1   9669.93  17181.08  20905.39   \n",
      "2       100009325             1          2  12835.48   3036.08   4729.43   \n",
      "3       100014865             1          4   1452.38   1764.97  10649.72   \n",
      "4       100018655             1          3   6301.98   1963.98  12770.14   \n",
      "...           ...           ...        ...       ...       ...       ...   \n",
      "207393  899973616             1          1   1431.52   4228.40    858.00   \n",
      "207394  899987209             1          3   8782.55   1877.56   2613.07   \n",
      "207395  899994536             1          2   8628.77   5786.43  15898.21   \n",
      "207396  899994603             1          2   7522.49  16485.09  37475.16   \n",
      "207397  899998254             1          1   9229.69   3589.55    578.35   \n",
      "\n",
      "         e_43568  e_64645  \n",
      "0         662.98     0.40  \n",
      "1       38635.13     3.22  \n",
      "2         180.38     1.11  \n",
      "3        6059.89     0.38  \n",
      "4        5180.09     0.89  \n",
      "...          ...      ...  \n",
      "207393   6142.00     1.35  \n",
      "207394     14.89     0.25  \n",
      "207395  36966.07     1.66  \n",
      "207396  37475.16     3.15  \n",
      "207397  31473.88     1.22  \n",
      "\n",
      "[207398 rows x 8 columns]\n"
     ]
    }
   ],
   "source": [
    "df1 = pd.read_csv(\"details.csv\"); #print(df1) \n",
    "df2 = pd.read_csv(\"details_fixed.csv\"); #print(df2) \n",
    "df3 = pd.read_csv(\"payments.csv\"); print(df3) \n",
    "df4 = pd.read_csv(\"profiling.csv\"); print(df4) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3980464e",
   "metadata": {},
   "source": [
    "**Merge the datasets (by ID)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "441f0372",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                 ID      Life_Time            Age      Is_Retail  \\\n",
      "count  2.073980e+05  207398.000000  207398.000000  207398.000000   \n",
      "mean   5.008909e+08       2.603342      41.490410       0.410023   \n",
      "std    2.306288e+08       3.122641      13.123745       0.491839   \n",
      "min    1.000011e+08       0.000000      18.000000       0.000000   \n",
      "25%    3.009800e+08       0.000000      31.000000       0.000000   \n",
      "50%    5.018123e+08       1.000000      39.000000       0.000000   \n",
      "75%    7.004120e+08       4.000000      51.000000       1.000000   \n",
      "max    8.999983e+08      21.000000     120.000000       1.000000   \n",
      "\n",
      "        Is_CRM_Email   CountDeposit  CountWithdrawal  TotalDeposits  \\\n",
      "count  207398.000000  207398.000000    207398.000000   2.073980e+05   \n",
      "mean        0.418042      26.245721         2.734848   1.418705e+03   \n",
      "std         0.493238      41.822574         7.559037   5.183685e+03   \n",
      "min         0.000000       1.000000         0.000000   5.000000e+00   \n",
      "25%         0.000000       4.000000         0.000000   1.150000e+02   \n",
      "50%         0.000000      12.000000         1.000000   4.700000e+02   \n",
      "75%         1.000000      31.000000         3.000000   1.437000e+03   \n",
      "max         1.000000    1241.000000       550.000000   1.027375e+06   \n",
      "\n",
      "       TotalWithdrawal  CountPaymentMethod  DifferentMethodWithdrawals  \\\n",
      "count    207398.000000       207398.000000               207398.000000   \n",
      "mean        774.237823            1.284207                  250.602113   \n",
      "std        3850.914994            0.592588                 2074.381593   \n",
      "min           0.000000            1.000000                    0.000000   \n",
      "25%           0.000000            1.000000                    0.000000   \n",
      "50%          30.000000            1.000000                    0.000000   \n",
      "75%         500.000000            1.000000                    0.000000   \n",
      "max      472869.000000            4.000000               472869.000000   \n",
      "\n",
      "        Multi_Device      IP_Counts        e_11234        e_23456  \\\n",
      "count  207398.000000  207398.000000  207398.000000  207398.000000   \n",
      "mean        0.836286       2.441658    7003.326455    6358.703833   \n",
      "std         0.370017       1.517011    7367.510253    6071.720284   \n",
      "min         0.000000       1.000000       0.000000       0.060000   \n",
      "25%         1.000000       1.000000    1135.527500    1298.802500   \n",
      "50%         1.000000       2.000000    4289.085000    4071.280000   \n",
      "75%         1.000000       3.000000   10862.585000   11675.885000   \n",
      "max         1.000000       7.000000   47299.040000   28135.150000   \n",
      "\n",
      "             e_34454        e_43568        e_64645  \n",
      "count  207398.000000  207398.000000  207398.000000  \n",
      "mean    14666.698999   18722.672481       1.516427  \n",
      "std     13152.810961   15426.545697       1.101400  \n",
      "min         0.000000       0.000000       0.000000  \n",
      "25%      3454.317500    3320.920000       0.490000  \n",
      "50%     10207.420000   14811.630000       1.350000  \n",
      "75%     25097.677500   34063.392500       2.670000  \n",
      "max     70086.760000   56891.910000       4.310000  \n"
     ]
    }
   ],
   "source": [
    "df23 = df2.merge(df3,on = 'ID')\n",
    "df234 = df23.merge(df4,on = 'ID'); print(df234.describe())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71570d13",
   "metadata": {},
   "source": [
    "**Check for missing values**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "96bda9fe",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Column ID  - missing values =  0\n",
      "Column Life_Time  - missing values =  0\n",
      "Column Age  - missing values =  0\n",
      "Column Is_Retail  - missing values =  0\n",
      "Column Is_CRM_Email  - missing values =  0\n",
      "Column CountDeposit  - missing values =  0\n",
      "Column CountWithdrawal  - missing values =  0\n",
      "Column TotalDeposits  - missing values =  0\n",
      "Column TotalWithdrawal  - missing values =  0\n",
      "Column CountPaymentMethod  - missing values =  0\n",
      "Column DifferentMethodWithdrawals  - missing values =  0\n",
      "Column Multi_Device  - missing values =  0\n",
      "Column IP_Counts  - missing values =  0\n",
      "Column e_11234  - missing values =  0\n",
      "Column e_23456  - missing values =  0\n",
      "Column e_34454  - missing values =  0\n",
      "Column e_43568  - missing values =  0\n",
      "Column e_64645  - missing values =  0\n"
     ]
    }
   ],
   "source": [
    "def missing(data):\n",
    "    cols = data.columns \n",
    "    for (i,col) in enumerate(cols):\n",
    "        print(\"Column %s  - missing values = \" %(col), data[col].isnull().sum())\n",
    "missing(df234)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6da9cbed",
   "metadata": {},
   "source": [
    "**Nothing missing - add in the suspect player data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "e24f1ed1",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             ID  Target_ml\n",
      "0     100095464          1\n",
      "1     100333793          1\n",
      "2     101329354          1\n",
      "3     101607100          1\n",
      "4     102590942          1\n",
      "...         ...        ...\n",
      "1747  898004908          1\n",
      "1748  898448610          1\n",
      "1749  899624336          1\n",
      "1750  899737861          1\n",
      "1751  899788191          1\n",
      "\n",
      "[1752 rows x 2 columns]\n",
      "                 ID  Target_ml\n",
      "count  1.752000e+03     1752.0\n",
      "mean   4.995049e+08        1.0\n",
      "std    2.322098e+08        0.0\n",
      "min    1.000955e+08        1.0\n",
      "25%    2.941709e+08        1.0\n",
      "50%    4.951482e+08        1.0\n",
      "75%    6.985999e+08        1.0\n",
      "max    8.997882e+08        1.0\n",
      "           ID  Life_Time  Age  Is_Retail  Is_CRM_Email  CountDeposit  \\\n",
      "26  100095464          9   55          0             0           222   \n",
      "\n",
      "    CountWithdrawal  TotalDeposits  TotalWithdrawal  CountPaymentMethod  \\\n",
      "26               38           5640             5200                   4   \n",
      "\n",
      "    DifferentMethodWithdrawals  Multi_Device  IP_Counts  e_11234  e_23456  \\\n",
      "26                      5200.0             0          2   777.65  7381.43   \n",
      "\n",
      "    e_34454  e_43568  e_64645  \n",
      "26   648.52    111.7     2.54  \n",
      "               ID  Life_Time  Age  Is_Retail  Is_CRM_Email  CountDeposit  \\\n",
      "0       100001096          1   33          1             0            86   \n",
      "1       100002057          1   44          0             0            26   \n",
      "2       100009325          7   30          1             1            76   \n",
      "3       100014865          3   31          1             0            21   \n",
      "4       100018655          9   61          1             1            45   \n",
      "...           ...        ...  ...        ...           ...           ...   \n",
      "207393  899973616          2   32          0             1            38   \n",
      "207394  899987209          0   23          0             0           192   \n",
      "207395  899994536          0   34          0             1             1   \n",
      "207396  899994603          3   35          0             0             1   \n",
      "207397  899998254          0   39          0             0             5   \n",
      "\n",
      "        CountWithdrawal  TotalDeposits  TotalWithdrawal  CountPaymentMethod  \\\n",
      "0                    17           3218             2622                   1   \n",
      "1                     0            300                0                   1   \n",
      "2                     9            558              315                   1   \n",
      "3                     0            475                0                   1   \n",
      "4                     3            915              690                   1   \n",
      "...                 ...            ...              ...                 ...   \n",
      "207393                2            715              601                   2   \n",
      "207394               31           3882             3573                   2   \n",
      "207395                1            100               79                   2   \n",
      "207396                0             10                0                   1   \n",
      "207397                0           1400                0                   1   \n",
      "\n",
      "        DifferentMethodWithdrawals  Multi_Device  IP_Counts   e_11234  \\\n",
      "0                           2359.8             1          3   5599.89   \n",
      "1                              0.0             1          1   9669.93   \n",
      "2                              0.0             1          2  12835.48   \n",
      "3                              0.0             1          4   1452.38   \n",
      "4                              0.0             1          3   6301.98   \n",
      "...                            ...           ...        ...       ...   \n",
      "207393                       601.0             1          1   1431.52   \n",
      "207394                         0.0             1          3   8782.55   \n",
      "207395                        79.0             1          2   8628.77   \n",
      "207396                         0.0             1          2   7522.49   \n",
      "207397                         0.0             1          1   9229.69   \n",
      "\n",
      "         e_23456   e_34454   e_43568  e_64645  Target_ml  \n",
      "0         986.36    283.05    662.98     0.40          0  \n",
      "1       17181.08  20905.39  38635.13     3.22          0  \n",
      "2        3036.08   4729.43    180.38     1.11          0  \n",
      "3        1764.97  10649.72   6059.89     0.38          0  \n",
      "4        1963.98  12770.14   5180.09     0.89          0  \n",
      "...          ...       ...       ...      ...        ...  \n",
      "207393   4228.40    858.00   6142.00     1.35          0  \n",
      "207394   1877.56   2613.07     14.89     0.25          0  \n",
      "207395   5786.43  15898.21  36966.07     1.66          0  \n",
      "207396  16485.09  37475.16  37475.16     3.15          0  \n",
      "207397   3589.55    578.35  31473.88     1.22          0  \n",
      "\n",
      "[207398 rows x 19 columns]\n",
      "                 ID      Life_Time            Age      Is_Retail  \\\n",
      "count  2.073980e+05  207398.000000  207398.000000  207398.000000   \n",
      "mean   5.008909e+08       2.603342      41.490410       0.410023   \n",
      "std    2.306288e+08       3.122641      13.123745       0.491839   \n",
      "min    1.000011e+08       0.000000      18.000000       0.000000   \n",
      "25%    3.009800e+08       0.000000      31.000000       0.000000   \n",
      "50%    5.018123e+08       1.000000      39.000000       0.000000   \n",
      "75%    7.004120e+08       4.000000      51.000000       1.000000   \n",
      "max    8.999983e+08      21.000000     120.000000       1.000000   \n",
      "\n",
      "        Is_CRM_Email   CountDeposit  CountWithdrawal  TotalDeposits  \\\n",
      "count  207398.000000  207398.000000    207398.000000   2.073980e+05   \n",
      "mean        0.418042      26.245721         2.734848   1.418705e+03   \n",
      "std         0.493238      41.822574         7.559037   5.183685e+03   \n",
      "min         0.000000       1.000000         0.000000   5.000000e+00   \n",
      "25%         0.000000       4.000000         0.000000   1.150000e+02   \n",
      "50%         0.000000      12.000000         1.000000   4.700000e+02   \n",
      "75%         1.000000      31.000000         3.000000   1.437000e+03   \n",
      "max         1.000000    1241.000000       550.000000   1.027375e+06   \n",
      "\n",
      "       TotalWithdrawal  CountPaymentMethod  DifferentMethodWithdrawals  \\\n",
      "count    207398.000000       207398.000000               207398.000000   \n",
      "mean        774.237823            1.284207                  250.602113   \n",
      "std        3850.914994            0.592588                 2074.381593   \n",
      "min           0.000000            1.000000                    0.000000   \n",
      "25%           0.000000            1.000000                    0.000000   \n",
      "50%          30.000000            1.000000                    0.000000   \n",
      "75%         500.000000            1.000000                    0.000000   \n",
      "max      472869.000000            4.000000               472869.000000   \n",
      "\n",
      "        Multi_Device      IP_Counts        e_11234        e_23456  \\\n",
      "count  207398.000000  207398.000000  207398.000000  207398.000000   \n",
      "mean        0.836286       2.441658    7003.326455    6358.703833   \n",
      "std         0.370017       1.517011    7367.510253    6071.720284   \n",
      "min         0.000000       1.000000       0.000000       0.060000   \n",
      "25%         1.000000       1.000000    1135.527500    1298.802500   \n",
      "50%         1.000000       2.000000    4289.085000    4071.280000   \n",
      "75%         1.000000       3.000000   10862.585000   11675.885000   \n",
      "max         1.000000       7.000000   47299.040000   28135.150000   \n",
      "\n",
      "             e_34454        e_43568        e_64645      Target_ml  \n",
      "count  207398.000000  207398.000000  207398.000000  207398.000000  \n",
      "mean    14666.698999   18722.672481       1.516427       0.008448  \n",
      "std     13152.810961   15426.545697       1.101400       0.091522  \n",
      "min         0.000000       0.000000       0.000000       0.000000  \n",
      "25%      3454.317500    3320.920000       0.490000       0.000000  \n",
      "50%     10207.420000   14811.630000       1.350000       0.000000  \n",
      "75%     25097.677500   34063.392500       2.670000       0.000000  \n",
      "max     70086.760000   56891.910000       4.310000       1.000000  \n"
     ]
    }
   ],
   "source": [
    "## ADD SUSPECT PLAYERS\n",
    "df5 = pd.read_csv(\"suspect.csv\"); print(df5); print(df5.describe())\n",
    "print(df234.loc[df234['ID'] == 100095464]) # LOOKS LIKE THESE ALREADY IN OTHER DATAFRAME\n",
    "\n",
    "df2345 = pd.merge(df234, df5, how='outer', on='ID');\n",
    "df2345['Target_ml'] = df2345['Target_ml'].replace(np.nan, 0)\n",
    "df2345['Target_ml'] = df2345['Target_ml'].astype(int)\n",
    "print(df2345); print(df2345.describe())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58ca1af7",
   "metadata": {},
   "source": [
    "**Look at the feauture distributions**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "550fe1c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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pQ4cOuaQ2zgQBAFpMiYf2e+Fl9OPHjzfaPj4+XhaLpd71aWlpSktLc7Cq86666iqZzWaHxg127dpVx44d07Fjx3TZZZdJOn+G6fjx44qJial3u+Dg4Ab7feWVV3T//ffXu/7111/XpEmT9Oabbyo5ObnZdVdWVur06dMqKirSFVdc0eztG0MIgiF40iS05eXlHj9GCXCVa91dQD1WrVqllJQUhYWF6U9/+pOk85eCKisr5e/vX6v9v//970veV1VVlSoqKvTjjz9KkioqKnTmzBn5+/vL19e3VvvAwECNGzdOL774om6//XZFR0fr1VdfVXFxsYYNG2ZvZzKZtHz5cqWmptbqo1evXkpISNDvfvc7vfzyy7LZbJo0aZJ9eX3Kysou+ThfeuklzZgxQ+vWrdOtt97aaPuSkhKtW7dOP//5z3XZZZepqKhIDz/8sDp37qzrrrvukutoCJfDYAjVk9B6wo+nhDEA/yc+Pl5JSUnq1KmTfHx8dP/992v8+PEueUbNli1b1LZtW1199dX2fbdt21YrV660twkODtbrr79uf/3MM89o2LBhuuWWWxQREaHXX39d77//vv0sjsVikZ+fn/r161fnPn18fPTOO+/IZrMpLi5OV111lUwmk/7xj3+4bH61Rx55RGVlZRo2bJiCg4PtP1u3bq3zOE0mk1atWqXY2FiZzWbdcsstMpvN+vDDD9WmTRuX1MiZIACA4f3kJz/RsmXLWmRfAwcObPSW9IvPwPj7+2vRokVatGhRne2zs7M1fvx4xcbG1ttnx44d9cYbbzS/4EvUlNvuLzzO9u3ba+PGja4sqRZCEAAArdy4cePcXUKrRAgCALhE+/btdfjwYbfuH2gIIQgA4BI+Pj7q0MHTng9dmyvnpoJnY2A0AAAwJEIQAMDpXDEXFXAhZ/yOEYIAAE5T/UwdT5+0GK1fRUWFJNX5bKWmYkwQ0MKY5R7ezNfXV+Hh4fYB0fzuwBWqqqp05MgRBQUFyc/v0qMMIQhoYcxyD2/XsWNHSXLrnWHwfj4+PurSpYtDIZsQBABwKpPJpMjISF1++eWqrKx0dznwUgEBAQ4/7ZoQBABwCV9fX4fGawCuxsBoAABgSJwJusBDDz2kl19+WYsXL9bDDz/s7nJgIMxyDwAtjxD0X+vWrdNHH32kqKgod5cCA6qe5R4A0HK4HCbp0KFDeuihh7Ry5Ur7My4AAIB38/gQtGrVKk2YMEEJCQkKDAyUyWRSVlZWg9ts375dd9xxh8LDw2U2m9W3b1+9+eab9bYfM2aMHn30UfXs2dPJ1QMAAE/l8ZfD0tPTZbFYFBERocjISFkslgbbb968WcnJyWrTpo1SUlIUEhKitWvXauTIkSoqKtLUqVNrtH/ppZdktVprLQcAAN7N488EZWZmqrCwUEeOHNHEiRMbbHv27FmNGzdOPj4+2rJli5YuXapFixbpiy++UFxcnNLS0mqEqG+++UZz5szRihUrHH7WAAAAaF08/pt/yJAhio6OblLbTZs2ac+ePRo9erRuvPFG+/KwsDClpaWpoqJCK1assC//17/+pSNHjqhHjx7y8/OTn5+fLBaLHnvssRrbAwAA7+Pxl8OaIycnR5I0dOjQWuuSk5MlSbm5ufZld999txISEmq1S01N1ZgxY5q1b5vNJqvVWuc67vpBa8LcZgBag/q+c6WmzzDvVSGooKBAkhQbG1trXceOHRUcHGxvI0nh4eEKDw+v0c7f31+RkZHq0aNHs/ZdXFys4ODgOtc19c0APAFzmwFoDer7zm0Oj78c1hylpaWSzl/+qktoaKi9DQAAMDavOhPkDIWFhZe0XVRUlHbv3u3cYgAAQJ3KysrqXRcXF6fi4uJG+/CqEFR9Bqi+sz0nT55Uu3btXLJvk8nE6XgAAFpIQ9+5TR0j6FUhqHosUEFBgXr16lVj3cGDB1VWVqbExER3lAa0asxtBsAbeVUIGjBggObNm6fs7GylpKTUWLd+/Xp7GwDNw9xmALyRV4WgwYMHq1u3blq9erUeffRR+7N+SktLNXfuXAUEBOiBBx5wb5EAHNIab+GXuI0f8EQeH4IyMzOVl5cnSdq1a5d9WfUzgZKSkjR27FhJkp+fnzIzM5WcnKz+/fvXmDbDYrFo4cKFiomJccdhAHCS1ngLv8Rt/IAn8vgQlJeXV+Mpz5KUn5+v/Px8++vqECRJgwYNUl5enmbNmqU1a9aosrJSPXv21IIFCzRy5MgWqxsAAHg2jw9BWVlZjc4af7HExES9//77rikIAAB4Ba96WCIAAEBTefyZIABojCfdwi9xGz/QWhCCALR63MIP4FJwOQwAABgSIQgAABgSl8MAwMla4wMdeZgjjIgQBABO1hof6MjDHGFEXA4DAACGRAgCAACGRAgCAACGxJggAGgBnvRARx7mCJxHCAKAFsADHQHPw+UwAABgSIQgAABgSIQgAABgSIQgAABgSIQgAABgSIQgAABgSIQgAABgSDwnCAAMhlnugfMIQQBgMMxyD5zH5TAAAGBIhCAAAGBIhCAAAGBIjAkCADDLPQyJEAQAYJZ7GBKXwwAAgCERggAAgCERggAAgCERggAAgCERggAAgCERggAAgCERggAAgCEZPgQ999xzio+PV3BwsMLDw3Xbbbfp448/dndZAADAxQwfgqKjo/XnP/9ZX3zxhbZt26YePXooOTlZR48edXdpAADAhQwfgn75y18qOTlZ3bt317XXXquFCxeqtLRUX331lbtLAwAALuTxIWjVqlWaMGGCEhISFBgYKJPJpKysrAa32b59u+644w6Fh4fLbDarb9++evPNNxvdV0VFhZYuXap27dqpZ8+eTjoCAADgiTx+7rD09HRZLBZFREQoMjJSFoulwfabN29WcnKy2rRpo5SUFIWEhGjt2rUaOXKkioqKNHXq1FrbbN26VcOGDdPp06fVsWNHbdiwQZdddpmrDgkAAHgAjz8TlJmZqcLCQh05ckQTJ05ssO3Zs2c1btw4+fj4aMuWLVq6dKkWLVqkL774QnFxcUpLS6szRCUkJGjnzp3atm2bhg0bpvvuu08lJSWuOiQAAOABPD4EDRkyRNHR0U1qu2nTJu3Zs0ejR4/WjTfeaF8eFhamtLQ0VVRUaMWKFbW2a9u2rXr06KE+ffooMzNTPj4+Wr58ebPqtNlsslqtdf4AAADnqu8712q1ymazNakPj78c1hw5OTmSpKFDh9Zal5ycLEnKzc1ttB+bzaYff/yxWfsuLi5WcHBwvf0BAADnqe87tzm8KgQVFBRIkmJjY2ut69ixo4KDg+1tqk2bNk0///nP1alTJx07dkxLlizRDz/8oBEjRrRIzQAAwD28KgSVlpZKOn/5qy6hoaH2NtWKi4uVkpKiw4cP67LLLlPv3r21detWXXPNNc3ad1RUlHbv3n1phQMAgGYpKyurd11cXJyKi4sb7cOrQtClWLlypVP6MZlMMpvNTukLAAA0rKHvXJPJ1KQ+vCoEVZ8BuvhsT7WTJ0+qXbt2LVkSAKCZ6hpHWV5e7oZKmi4oKKjJX7zwHA6FIF9fX6WkpOj11193Vj0OqR4LVFBQoF69etVYd/DgQZWVlSkxMdEdpTVZVVVVrTvKjhw54lH/AJSUlNSqsaqqyk3VAPA2p0+frrVsyZIlbqik6R5//HGuBrRCDoWg0NBQde7c2Vm1OGzAgAGaN2+esrOzlZKSUmPd+vXr7W082dGjR/Xss8/WWHbxa080adIkhYSEuLsMAACazKHnBCUmJuqLL75wVi0OGzx4sLp166bVq1dr586d9uWlpaWaO3euAgIC9MADD7ivQAAA4DEcOhOUkZGhgQMH6rXXXnNZuMjMzFReXp4kadeuXfZl1c8ESkpK0tixYyVJfn5+yszMVHJysvr3719j2gyLxaKFCxcqJibGJXUa3dGjRz3mVDCX6wAATeFQCNqwYYMGDhyoMWPGaPHixerdu7euuOKKWoPDTCaTZsyYcUn7yMvLq/WU5/z8fOXn59tfV4cgSRo0aJDy8vI0a9YsrVmzRpWVlerZs6cWLFigkSNHXlINaFxCQoK7S2gQl+uA1m3SpEkKCgpydxmSzg/S9vQxSmgah88EVfvss8/02Wef1dnOkRCUlZXV6KzxF0tMTNT7779/SfvzRF9LinB3ERfYLSnJ3UUAMJSgoCCPOdsM7+FQCNq8ebOz6kADIiR1cHcRF2BqWQCAN3AoBHn6nVYAAAD18aqHJcJ9POmSXYmka91dBADA4zkcgs6ePavFixfrb3/7m7755huVl5fr7NmzkqSdO3dq6dKlmjx5suLi4hwuFp7L0y7ZAQDQGIdC0OnTpzV06FBt27ZNERERCg0NrXFrcteuXbV8+XJddtll+uMf/+hwsQAAAM7i0MMS586dq/z8fM2bN08HDx6scau6dH4urwEDBtif1gwAAOApHApBa9as0aBBg/Tkk0/KZDLVOXlct27dtG/fPkd2AwAA4HQOhaB9+/Y1+pC8kJCQemd1BwAAcBeHQlBISIgOHz7cYJs9e/aoQweGzAIAAM/iUAjq27ev3n33XZ04caLO9UVFRXrvvffUv39/R3YDAADgdA6FoCeeeELHjx/X4MGDlZ+fb781vry8XB9++KGSk5N19uxZTZkyxSnFAgAAOItDt8j3799fL730kh577LEaZ3uqJ6r09fXVkiVL1KtXL8eqBAAAcDKHH5b40EMPaeDAgXr55Zf18ccf69ixYwoNDVWfPn00adIkxcfHO6NOAAAAp3LKtBnXXHONXnjhBWd0BQAA0CIcGhMEAADQWjklBP3973/XXXfdpS5duigsLExdunTRXXfdpbffftsZ3QMAADidQ5fDzp49q9GjR2vt2rWy2Wzy8/NT+/btdfDgQb377rtat26dRowYodWrV8vPjwnrAQCA53DoTNC8efP01ltv6dZbb9XWrVt15swZHThwQGfOnNGWLVuUlJSktWvXav78+c6qFwAAwCkcCkHLly/X1VdfrY0bN6pfv37y8TnfnY+Pj5KSkrRx40bFxcVp2bJlTikWAADAWRwKQQcOHNDw4cPrvdTl7++v4cOH68CBA47sBgAAwOkcGqjTuXNnlZWVNdjGarWqS5cujuwGaJaqOpYdPXpUZrO5xWupS0lJiaxWa41lVVV1VQ0AcCWHQtDYsWP17LPPKj09XZGRkbXW79+/X2vWrNG0adMc2Q3QLMfqWJaQkNDidTTHpEmT7E9aBwC0jGaFoH379tV4fd999yk/P1833XSTJk+erKSkJF1xxRU6dOiQtm7dqhdeeEFJSUm69957nVo0AACAo5oVgmJiYmQymWott9ls+sMf/lDn8nfeeUfr1q2zT64KAADgCZoVgh544IE6QxAAAEBr06wQlJWV5aIyANf6WlKEu4v4rxJJ17q7CACAcyZQBTxdhKQO7i4CAOBRmEAVAAAYksMhKC8vT3fffbe6du2qwMBA+fr61vph3jAAAOBpHEonK1euVGpqqmw2m7p166bExEQCDwAAaBUcSixz5sxRu3bt9N577ykxMdFZNQEAALicQ5fDioqKlJKSQgACAACtjkMhKDo6WhUVFc6qBQAAoMU4FILGjRundevW6dixumZrAgAA8FwOhaCpU6fqF7/4hfr166fXX39dX331lfbt21fnT3OsWrVKEyZMUEJCggIDA2UymRp8UOPJkyc1ZcoURUdHKzAwUDExMXriiSfqneG+qqpKixcvVs+ePdW2bVt16NBBo0aN0vfff9+sOgEAQOvl8K1cN998s1avXq0HHnig3jYmk6lZc4elp6fLYrEoIiJCkZGRslgs9ba1Wq0aMGCAdu7cqaFDh2rUqFHasWOHFi5cqNzcXG3ZskVt2rSpsc2ECROUmZmp+Ph4PfrooyouLtabb76p7Oxs/etf/1JsbGyTawUAAK2TQyFo8eLFmjx5svz9/TVo0CBFRkY65Rb5zMxMxcbGKjo6WvPnz9dTTz1Vb9tnnnlGO3fu1LRp0zR//nz78unTp2vBggV67rnnamy/efNmZWZmqn///tqwYYMCAgIkSaNHj9Ydd9yhhx9+WOvXr3f4GAAAgGdzKLE899xzuvLKK7Vt2zZ16tTJWTVpyJAhTWpns9mUmZmp4OBgzZgxo8a6GTNm6C9/+YsyMzNrhKBXX31V0vnb+6sDkCQNGzZMAwcOVHZ2tvbt26cuXbo44UgAAICncmhM0MGDBzVixAinBqDmKCgoUHFxsfr16yez2VxjndlsVr9+/fT999+rqKjIvjwnJ8e+7mLJycmSpNzcXNcWDgAA3M6hENSjRw+dOHHCSaU0X0FBgSTVO4anenl1O6vVqgMHDqhr167y9fVttH1z2Gw2Wa3WOn8AAIBz1feda7VaZbPZmtSHQ5fDfv/732vq1KmyWCyKjo52pKtLUlpaKkkKCwurc31oaGiNds1t3xzFxcUKDg6uc11T3wwAANA09X3nNodDIah79+4aMGCAEhISNHnyZN1www32IHGx/v37O7IrAAAAp3IoBA0cOFAmk0k2m00zZsyQyWSqt+25c+cc2VWdqs/o1Hfm5uTJkzXaNbd9c0RFRWn37t3N3g4AADRffc8ClKS4uDgVFxc32odDIWjmzJkNBh9Xa2wMz8VjhsxmsyIjI7V3716dO3eu1rigxsYYNcRkMtUanA0AAFyjoe/cpmYTh0JQRkaGI5s7LDY2VlFRUcrPz5fVaq3xF2K1WpWfn6+uXbuqc+fO9uUDBgzQG2+8ofz8/FqX6KqfD8SlOwAAvJ/jTzZ0I5PJpLFjx2r27NmaM2dOjYclzpkzR2VlZUpLS6uxzfjx4/XGG29oxowZNR6W+P777ysnJ0dDhw51yyBvGEdVHcuOHj3qMWcSS0pKat3VWFVVV9UA0Lp5ZAjKzMxUXl6eJGnXrl32ZTk5OZKkpKQkjR07VpL05JNP6h//+IcWLFigHTt26Oabb9bnn3+u7Oxs9e7dW5MnT67R96BBgzR27FhlZmbq5ptv1p133qkDBw5ozZo1uuyyy7R48eIWO04YU13TDSckJLR4Hc0xadIkhYSEuLsMAHAqh0KQj49Pk667NXfusLy8PK1YsaLGsvz8fOXn59tfV4cgs9ms3NxcZWRkaO3atdq8ebMiIyM1depUzZo1S23btq3V/yuvvKKePXtq6dKleuGFFxQcHKxf/OIX+tOf/qTu3bs3uU4AANB6ORSC+vfvX2cIKi0tVUFBgaxWq2644QaFh4c3q9+srKwGZ42/WFhYmJ577jk999xzTWrv4+OjRx99VI8++miz6gIAAN7DoRBUfXmqLuXl5Zo+fbo++OADbdiwwZHdAAAAOJ3LxgQFBQXpxRdfVO/evfXEE09o+fLlrtoV0Op9LSnC3UX8V4mka91dBAC0AJcPjL711lu1atUqV+8GaNUiJHVwdxEAYDAOTaDaFEeOHGnwqY4AAADu4LIzQVVVVXr99de1Zs0aj7/9FwCApqprUuzy8nI3VNI8QUFBbp3lwRM5FIK6detW5/KzZ8/q8OHDqqyslL+/v+bNm+fIbgAA8BinT5+utWzJkiVuqKR5Hn/8cY95KKuncCgEVVVV1Zkq/f39dd1116l37956+OGHFR8f78huAAAAnM6hEFRYWOikMgAAAFqWywdGAwAAeKJmnwn6zW9+0+ydmEwm/c///E+ztwMAoDWYNGmSgoKC3F2GXXl5easYp+RuzQ5BzZnOwmQyyWazEYIAAF4tKCiIQcetULND0EcffdSkdt99950yMjK0Z8+eZhcFAADgas0OQX369GlwfUlJiZ5++mm9+uqrqqioUFJSkhYsWHDJBQIAgOZpjc8ycsdzjJz2sMTy8nItXLhQixYt0qlTpxQfH6+5c+dq+PDhztoFAABogtb4LCN3PMfI4RB07tw5vfLKK5ozZ44OHTqkTp066fnnn9eDDz4oHx9uPgMAAJ7JoRD0v//7v0pPT9d3332nsLAwzZ8/X48++qjatGnjrPoAAABc4pJCUE5OjqZNm6ZPP/1UAQEBmjp1qtLS0hQeHu7k8gAAAFyj2SFo2LBhys7Olo+Pjx588EHNnj1bnTp1ckVtANygqo5lR48e9Zjbf0tKSmS1Wmssq6qqq2oAF/KkZxl5ynOMmh2C1q9fL5PJpC5duujgwYMaP358o9uYTCb985//vKQCAbSsY3UsS0hIaPE6mmPkyJHq0qWLu8uwI6jBE/Eso9ou6XKYzWbT3r17tXfv3ia1b+lb3gAYi6eHNOn8/8JDQkLcXQaACzQ7BDU1+AAAAHiyZoeg6OhoV9QBAADQopz2sEQA3utrSRHuLuK/dktKcncRALwCIQhAoyIkdXB3Ef9VUscyTwpp0vkar3V3EQAaRQgC0Op5UkgD0HowrwUAADAkQhAAADAkQhAAADAkQhAAADAkQhAAADAkQhAAADAkQhAAADAkQhAAADAkQhAAADAkQhAAADAkps0AACerqmPZ0aNHZTabW7yWupSUlMhqtdZYVlVVV9WAd/OKELRq1Spt3bpVn332mXbt2qWKigotX75cqampdbY/efKkMjIytHbtWh08eFCRkZG69957NWvWLAUHB7ds8QC8zrE6liUkJLR4Hc0xadIkhYSEuLsMoEV5RQhKT0+XxWJRRESEIiMjZbFY6m1rtVo1YMAA7dy5U0OHDtWoUaO0Y8cOLVy4ULm5udqyZYvatGnTgtUDAAB38IoxQZmZmSosLNSRI0c0ceLEBts+88wz2rlzp6ZNm6b169dr/vz5Wr9+vaZNm6bt27frueeea6GqAQCAO3lFCBoyZIiio6MbbWez2ZSZmang4GDNmDGjxroZM2YoODhYmZmZrioTAAB4EK+4HNZUBQUFKi4uVnJycq0BimazWf369dP69etVVFSkzp07N6tvm81Wa6DhhX0DMLavJUW4u4j/KpF0rbuLABxU33eudP47uSkMF4IkKTY2ts71sbGxWr9+vQoKCpodgoqLi+sdVN3UNwOA94qQ1MHdRQBexBk3MhkqBJWWlkqSwsLC6lwfGhpaox0AeCNu4QfOM1QIcqWoqCjt3r3b3WUAQKO4hR/eoKysrN51cXFxKi4ubrQPQ4Wg6jNA9Z3pOXnyZI12zWEymTzmf1EAAHi7hr5zTSZTk/rwirvDmqp6LFD12KCLNTZmCAAAeA/DhaCoqCjl5+fXut5stVqVn5+vrl27NntQNAAAaH0MFYJMJpPGjh2rsrIyzZkzp8a6OXPmqKysTOPGjXNTdQDgPl9LOuwhP1+7+FiBal4xJigzM1N5eXmSpF27dtmX5eTkSJKSkpI0duxYSdKTTz6pf/zjH1qwYIF27Nihm2++WZ9//rmys7PVu3dvTZ482R2HAABuxS38MCKvCEF5eXlasWJFjWX5+fnKz8+3v64OQWazWbm5ufYJVDdv3qzIyEhNnTpVs2bNUtu2bVu0dgAA4B5eEYKysrKUlZXV5PZhYWF67rnnmCcMAAADM9SYIAAAgGqEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiEIAAAYEiGDEGrVq3ShAkTlJCQoMDAQJlMJmVlZbm7LAAA0IL83F2AO6Snp8tisSgiIkKRkZGyWCzuLgkAALQwQ54JyszMVGFhoY4cOaKJEye6uxwAAOAGhjwTNGTIEHeXAABopaqqqmS1WmssO3LkiMrLy91UUW0lJSW1aqyqqnJTNZ7LkCHIFWw2W61fuGpms7mFqwEAuMqxY8f07LPP1lh28WtPNGnSJIWEhLi7DKep7ztXOv+d3BSEICcpLi5WcHBwneua+mYAAICmqe87tzkMOSYIAACAM0FOEhUVpd27d7u7DAAADKGsrKzedXFxcSouLm60D0KQk5hMJsb+AIBBfS0pwt1FXKBE0rXuLsLFGvrONZlMTeqDEAQAgIMiJHVwdxFoNsYEAQAAQyIEAQAAQzLk5bDMzEzl5eVJknbt2mVflpOTI0lKSkrS2LFj3VUeAABoAYYMQXl5eVqxYkWNZfn5+crPz7e/JgQBAODdDBmCsrKymDUeAACDY0wQAAAwJEIQAAAwJEIQAAAwJEIQAAAwJEIQAAAwJEIQAAAwJEIQAAAwJEIQAAAwJEIQAAAwJEIQAAAwJEIQAAAwJEKQAVglmf77Y3VzLYCn4nMCNMxqtcpkMslkMslq9Y5PCSEIAAAYkmFD0Pbt23XHHXcoPDxcZrNZffv21ZtvvunusgAAQAvxc3cB7rB582YlJyerTZs2SklJUUhIiNauXauRI0eqqKhIU6dOdXeJAADAxQx3Jujs2bMaN26cfHx8tGXLFi1dulSLFi3SF198obi4OKWlpclisTS73/3793vVddKW5unjMajPMZ5eX2vg6X+HHl9fKxjP4ul/h85WUVGhjIwMZWRkqKKiwuH+LnyPbTZbk7Yx3JmgTZs2ac+ePRozZoxuvPFG+/KwsDClpaUpNTVVK1as0MyZM91X5EVKHNz+wg/TEUnlDvZ3rI5lnlQj9VHfpfD0Go1UX1217N+/34EepfLy/6vIYrEoKCjokvs6cOBArWWe9jvo6X+Hp0+f9ogwargQlJOTI0kaOnRorXXJycmSpNzc3Evuv6431Ww2X3J/knStQ1vX1NWJfV3I02ukPscYqT7J82s0Yn1JSUlO6ys+Pt5pfVVrDb+Dnv532FwXf99e+LqpZ4JMtqa29BL33nuv3nrrLX366afq1atXrfUhISFq166d9u3b16T+AgICVFlZ2WCbK6+8ssn1nTt3TgcPHmxyewAAWruQkBCFhITIZDI1eZumnNny9/dv8FKb4c4ElZaWSjp/+asuoaGh9jZNce7cuUbbOHoKEgAAb3bq1CmdOnXK6f029h1tuBDkbG3atNGZM2fk6+urDh061NmmOckWAAA0rqELWUeOHNG5c+fUpk2bBvswXAiqPgNU39mekydPql27dk3uzxMGdgEAgOYz3C3ysbGxkqSCgoJa6w4ePKiysjJ7GwAA4L0MF4IGDBggScrOzq61bv369TXaAAAA72W4u8POnj2rq666Svv379e//vUv+7OCSktLlZiYqMLCQn377beKiYlxa50AAMC1DBeCpPqnzbBYLFq4cCHTZgAAYACGDEGS9Mknn2jWrFnatm2bKisr1bNnT02ZMkUjR450d2kAAKAFGDYEAQAAYzPcwGgAAACJEAQAAAyKEGQA27dv1x133KHw8HCZzWb17dtXb775prvLMqSYmBiZTKY6fwYOHOju8rzWqlWrNGHCBCUkJCgwMFAmk0lZWVn1tj958qSmTJmi6OhoBQYGKiYmRk888YTKysparmgv15z3JCMjo97PjclkUmFhYYvW7o3279+v559/XkOHDlWXLl0UEBCgjh07asSIEfr444/r3MYbPieGe2K00dR3J9zIkSNVVFTEnXBuEBYWpsmTJ9dazmMZXCc9PV0Wi0URERGKjIyUxWKpt63VatWAAQO0c+dODR06VKNGjdKOHTu0cOFC5ebmasuWLY0+ih+Na857Uu3BBx+s83MSHh7u/AINZvHixVqwYIG6d++uoUOHqkOHDiooKNDbb7+tt99+W6tXr65x45DXfE5s8FqVlZW27t272wIDA207duywLz9x4oQtLi7OFhAQYCssLHRfgQYUHR1ti46OdncZhrNhwwb77/q8efNskmzLly+vs+3MmTNtkmzTpk2rsXzatGk2Sba5c+e6ulxDaM57MmvWLJsk2+bNm1uuQINZu3atLScnp9byLVu22Pz9/W3t2rWznTlzxr7cWz4nXA7zYps2bdKePXs0evRo+0MhpfNnItLS0lRRUaEVK1a4r0CghQwZMkTR0dGNtrPZbMrMzFRwcLBmzJhRY92MGTMUHByszMxMV5VpKE19T9AyfvnLX9Y5W8Ktt96qQYMG6fjx49q1a5ck7/qccDnMi+Xk5EiShg4dWmtdcnKyJCk3N7clS4KkH3/8UVlZWSouLlZoaKh69+6tPn36uLss6PycgsXFxUpOTpbZbK6xzmw2q1+/flq/fr2KiorUuXNnN1VpXFu2bNHHH38sHx8fxcbGasiQIQoODnZ3WV7P399fkuTndz4yeNPnhBDkxaonia1rQtiOHTsqODi4zolk4VoHDx7UmDFjaizr3bu3/va3v6l79+5uqgpSw5+Z6uXr169XQUGBx//j7o1mzZpV43V4eLheeOEFPfDAA26qyPvt27dPGzduVGRkpHr27CnJuz4nXA7zYqWlpZLOX/6qS2hoqL0NWsaYMWP04Ycf6tChQ7JardqxY4d+/etfa/v27Ro8eLBOnTrl7hINrSmfmQvboWXccMMNWrZsmb7//nudPn1ae/fu1eLFi2UymZSamqp33nnH3SV6pcrKSv3617/Wjz/+qAULFsjX11eSd31OOBMEtKCL/yd744036rXXXpMkrVy5Uq+++qqmTJnijtIAj/WLX/yixuuYmBg9/PDDuuaaa3T77bcrPT1dP//5z91UnXeqqqpSamqqtmzZonHjxunXv/61u0tyCc4EebHqlF5fGj958mS9SR4ta8KECZKk/Px8N1dibE35zFzYDu41ePBgde/eXbt27bK/N3BcVVWVfvOb32j16tX61a9+pZdffrnGem/6nBCCvFj19dq6xv0cPHhQZWVl9V7TRcuKiIiQdP7ZG3Cfhj4zFy7nc+M5qj875eXlbq7EO1RVVWnMmDFasWKFRo0apaysLPn41IwK3vQ5IQR5serbHbOzs2utW79+fY02cK/qJ7LywET3io2NVVRUlPLz82sFUqvVqvz8fHXt2tXjB3sahdVq1b///W+ZzWZ7GMKlqw5Ar732mkaOHKmVK1faxwFdyJs+J4QgLzZ48GB169ZNq1ev1s6dO+3LS0tLNXfuXAUEBHBXRQv65ptv6vzf6jfffKNp06ZJkkaPHt3SZeECJpNJY8eOVVlZmebMmVNj3Zw5c1RWVqZx48a5qTpjOnXqlHbv3l1r+enTpzVu3DidOnVK9913n/32bVya6ktgr732mu69916tWrWqzgAkedfnxGSz2WzuLgKuU9+0GRaLRQsXLmTajBaUkZGhP//5z+rfv7+io6NlNpu1e/duvffee6qsrNRTTz2luXPnurtMr5SZmam8vDxJ0q5du/T555+rX79+6tGjhyQpKSlJY8eOlXT+f7L9+vXTF198oaFDh+rmm2/W559/ruzsbPXu3Vu5ublq27at247FWzT1PSksLFS3bt3Uu3dvXXPNNerYsaMOHTqkjRs36ocfflDPnj21efNmtW/f3p2H0+plZGTo6aefVnBwsB577LE6Q+Xdd99tf/Cu13xO3PvAarSEjz/+2PbTn/7UFhoaamvbtq0tMTHR9sYbb7i7LMPJycmx3XfffbbY2FhbaGiozc/Pz9axY0fbXXfdZVu/fr27y/NqDz74oE1SvT8PPvhgjfYnTpywTZ482da5c2ebv7+/rUuXLrapU6faTp486Z4D8EJNfU9KS0ttv/vd72y9e/e2dejQwebn52cLCQmxJSYm2p555hlbeXm5ew/ESzT2fqiOaU284XPCmSAAAGBIjAkCAACGRAgCAACGRAgCAACGRAgCAACGRAgCAACGRAgCAACGRAgCAACGRAgCAACGRAgCAACGRAgC4JEKCwtlMpmUlZVVY/kHH3ygG2+8UW3atJHJZNKJEydavLacnByZTCbl5OS0+L4BOA8hCIBbZGVlyWQy6dNPP23yNkePHtV9992ntm3b6i9/+YtWrlwps9nslHpSU1NlMpka/UlNTXXK/gC4X+1pYgHAA0RHR+v06dPy9/e3L9u+fbtOnTqlOXPmaMiQIU7d34QJE2r0uXfvXs2cOVPjx4/Xrbfeal/evXt39enTR6dPn1ZAQIBTawDQsghBADySyWRSmzZtaiw7fPiwJCk8PNzp+7vlllt0yy232F9/+umnmjlzpm655Rb96le/qtX+4toAtD5cDgPgkS4eEzRw4EA9+OCDkqTevXvXujT18ccf66c//anCwsIUFBSkAQMGKD8/3yW11TUmaODAgbruuuv05ZdfasCAAQoKClKPHj301ltvSZJyc3PVp08ftW3bVldddZU2btxYq9/9+/frN7/5ja644goFBgYqPj5ey5Ytc8kxACAEAWgl/vCHP2j8+PGSpNmzZ2vlypWaMGGCJGnTpk3q37+/Tp48qVmzZmnu3Lk6ceKEbrvtNn3yySctVuPx48f1s5/9TH369NEzzzyjwMBApaSkaM2aNUpJSdEdd9yh+fPny2q16p577tGpU6fs2x46dEh9+/bVxo0b9fDDD+uFF15Qjx499Nvf/lbPP/98ix0DYCRcDgPQKtx+++3av3+/li5dqmHDhikhIUGSZLPZNHHiRA0aNEjvv/++TCaTpPNjfOLj45Wenq7s7OwWqbG4uFirV6/WqFGj7DVfffXVGj16tLZt26Y+ffpIkq655holJydr7dq19rNZf/jDH3Tu3Dnt2rVL7du3lyRNnDhRo0aNUkZGhiZMmKC2bdu2yHEARsGZIACt2s6dO1VQUKDRo0fr6NGjKikpUUlJiaxWqwYPHqwtW7aoqqqqRWoJDg5WSkqK/fVVV12l8PBwXXPNNfYAJMn+5++//17S+SC3du1aDR8+XDabzX4MJSUlSk5OVmlpqT7//PMWOQbASDgTBKBVKygokCT7eKG6lJaWql27di6vpVOnTvYzUdXCwsLUuXPnWsuk85fPJOnIkSM6ceKEli5dqqVLl9bZd/WgcADOQwgC0KpVn+V59tlndeONN9bZJjg4uEVq8fX1bdZym80m6f+O4Ve/+lW9Ye766693QoUALkQIAtCqde/eXZIUGhrq9GcHtZQOHTooJCRE586da7XHALRGjAkC0Kr16tVL3bt318KFC1VWVlZr/ZEjR9xQVfP4+vpqxIgRWrt2rb766qta61vDMQCtEWeCALjVsmXL9MEHH9RaftdddzVpex8fH2VmZmrYsGGKj4/XmDFjdOWVV2r//v3avHmzQkND9e677zq7bKebP3++Nm/erD59+mjcuHG69tprdezYMX3++efauHGjjh075u4SAa9DCALgVn/961/rXD5w4MAm9zFw4EB99NFHmjNnjl566SWVlZWpY8eO6tOnj/1ZQp7uiiuu0CeffKLZs2fr//2//6clS5aoffv2io+P14IFC9xdHuCVTLbqkXkAAAAGwpggAABgSFwOA+D1zp071+jg4uDg4Ba7lR6AZyAEAfB6RUVF6tq1a4NtZs2apYyMjJYpCIBHIAQB8HodO3bUhg0bGmzTrVu3FqoGgKdgYDQAADAkBkYDAABDIgQBAABDIgQBAABDIgQBAABDIgQBAABDIgQBAABDIgQBAABDIgQBAABD+v86y9bEjM9r5QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = df2345.copy()\n",
    "paras = ['Life_Time', 'Age', 'CountDeposit', 'CountWithdrawal', 'TotalDeposits', 'TotalWithdrawal', 'CountPaymentMethod', 'DifferentMethodWithdrawals', 'IP_Counts', 'e_11234', 'e_23456', 'e_34454', 'e_43568','e_64645']\n",
    "\n",
    "for (i, para) in enumerate(paras):\n",
    "   \n",
    "    xmin = min(df[para]); \n",
    "    xmax = max(df[para]);\n",
    "    \n",
    "    if para == 'CountPaymentMethod':\n",
    "        dbs = 0.5 # desired bin size\n",
    "    elif para == 'IP_Counts':\n",
    "        dbs = 1\n",
    "    elif para == 'e_64645':\n",
    "        dbs = 0.5\n",
    "    else:\n",
    "        dbs =  int((xmax-xmin)/10)\n",
    "    \n",
    "    data = df[para]\n",
    "    min_val = np.min(data); max_val = np.max(data)\n",
    "    min_boundary = -1.0 * (min_val % dbs - min_val)\n",
    "    max_boundary = max_val - max_val % dbs + dbs\n",
    "    n_bins = int((max_boundary - min_boundary) / dbs) + 1\n",
    "    bins = np.linspace(min_boundary, max_boundary, n_bins)\n",
    "    \n",
    "    plt.rcParams.update({'font.size': 14})\n",
    "    plt.figure(figsize=(6,4))\n",
    "    ax = plt.gca()\n",
    "    plt.setp(ax.spines.values(),linewidth=2)\n",
    "    ax.tick_params(direction='in', pad = 7,length=6, width=1.5, which='major',right=True,top=True)\n",
    "    ax.tick_params(direction='in', pad = 7,length=3, width=1.5, which='minor',right=True,top=True)\n",
    "\n",
    "    text = '%s' %(para)\n",
    "    plt.ylabel('Number', size=14); plt.xlabel(text, size=font)\n",
    "    sus = df.loc[df['Target_ml'] == 1]\n",
    "    non = df.loc[df['Target_ml'] == 0]; #print(len(sus),len(non))\n",
    "    \n",
    "    \n",
    "    mean = np.mean(non[para]); std = np.std(non[para])\n",
    "\n",
    "    ymin, ymax = plt.ylim(); #print(ymax)\n",
    "         \n",
    "    if xmax < 10:\n",
    "        text = \"\\u03BC = %1.2f, \\u03C3 = %1.2f\" %(mean,std); xoff = 3.9\n",
    "    elif xmax >10 and mean <= 100:\n",
    "        text = \"\\u03BC = %1.1f, \\u03C3 = %1.1f\" %(mean,std); xoff = 2.9\n",
    "    elif xmax >100 and mean <= 1000:\n",
    "        text = \"\\u03BC = %1.1f, \\u03C3 = %1.0f\" %(mean,std);xoff = 2.5  \n",
    "    elif xmax > 1000 and mean <= 10000:\n",
    "        text = \"\\u03BC = %1.0f, \\u03C3 = %1.0f\" %(mean,std); xoff = 3.5\n",
    "    else:\n",
    "        text = \"\\u03BC = %1.0f, \\u03C3 = %1.0f\" %(mean,std); xoff = 2.5\n",
    "\n",
    "    ax.hist(non[para], bins=bins-dbs/2, color=\"w\", edgecolor='grey', linewidth=3, label = text);\n",
    "  \n",
    "    mean = np.mean(sus[para]); std = np.std(sus[para])\n",
    "    if xmax < 10:\n",
    "        text = \"\\u03BC = %1.2f, \\u03C3 = %1.2f\" %(mean,std); xoff = 3.9\n",
    "    elif xmax >10 and mean < 100:\n",
    "        text = \"\\u03BC = %1.1f, \\u03C3 = %1.1f\" %(mean,std); xoff = 2.9\n",
    "    elif xmax >100 and mean < 1000:\n",
    "        text = \"\\u03BC = %1.1f, \\u03C3 = %1.0f\" %(mean,std);xoff = 2.5  \n",
    "    else:\n",
    "        text = \"\\u03BC = %1.0f, \\u03C3 = %1.0f\" %(mean,std);xoff = 2.2\n",
    "    \n",
    "    ax.hist(sus[para], bins=bins-dbs/2, color=\"r\", edgecolor='k', linewidth=3, label = text);\n",
    "    \n",
    "    ax.set_yscale('symlog');\n",
    "    def update_ticks(z, pos):\n",
    "        if z ==0:\n",
    "            return '0'\n",
    "        elif z >=1 and z <1000:\n",
    "            return '%d' %(z)\n",
    "        elif z < 1 and z > 0.001:\n",
    "            return z\n",
    "        else:\n",
    "            return  '10$^{%1.0f}$' %(np.log10(z))\n",
    "    \n",
    "    ax.yaxis.set_major_formatter(ticker.FuncFormatter(update_ticks))\n",
    "    x_maj = ax.get_xticks()# MAJOR TICK SPACING\n",
    "    x_min = (x_maj[1] -  x_maj[0])/5\n",
    "    ax.xaxis.set_minor_locator(ticker.MultipleLocator(x_min))\n",
    "    ymin, ymax = plt.ylim(); \n",
    "    ax.set_ylim([ymin,1.2*ymax])\n",
    "    ax.legend(fontsize = 0.8*font,loc=\"upper right\")\n",
    "    \n",
    "    plt.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8d6b0dc",
   "metadata": {},
   "source": [
    "# Machine learning\n",
    "\n",
    "**Randomise and balance data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "48864056",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sample sizes now 1752 1752\n"
     ]
    }
   ],
   "source": [
    "## RANDOMISE\n",
    "df = df.sample(frac=1)\n",
    "df['Target_ml'] = df['Target_ml'].astype(int)\n",
    "\n",
    "target = 'Target_ml'\n",
    "\n",
    "## BALANCE DATASET\n",
    "sus = df[df[target] == 1]; n1 = len(sus)\n",
    "not_sus = df[df[target] == 0]; n0 = len(not_sus)\n",
    "\n",
    "if n1 > n0:\n",
    "    class0 = df.loc[df[target] == 0]\n",
    "    class1 = df.loc[df[target] == 1][:n0]\n",
    "else:\n",
    "    class0 = df.loc[df[target] == 0][:n1]\n",
    "    class1 = df.loc[df[target] == 1]\n",
    "print(\"Sample sizes now\", len(class0),len(class1))\n",
    "df = pd.concat([class0, class1])\n",
    "\n",
    "df = df.reindex(np.random.permutation(df.index))\n",
    "df.reset_index(drop=True, inplace=True)\n",
    "del df['ID']\n",
    "#print(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "664ae690",
   "metadata": {},
   "source": [
    "**Split and standardise**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b93f291d",
   "metadata": {},
   "outputs": [],
   "source": [
    "## SPLIT INTO TRAINING AND TEST\n",
    "test_frac = 0.2\n",
    "max_iter = 1000\n",
    "n_neighbors = 26\n",
    "max_depth = 6\n",
    "cv = 10\n",
    "\n",
    "## DROP TARGET\n",
    "X = df.drop([target], axis = 1); y = df[target]\n",
    "## SPLIT DATA\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_frac, random_state = 42)\n",
    "## SCALE FEATURES - TRAIN AND TEST SEPERATELY\n",
    "sc = StandardScaler()\n",
    "X_train = sc.fit_transform(X_train)\n",
    "X_test = sc.fit_transform(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "274b5c7d",
   "metadata": {},
   "source": [
    "**Define classifiers and run these**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "db3fabc7",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Show calibration plots [y/n]?  n\n",
      "Show feature importance [y/n]?  y\n",
      "For a 0.2 test fraction (2803 train & 701 test) LR score = 75.956\n",
      "Validation accuracy of LR is 77.32 percent\n",
      "                       Feature  Importance\n",
      "8              TotalWithdrawal    0.060364\n",
      "15                     e_34454    0.030681\n",
      "16                     e_43568    0.023189\n",
      "11                Multi_Device    0.017838\n",
      "13                     e_11234    0.012986\n",
      "9           CountPaymentMethod    0.010203\n",
      "12                   IP_Counts    0.009133\n",
      "14                     e_23456    0.007920\n",
      "4                 Is_CRM_Email    0.005280\n",
      "3                    Is_Retail    0.004210\n",
      "1                    Life_Time    0.003924\n",
      "2                          Age    0.003710\n",
      "6              CountWithdrawal    0.003639\n",
      "10  DifferentMethodWithdrawals    0.003496\n",
      "7                TotalDeposits    0.002925\n",
      "0                           ID    0.002854\n",
      "5                 CountDeposit    0.000428\n",
      "17                     e_64645         NaN\n",
      "----------------------------------------\n",
      "For a 0.2 test fraction (2803 train & 701 test) KNN score = 78.454\n",
      "Validation accuracy of KNN is 80.03 percent\n",
      "                       Feature  Importance\n",
      "16                     e_43568    0.038530\n",
      "13                     e_11234    0.030681\n",
      "15                     e_34454    0.030681\n",
      "8              TotalWithdrawal    0.023832\n",
      "2                          Age    0.017909\n",
      "12                   IP_Counts    0.011987\n",
      "0                           ID    0.009633\n",
      "14                     e_23456    0.008420\n",
      "11                Multi_Device    0.005565\n",
      "1                    Life_Time    0.004995\n",
      "4                 Is_CRM_Email    0.004852\n",
      "10  DifferentMethodWithdrawals    0.003996\n",
      "9           CountPaymentMethod    0.003710\n",
      "5                 CountDeposit    0.002997\n",
      "6              CountWithdrawal    0.002283\n",
      "7                TotalDeposits    0.001142\n",
      "3                    Is_Retail    0.000714\n",
      "17                     e_64645         NaN\n",
      "----------------------------------------\n",
      "For a 0.2 test fraction (2803 train & 701 test) SVC score = 80.808\n",
      "Validation accuracy of SVC is 81.88 percent\n",
      "                       Feature  Importance\n",
      "13                     e_11234    0.062790\n",
      "16                     e_43568    0.053157\n",
      "15                     e_34454    0.041598\n",
      "8              TotalWithdrawal    0.013700\n",
      "12                   IP_Counts    0.013343\n",
      "4                 Is_CRM_Email    0.011630\n",
      "14                     e_23456    0.011416\n",
      "0                           ID    0.009633\n",
      "11                Multi_Device    0.008919\n",
      "9           CountPaymentMethod    0.008919\n",
      "7                TotalDeposits    0.007349\n",
      "2                          Age    0.007278\n",
      "6              CountWithdrawal    0.005994\n",
      "10  DifferentMethodWithdrawals    0.005922\n",
      "5                 CountDeposit    0.004781\n",
      "3                    Is_Retail    0.004138\n",
      "1                    Life_Time    0.003996\n",
      "17                     e_64645         NaN\n",
      "----------------------------------------\n",
      "For a 0.2 test fraction (2803 train & 701 test) DTR score = 80.202\n",
      "Validation accuracy of DTR is 77.18 percent\n",
      "                       Feature  Importance\n",
      "5                 CountDeposit    0.188227\n",
      "8              TotalWithdrawal    0.115590\n",
      "6              CountWithdrawal    0.088762\n",
      "13                     e_11234    0.057224\n",
      "15                     e_34454    0.039244\n",
      "16                     e_43568    0.034178\n",
      "12                   IP_Counts    0.023760\n",
      "14                     e_23456    0.022904\n",
      "0                           ID    0.014270\n",
      "7                TotalDeposits    0.008776\n",
      "1                    Life_Time    0.006208\n",
      "4                 Is_CRM_Email    0.005209\n",
      "3                    Is_Retail    0.001070\n",
      "9           CountPaymentMethod    0.000000\n",
      "10  DifferentMethodWithdrawals    0.000000\n",
      "11                Multi_Device    0.000000\n",
      "2                          Age    0.000000\n",
      "17                     e_64645         NaN\n",
      "----------------------------------------\n"
     ]
    }
   ],
   "source": [
    "classifiers = {\n",
    "    \"LR\": LogisticRegression(C=0.004832930238571752, solver='newton-cg'),\n",
    "    \"KNN\": KNeighborsClassifier(n_neighbors=n_neighbors),\n",
    "    \"SVC\": SVC(C=1, gamma=0.1,probability=True),\n",
    "    \"DTR\": DecisionTreeClassifier(max_depth = max_depth),\n",
    "}\n",
    "\n",
    "cal = str(input(\"Show calibration plots [y/n]?  \"))\n",
    "\n",
    "fea = str(input(\"Show feature importance [y/n]?  \"))\n",
    "\n",
    "for key, classifier in classifiers.items():\n",
    "    clf = classifier.fit(X_train, y_train)\n",
    "    training_score = cross_val_score(classifier, X_train, y_train, cv=cv) \n",
    "    print(\"For a %1.1f test fraction (%d train & %d test) %s score = %1.3f\" %(test_frac, len(X_train), len(X_test), key, training_score.mean()*100))\n",
    "\n",
    "    predictions = classifier.predict(X_test); #print('Testing\\n', confusion_matrix(predictions, y_test))\n",
    "    TN, FP, FN, TP = confusion_matrix(y_test, predictions).ravel()\n",
    "    print('Validation accuracy of %s is %1.2f percent' %(key, 100*(TP + TN)/(TP + FP + TN + FN)))\n",
    "\n",
    "    #### CALIBRATION PLOTS ######\n",
    "    if (cal =='y') | (cal == 'Y'):\n",
    "        from sklearn.calibration import CalibrationDisplay\n",
    "        nbins= 20\n",
    "        strat='quantile'\n",
    "        #strat = 'uniform'\n",
    "        font = 12\n",
    "\n",
    "        plt.rcParams.update({'font.size': font})\n",
    "        fig, ax1 = plt.subplots(figsize = (6, 4))\n",
    "        #ax2 = fig.add_axes([0.55, 0.2, 0.35, 0.3]) # INSET left, bottom, width, height\n",
    "        ax2 = fig.add_axes([0.15, 0.6, 0.35, 0.3])\n",
    "        ax2.yaxis.set_label_position(\"right\"); ax2.yaxis.tick_right()\n",
    "        plt.setp(ax1.spines.values(),linewidth=2)\n",
    "        plt.setp(ax2.spines.values(),linewidth=2)\n",
    "        ax1.tick_params(direction='in', pad = 5,length=6, width=1.5, which='major')\n",
    "        ax1.tick_params(direction='in', pad = 5,length=3, width=1.5, which='minor')\n",
    "        ax2.tick_params(axis='both', which='major', labelsize=0.8*font)\n",
    "    \n",
    "        disp = CalibrationDisplay.from_estimator(clf,X_test,y_test,n_bins=nbins,strategy=strat,\n",
    "                                                 pos_label=None, color='r', name=key, ref_line=True,\n",
    "                                                 ax=ax1,zorder = 2, label = r\"%s, $n = %d$\" %(key,len(X_test)))\n",
    "\n",
    "        ax2.hist(disp.y_prob,range=(0,1),bins=nbins,label=key, color=\"silver\", edgecolor='k',lw=2,zorder=1,alpha=0.7)\n",
    "        #ax2.set_xlabel(r'Mean predicted probability', size=0.8*font);\n",
    "        ax2.set_ylabel(r'Number',size=0.8*font)\n",
    "    \n",
    "        #print(disp.y_prob); print(disp.prob_pred); print(disp.prob_true)\n",
    "        diff2  = (disp.prob_pred - disp.prob_true)**2; \n",
    "        diff2_sum = diff2.sum(); print(diff2_sum)\n",
    "        ax1.plot([], [], ' ', label=r\"$\\chi^2/n_{\\rm bins} = %1.3f$\" %(diff2_sum/(nbins)))# Extra label on the legend\n",
    "        ax1.legend(fontsize = font,loc='lower right',labelcolor='k')\n",
    "\n",
    "        plt.tight_layout()\n",
    "        outfile = 'cal_display_%s-nbins=%d.eps' %(key,nbins)\n",
    "        #plt.savefig(outfile, format = 'eps'); print('Written to %s' %(outfile))\n",
    "        plt.show()\n",
    "    \n",
    "    if (fea =='y') | (fea == 'Y'):\n",
    "        #FEATURE IMPORTANCE #########\n",
    "        from sklearn.inspection import permutation_importance\n",
    "        results = permutation_importance(classifier, X_train, y_train, scoring='accuracy')\n",
    "        importance = results.importances_mean\n",
    "        features = df.drop(target,axis = 1) \n",
    "        features = features.columns.tolist()\n",
    "        df1 = pd.DataFrame(features, columns=['Feature']); \n",
    "        df2 = pd.DataFrame(importance, columns=['Importance'])\n",
    "        df1['Importance'] = df2.Importance  # adding to df1\n",
    "        print(df1.sort_values(by=['Importance'], ascending=False)) \n",
    "        print('------------------------------------------------------')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5ed28aec",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7263ba7c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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