Customer Churn Prediction.ipynb

{
 "cells": [
  {
   "cell_type": "code",
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   "id": "e5a6465e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing the dependencies\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import time\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.svm import LinearSVC\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.metrics import accuracy_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "58ff9d69",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RowNumber</th>\n",
       "      <th>CustomerId</th>\n",
       "      <th>Surname</th>\n",
       "      <th>CreditScore</th>\n",
       "      <th>Geography</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Tenure</th>\n",
       "      <th>Balance</th>\n",
       "      <th>NumOfProducts</th>\n",
       "      <th>HasCrCard</th>\n",
       "      <th>IsActiveMember</th>\n",
       "      <th>EstimatedSalary</th>\n",
       "      <th>Exited</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>15634602</td>\n",
       "      <td>Hargrave</td>\n",
       "      <td>619</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>42</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>101348.88</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>15647311</td>\n",
       "      <td>Hill</td>\n",
       "      <td>608</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Female</td>\n",
       "      <td>41</td>\n",
       "      <td>1</td>\n",
       "      <td>83807.86</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>112542.58</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>15619304</td>\n",
       "      <td>Onio</td>\n",
       "      <td>502</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>42</td>\n",
       "      <td>8</td>\n",
       "      <td>159660.80</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113931.57</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>15701354</td>\n",
       "      <td>Boni</td>\n",
       "      <td>699</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>93826.63</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>15737888</td>\n",
       "      <td>Mitchell</td>\n",
       "      <td>850</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Female</td>\n",
       "      <td>43</td>\n",
       "      <td>2</td>\n",
       "      <td>125510.82</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>79084.10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9995</th>\n",
       "      <td>9996</td>\n",
       "      <td>15606229</td>\n",
       "      <td>Obijiaku</td>\n",
       "      <td>771</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>39</td>\n",
       "      <td>5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>96270.64</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>9996</th>\n",
       "      <td>9997</td>\n",
       "      <td>15569892</td>\n",
       "      <td>Johnstone</td>\n",
       "      <td>516</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>35</td>\n",
       "      <td>10</td>\n",
       "      <td>57369.61</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>101699.77</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9997</th>\n",
       "      <td>9998</td>\n",
       "      <td>15584532</td>\n",
       "      <td>Liu</td>\n",
       "      <td>709</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>36</td>\n",
       "      <td>7</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>42085.58</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>9998</th>\n",
       "      <td>9999</td>\n",
       "      <td>15682355</td>\n",
       "      <td>Sabbatini</td>\n",
       "      <td>772</td>\n",
       "      <td>Germany</td>\n",
       "      <td>Male</td>\n",
       "      <td>42</td>\n",
       "      <td>3</td>\n",
       "      <td>75075.31</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>92888.52</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>9999</th>\n",
       "      <td>10000</td>\n",
       "      <td>15628319</td>\n",
       "      <td>Walker</td>\n",
       "      <td>792</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>28</td>\n",
       "      <td>4</td>\n",
       "      <td>130142.79</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>38190.78</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "<p>10000 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      RowNumber  CustomerId    Surname  CreditScore Geography  Gender  Age   \n",
       "0             1    15634602   Hargrave          619    France  Female   42  \\\n",
       "1             2    15647311       Hill          608     Spain  Female   41   \n",
       "2             3    15619304       Onio          502    France  Female   42   \n",
       "3             4    15701354       Boni          699    France  Female   39   \n",
       "4             5    15737888   Mitchell          850     Spain  Female   43   \n",
       "...         ...         ...        ...          ...       ...     ...  ...   \n",
       "9995       9996    15606229   Obijiaku          771    France    Male   39   \n",
       "9996       9997    15569892  Johnstone          516    France    Male   35   \n",
       "9997       9998    15584532        Liu          709    France  Female   36   \n",
       "9998       9999    15682355  Sabbatini          772   Germany    Male   42   \n",
       "9999      10000    15628319     Walker          792    France  Female   28   \n",
       "\n",
       "      Tenure    Balance  NumOfProducts  HasCrCard  IsActiveMember   \n",
       "0          2       0.00              1          1               1  \\\n",
       "1          1   83807.86              1          0               1   \n",
       "2          8  159660.80              3          1               0   \n",
       "3          1       0.00              2          0               0   \n",
       "4          2  125510.82              1          1               1   \n",
       "...      ...        ...            ...        ...             ...   \n",
       "9995       5       0.00              2          1               0   \n",
       "9996      10   57369.61              1          1               1   \n",
       "9997       7       0.00              1          0               1   \n",
       "9998       3   75075.31              2          1               0   \n",
       "9999       4  130142.79              1          1               0   \n",
       "\n",
       "      EstimatedSalary  Exited  \n",
       "0           101348.88       1  \n",
       "1           112542.58       0  \n",
       "2           113931.57       1  \n",
       "3            93826.63       0  \n",
       "4            79084.10       0  \n",
       "...               ...     ...  \n",
       "9995         96270.64       0  \n",
       "9996        101699.77       0  \n",
       "9997         42085.58       1  \n",
       "9998         92888.52       1  \n",
       "9999         38190.78       0  \n",
       "\n",
       "[10000 rows x 14 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Loading the Dataset\n",
    "\n",
    "data = pd.read_csv('Churn_Modelling.csv')\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "02711501",
   "metadata": {},
   "outputs": [
    {
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       "      <th>CreditScore</th>\n",
       "      <th>Geography</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Tenure</th>\n",
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       "      <th>0</th>\n",
       "      <td>619</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
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       "      <td>608</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Female</td>\n",
       "      <td>41</td>\n",
       "      <td>1</td>\n",
       "      <td>83807.86</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "      <th>2</th>\n",
       "      <td>502</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>42</td>\n",
       "      <td>8</td>\n",
       "      <td>159660.80</td>\n",
       "      <td>3</td>\n",
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       "      <td>113931.57</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>699</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>93826.63</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>850</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Female</td>\n",
       "      <td>43</td>\n",
       "      <td>2</td>\n",
       "      <td>125510.82</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>79084.10</td>\n",
       "      <td>0</td>\n",
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      "text/plain": [
       "   CreditScore Geography  Gender  Age  Tenure    Balance  NumOfProducts   \n",
       "0          619    France  Female   42       2       0.00              1  \\\n",
       "1          608     Spain  Female   41       1   83807.86              1   \n",
       "2          502    France  Female   42       8  159660.80              3   \n",
       "3          699    France  Female   39       1       0.00              2   \n",
       "4          850     Spain  Female   43       2  125510.82              1   \n",
       "\n",
       "   HasCrCard  IsActiveMember  EstimatedSalary  Exited  \n",
       "0          1               1        101348.88       1  \n",
       "1          0               1        112542.58       0  \n",
       "2          1               0        113931.57       1  \n",
       "3          0               0         93826.63       0  \n",
       "4          1               1         79084.10       0  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data Processing & Cleaning\n",
    "\n",
    "df = data.copy()\n",
    "df.drop(columns=['CustomerId','RowNumber','Surname'], inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b9dedb4d",
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   "outputs": [
    {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>CreditScore</th>\n",
       "      <th>Geography</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Tenure</th>\n",
       "      <th>Balance</th>\n",
       "      <th>NumOfProducts</th>\n",
       "      <th>HasCrCard</th>\n",
       "      <th>IsActiveMember</th>\n",
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       "      <th>Exited</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Null count</th>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cardinality</th>\n",
       "      <td>460</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>70</td>\n",
       "      <td>11</td>\n",
       "      <td>6382</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>9999</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Data Type</th>\n",
       "      <td>int64</td>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>int64</td>\n",
       "      <td>int64</td>\n",
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      ],
      "text/plain": [
       "            CreditScore Geography  Gender    Age Tenure  Balance   \n",
       "Null count            0         0       0      0      0        0  \\\n",
       "cardinality         460         3       2     70     11     6382   \n",
       "Data Type         int64    object  object  int64  int64  float64   \n",
       "\n",
       "            NumOfProducts HasCrCard IsActiveMember EstimatedSalary Exited  \n",
       "Null count              0         0              0               0      0  \n",
       "cardinality             4         2              2            9999      2  \n",
       "Data Type           int64     int64          int64         float64  int64  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Checking for null values\n",
    "\n",
    "overview = pd.concat((df.isnull().sum(),df.nunique(),df.dtypes), axis=1, keys=['Null count','cardinality','Data Type'])\n",
    "display(overview.T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "69b9fe80",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CreditScore</th>\n",
       "      <th>Geography</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Tenure</th>\n",
       "      <th>Balance</th>\n",
       "      <th>NumOfProducts</th>\n",
       "      <th>HasCrCard</th>\n",
       "      <th>IsActiveMember</th>\n",
       "      <th>EstimatedSalary</th>\n",
       "      <th>Exited</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>619</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>42</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>101348.88</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>608</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>41</td>\n",
       "      <td>1</td>\n",
       "      <td>83807.86</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>112542.58</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>502</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>42</td>\n",
       "      <td>8</td>\n",
       "      <td>159660.80</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113931.57</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>699</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>93826.63</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>850</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>43</td>\n",
       "      <td>2</td>\n",
       "      <td>125510.82</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>79084.10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9995</th>\n",
       "      <td>771</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>39</td>\n",
       "      <td>5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>96270.64</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9996</th>\n",
       "      <td>516</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>10</td>\n",
       "      <td>57369.61</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>101699.77</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9997</th>\n",
       "      <td>709</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>36</td>\n",
       "      <td>7</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>42085.58</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9998</th>\n",
       "      <td>772</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>42</td>\n",
       "      <td>3</td>\n",
       "      <td>75075.31</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>92888.52</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9999</th>\n",
       "      <td>792</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>4</td>\n",
       "      <td>130142.79</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>38190.78</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10000 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      CreditScore  Geography  Gender  Age  Tenure    Balance  NumOfProducts   \n",
       "0             619          0       0   42       2       0.00              1  \\\n",
       "1             608          2       0   41       1   83807.86              1   \n",
       "2             502          0       0   42       8  159660.80              3   \n",
       "3             699          0       0   39       1       0.00              2   \n",
       "4             850          2       0   43       2  125510.82              1   \n",
       "...           ...        ...     ...  ...     ...        ...            ...   \n",
       "9995          771          0       1   39       5       0.00              2   \n",
       "9996          516          0       1   35      10   57369.61              1   \n",
       "9997          709          0       0   36       7       0.00              1   \n",
       "9998          772          1       1   42       3   75075.31              2   \n",
       "9999          792          0       0   28       4  130142.79              1   \n",
       "\n",
       "      HasCrCard  IsActiveMember  EstimatedSalary  Exited  \n",
       "0             1               1        101348.88       1  \n",
       "1             0               1        112542.58       0  \n",
       "2             1               0        113931.57       1  \n",
       "3             0               0         93826.63       0  \n",
       "4             1               1         79084.10       0  \n",
       "...         ...             ...              ...     ...  \n",
       "9995          1               0         96270.64       0  \n",
       "9996          1               1        101699.77       0  \n",
       "9997          0               1         42085.58       1  \n",
       "9998          1               0         92888.52       1  \n",
       "9999          1               0         38190.78       0  \n",
       "\n",
       "[10000 rows x 11 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# LABEL ENCODING\n",
    "# Label encoding for some categorical features\n",
    "\n",
    "gender_labels = {'Female':0, 'Male':1}\n",
    "geography_labels = {'France':0, 'Germany':1, 'Spain':2}\n",
    "df.Gender = df.Gender.map(gender_labels)\n",
    "df.Geography = df.Geography.map(geography_labels)\n",
    "\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "bd9ce66b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Geography', 'Gender', 'NumOfProducts', 'HasCrCard', 'IsActiveMember']\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x1000 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Checking class imbalances for categorical factors\n",
    "\n",
    "cat = df.columns[df.nunique()<10].tolist()\n",
    "cat.pop()\n",
    "print(cat)\n",
    "plt.figure(figsize=(20,10))\n",
    "i=1\n",
    "for factor in cat:\n",
    "    plt.subplot(2,3,i)\n",
    "    sns.distplot(df[factor].loc[df['Exited']==0], hist=False)\n",
    "    sns.distplot(df[factor].loc[df['Exited']==1], hist=False)\n",
    "    i+=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d565a369",
   "metadata": {},
   "outputs": [],
   "source": [
    "# DATA VISUALIZATION\n",
    "\n",
    "color_1 = sns.color_palette(\"Accent\",10)\n",
    "color_2 = sns.color_palette(\"mako_r\",10)\n",
    "color_3 = sns.color_palette(\"Spectral_r\",10)\n",
    "color_4 = sns.color_palette()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "62463960",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Exited\n",
      "0    7963\n",
      "1    2037\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Finding the insight in the exited columns and visualization using the countplot for Seaborn and Pie Plot.\n",
    "\n",
    "plt.figure(figsize=(15,4))\n",
    "plt.subplot(1,2,1)\n",
    "sns.countplot(x=df[\"Exited\"],palette=color_1)\n",
    "\n",
    "plt.subplot(1,2,2)\n",
    "plt.pie(df[\"Exited\"].value_counts(),explode=[0.0,0.1],labels=[\"current customers\",\"exited customers\"],\n",
    "        colors=color_1,autopct=\"%.01f%%\")\n",
    "print(df[\"Exited\"].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "bbbe39da",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Exited  Geography\n",
      "0       0            4204\n",
      "        2            2064\n",
      "        1            1695\n",
      "1       1             814\n",
      "        0             810\n",
      "        2             413\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "label = [\"France_0\",\"Spain_0\",\"Germany_0\",\"Germany_1\",\"France_1\",\"Spain_1\"]\n",
    "eplode = [0.1,0.0,0.0,0.0,0.0,0.0]\n",
    "plt.figure(figsize=(12,10))\n",
    "plt.subplot(2,2,1)\n",
    "sns.countplot(data=df,x=\"Geography\",hue=\"Exited\",palette=color_4)\n",
    "plt.subplot(2,2,2)\n",
    "plt.pie(df.Geography.groupby(df.Exited).value_counts(),explode=eplode,shadow=True,colors=color_1,\n",
    "        labels=label,autopct=\"%0.1f%%\")\n",
    "\n",
    "\n",
    "print(df.Geography.groupby(df.Exited).value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9441accf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Exited  NumOfProducts\n",
      "0       2                4242\n",
      "        1                3675\n",
      "        3                  46\n",
      "1       1                1409\n",
      "        2                 348\n",
      "        3                 220\n",
      "        4                  60\n",
      "Name: count, dtype: int64\n",
      "------------------------------\n",
      "Exited  HasCrCard\n",
      "0       1            5631\n",
      "        0            2332\n",
      "1       1            1424\n",
      "        0             613\n",
      "Name: count, dtype: int64\n",
      "------------------------------\n",
      "Exited  IsActiveMember\n",
      "0       1                 4416\n",
      "        0                 3547\n",
      "1       0                 1302\n",
      "        1                  735\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x1000 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,10))\n",
    "plt.subplot(3,3,1)\n",
    "sns.countplot(data=df,x=\"NumOfProducts\",hue=\"Exited\",palette=color_1)\n",
    "plt.subplot(3,3,2)\n",
    "sns.countplot(data=df,x=\"HasCrCard\",hue=\"Exited\",palette=color_3)\n",
    "plt.subplot(3,3,3)\n",
    "sns.countplot(data=df,x=\"IsActiveMember\",hue=\"Exited\",palette=color_4)\n",
    "\n",
    "\n",
    "print(df.NumOfProducts.groupby(df.Exited).value_counts())\n",
    "print(\"--\"*15)\n",
    "print(df.HasCrCard.groupby(df.Exited).value_counts())\n",
    "print(\"--\"*15)\n",
    "print(df.IsActiveMember.groupby(df.Exited).value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "cb54b07f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Representation\n",
    "\n",
    "plt.figure(figsize=(5,5))\n",
    "sns.heatmap(df.corr(), cbar=False, annot=True, fmt='.2f')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c7536947",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Train Test Split\n",
    "\n",
    "x_train, x_test, y_train, y_test = train_test_split(df.drop(columns=['Exited']).values, df.Exited.values, \n",
    "                                                    test_size=0.2, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0f9b2711",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Finding Best Classifier: GridSearchCV\n",
    "\n",
    "def result_grid(x_train, y_train, x_test, y_test):\n",
    "    model_param_grid={\n",
    "        'Logistic Regression':(LogisticRegression(max_iter=10000),{'C': [0.01, 0.1, 1, 10.0],\n",
    "                                                                   'solver': ['liblinear','lbfgs','newton-cg']}),\n",
    "        'KNN':(KNeighborsClassifier(),{'n_neighbors': [3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35]}),\n",
    "#         'Naive Bayes':(MultinomialNB(),{'alpha': [0.1, 1.0, 10.0], 'fit_prior': [True,False]}),\n",
    "#         'SVM':(LinearSVC(max_iter=10000),{'C': [0.01, 0.1, 1.0, 10.0]}),\n",
    "        'Decision Tree':(DecisionTreeClassifier(max_depth=10),{'criterion': ['gini','entropy'], 'splitter':['best','random'],\n",
    "                                                  'max_depth':[10,50,100,150,200,250,300,350,400]}),\n",
    "        'Random Forest':(RandomForestClassifier(),{'n_estimators':[50,100,150,200]})\n",
    "    }\n",
    "    \n",
    "    results=[]\n",
    "    \n",
    "    for name, (model,parameters) in model_param_grid.items():\n",
    "        grid=GridSearchCV(model,parameters)\n",
    "        \n",
    "        print(f\"Tuning for {name}\")\n",
    "        \n",
    "        st=time.time()\n",
    "        \n",
    "        grid.fit(x_train,y_train) # fitting in GridSearchCV\n",
    "        y_pred=grid.predict(x_test) # predicts using best hyperparameters\n",
    "        acc=accuracy_score(y_test,y_pred) # best accuracy obtained\n",
    "        \n",
    "        en=time.time()\n",
    "        \n",
    "        net_time=en-st\n",
    "        \n",
    "        # printing best parameters:\n",
    "        print(f\"Best hyperparameters for {name}: {grid.best_params_}\")\n",
    "        print(f\"Best obtined score for {name}: {grid.best_score_*100:.3f}%\")\n",
    "        print(f\"Running time for {name}:{net_time:.3f}s\")\n",
    "        \n",
    "        results.append([name,grid.best_params_,grid.best_score_*100,net_time])\n",
    "        print('-'*100)\n",
    "        print()\n",
    "    \n",
    "    result_df=pd.DataFrame(results, columns=['model_name','best_parameters','best_test_score','running_time'])\n",
    "    result_df=result_df.style.highlight_max(subset=['best_test_score'], color = 'lightgreen')\n",
    "    result_df=result_df.highlight_min(subset=['best_test_score'], color = 'pink')\n",
    "    result_df=result_df.highlight_max(subset=['running_time'], color = 'pink')\n",
    "    result_df=result_df.highlight_min(subset=['running_time'], color = 'lightgreen')\n",
    "    return result_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a90c9599",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tuning for Logistic Regression\n",
      "Best hyperparameters for Logistic Regression: {'C': 10.0, 'solver': 'newton-cg'}\n",
      "Best obtined score for Logistic Regression: 80.638%\n",
      "Running time for Logistic Regression:28.303s\n",
      "----------------------------------------------------------------------------------------------------\n",
      "\n",
      "Tuning for KNN\n",
      "Best hyperparameters for KNN: {'n_neighbors': 31}\n",
      "Best obtined score for KNN: 79.450%\n",
      "Running time for KNN:5.969s\n",
      "----------------------------------------------------------------------------------------------------\n",
      "\n",
      "Tuning for Decision Tree\n",
      "Best hyperparameters for Decision Tree: {'criterion': 'gini', 'max_depth': 10, 'splitter': 'random'}\n",
      "Best obtined score for Decision Tree: 83.925%\n",
      "Running time for Decision Tree:4.053s\n",
      "----------------------------------------------------------------------------------------------------\n",
      "\n",
      "Tuning for Random Forest\n",
      "Best hyperparameters for Random Forest: {'n_estimators': 200}\n",
      "Best obtined score for Random Forest: 86.062%\n",
      "Running time for Random Forest:27.795s\n",
      "----------------------------------------------------------------------------------------------------\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_6db0f_row0_col3, #T_6db0f_row1_col2 {\n",
       "  background-color: pink;\n",
       "}\n",
       "#T_6db0f_row2_col3, #T_6db0f_row3_col2 {\n",
       "  background-color: lightgreen;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_6db0f\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_6db0f_level0_col0\" class=\"col_heading level0 col0\" >model_name</th>\n",
       "      <th id=\"T_6db0f_level0_col1\" class=\"col_heading level0 col1\" >best_parameters</th>\n",
       "      <th id=\"T_6db0f_level0_col2\" class=\"col_heading level0 col2\" >best_test_score</th>\n",
       "      <th id=\"T_6db0f_level0_col3\" class=\"col_heading level0 col3\" >running_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_6db0f_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "      <td id=\"T_6db0f_row0_col0\" class=\"data row0 col0\" >Logistic Regression</td>\n",
       "      <td id=\"T_6db0f_row0_col1\" class=\"data row0 col1\" >{'C': 10.0, 'solver': 'newton-cg'}</td>\n",
       "      <td id=\"T_6db0f_row0_col2\" class=\"data row0 col2\" >80.637500</td>\n",
       "      <td id=\"T_6db0f_row0_col3\" class=\"data row0 col3\" >28.302526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6db0f_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_6db0f_row1_col0\" class=\"data row1 col0\" >KNN</td>\n",
       "      <td id=\"T_6db0f_row1_col1\" class=\"data row1 col1\" >{'n_neighbors': 31}</td>\n",
       "      <td id=\"T_6db0f_row1_col2\" class=\"data row1 col2\" >79.450000</td>\n",
       "      <td id=\"T_6db0f_row1_col3\" class=\"data row1 col3\" >5.969469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6db0f_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "      <td id=\"T_6db0f_row2_col0\" class=\"data row2 col0\" >Decision Tree</td>\n",
       "      <td id=\"T_6db0f_row2_col1\" class=\"data row2 col1\" >{'criterion': 'gini', 'max_depth': 10, 'splitter': 'random'}</td>\n",
       "      <td id=\"T_6db0f_row2_col2\" class=\"data row2 col2\" >83.925000</td>\n",
       "      <td id=\"T_6db0f_row2_col3\" class=\"data row2 col3\" >4.053130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6db0f_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "      <td id=\"T_6db0f_row3_col0\" class=\"data row3 col0\" >Random Forest</td>\n",
       "      <td id=\"T_6db0f_row3_col1\" class=\"data row3 col1\" >{'n_estimators': 200}</td>\n",
       "      <td id=\"T_6db0f_row3_col2\" class=\"data row3 col2\" >86.062500</td>\n",
       "      <td id=\"T_6db0f_row3_col3\" class=\"data row3 col3\" >27.794824</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1b6ab2d20e0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res = result_grid(x_train, y_train, x_test, y_test)\n",
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "aeb58511",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\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>CreditScore</th>\n",
       "      <th>Geography</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Tenure</th>\n",
       "      <th>Balance</th>\n",
       "      <th>NumOfProducts</th>\n",
       "      <th>HasCrCard</th>\n",
       "      <th>IsActiveMember</th>\n",
       "      <th>EstimatedSalary</th>\n",
       "      <th>Exited</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>619</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>42</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>101348.88</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>608</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>41</td>\n",
       "      <td>1</td>\n",
       "      <td>83807.86</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>112542.58</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>502</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>42</td>\n",
       "      <td>8</td>\n",
       "      <td>159660.80</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113931.57</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>699</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>93826.63</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>850</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>43</td>\n",
       "      <td>2</td>\n",
       "      <td>125510.82</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>79084.10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   CreditScore  Geography  Gender  Age  Tenure    Balance  NumOfProducts   \n",
       "0          619          0       0   42       2       0.00              1  \\\n",
       "1          608          2       0   41       1   83807.86              1   \n",
       "2          502          0       0   42       8  159660.80              3   \n",
       "3          699          0       0   39       1       0.00              2   \n",
       "4          850          2       0   43       2  125510.82              1   \n",
       "\n",
       "   HasCrCard  IsActiveMember  EstimatedSalary  Exited  \n",
       "0          1               1        101348.88       1  \n",
       "1          0               1        112542.58       0  \n",
       "2          1               0        113931.57       1  \n",
       "3          0               0         93826.63       0  \n",
       "4          1               1         79084.10       0  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Label Encoding\n",
    "\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "model=LabelEncoder()\n",
    "for i in data.columns:\n",
    "    if data[i].dtype==\"object\":\n",
    "        data[i]=model.fit_transform(data[i])\n",
    "        \n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "6568d178",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data Spilting and Training Model\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "x=data.drop(\"Exited\",axis=1)\n",
    "y=data['Exited']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4bb7806f",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train,x_test,y_train,y_test=train_test_split(x,y,random_state=1,test_size=0.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "651ee503",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "model=StandardScaler()\n",
    "\n",
    "x_train=pd.DataFrame(model.fit_transform(x_train),columns=x_train.columns)\n",
    "x_test=pd.DataFrame(model.fit_transform(x_test),columns=x_test.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "d9b049c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7000, 13)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b0ac492d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7000,)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "0563ba78",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8456666666666667"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# RANDOM FOREST\n",
    "\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "classifier_rf = RandomForestClassifier(random_state=42, n_jobs=-1, max_depth=5,\n",
    "                                       n_estimators=100, oob_score=True)\n",
    "\n",
    "classifier_rf.fit(x_train, y_train)\n",
    "\n",
    "\n",
    "classifier_rf.score(x_test,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "63c9edf4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "feature_importances = pd.Series(classifier_rf.feature_importances_, index=x_train.columns).sort_values(ascending=False)\n",
    "plt.figure(figsize=(10,5))\n",
    "# Plot a simple bar chart\n",
    "feature_importances.plot.bar();\n",
    "plt.grid()\n",
    "plt.title(\"Features have the maximum effect on result\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "827c8bf5",
   "metadata": {},
   "outputs": [],
   "source": [
    "imp_feature_data=data[['Age','NumOfProducts','IsActiveMember']]\n",
    "x1_train,x1_test,y1_train,y1_test=train_test_split(imp_feature_data,data['Exited'],random_state=1,test_size=0.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "ccc20241",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.855"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "classifier_rf = RandomForestClassifier(random_state=42, n_jobs=-1, max_depth=5,\n",
    "                                       n_estimators=100, oob_score=True)\n",
    "\n",
    "classifier_rf.fit(x1_train, y1_train)\n",
    "\n",
    "\n",
    "classifier_rf.score(x1_test,y1_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "c00b1fdc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8563333333333333"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.model_selection import GridSearchCV, RandomizedSearchCV\n",
    "params = {'n_estimators':np.arange(2,10),\n",
    "         'criterion': ['gini','entropy'],\n",
    "         'max_depth':np.arange(2,5),\n",
    "         'min_samples_leaf':np.arange(1,5),\n",
    "         'min_samples_split':np.arange(1,5),\n",
    "         'max_features':['auto'],\n",
    "         'random_state':[10]}\n",
    "\n",
    "rf_model=RandomForestClassifier()\n",
    "\n",
    "rf_hyper_model1=GridSearchCV(rf_model,param_grid=params)\n",
    "\n",
    "rf_hyper_model1.fit(x1_train,y1_train)\n",
    "\n",
    "rf_hyper_model1.score(x1_test,y1_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "691e865b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8373333333333334"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "params = {'n_estimators':np.arange(2,10),\n",
    "         'criterion': ['gini','entropy'],\n",
    "         'max_depth':np.arange(2,5),\n",
    "         'min_samples_leaf':np.arange(1,5),\n",
    "         'min_samples_split':np.arange(1,5),\n",
    "         'max_features':['auto'],\n",
    "         'random_state':[10]}\n",
    "\n",
    "rf_model=RandomForestClassifier()\n",
    "\n",
    "rf_hyper_model=GridSearchCV(rf_model,param_grid=params)\n",
    "\n",
    "rf_hyper_model.fit(x_train,y_train)\n",
    "\n",
    "y_pred = rf_hyper_model.predict(x_test)\n",
    "\n",
    "rf_hyper_model.score(x_test,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "8f5e8dea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GridSearchCV(estimator=RandomForestClassifier(),\n",
       "             param_grid={&#x27;criterion&#x27;: [&#x27;gini&#x27;, &#x27;entropy&#x27;],\n",
       "                         &#x27;max_depth&#x27;: array([2, 3, 4]),\n",
       "                         &#x27;max_features&#x27;: [&#x27;auto&#x27;],\n",
       "                         &#x27;min_samples_leaf&#x27;: array([1, 2, 3, 4]),\n",
       "                         &#x27;min_samples_split&#x27;: array([1, 2, 3, 4]),\n",
       "                         &#x27;n_estimators&#x27;: array([2, 3, 4, 5, 6, 7, 8, 9]),\n",
       "                         &#x27;random_state&#x27;: [10]})</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">GridSearchCV</label><div class=\"sk-toggleable__content\"><pre>GridSearchCV(estimator=RandomForestClassifier(),\n",
       "             param_grid={&#x27;criterion&#x27;: [&#x27;gini&#x27;, &#x27;entropy&#x27;],\n",
       "                         &#x27;max_depth&#x27;: array([2, 3, 4]),\n",
       "                         &#x27;max_features&#x27;: [&#x27;auto&#x27;],\n",
       "                         &#x27;min_samples_leaf&#x27;: array([1, 2, 3, 4]),\n",
       "                         &#x27;min_samples_split&#x27;: array([1, 2, 3, 4]),\n",
       "                         &#x27;n_estimators&#x27;: array([2, 3, 4, 5, 6, 7, 8, 9]),\n",
       "                         &#x27;random_state&#x27;: [10]})</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">estimator: RandomForestClassifier</label><div class=\"sk-toggleable__content\"><pre>RandomForestClassifier()</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">RandomForestClassifier</label><div class=\"sk-toggleable__content\"><pre>RandomForestClassifier()</pre></div></div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "GridSearchCV(estimator=RandomForestClassifier(),\n",
       "             param_grid={'criterion': ['gini', 'entropy'],\n",
       "                         'max_depth': array([2, 3, 4]),\n",
       "                         'max_features': ['auto'],\n",
       "                         'min_samples_leaf': array([1, 2, 3, 4]),\n",
       "                         'min_samples_split': array([1, 2, 3, 4]),\n",
       "                         'n_estimators': array([2, 3, 4, 5, 6, 7, 8, 9]),\n",
       "                         'random_state': [10]})"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rf_hyper_model.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "7ae5bf34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8373333333333334"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred = rf_hyper_model.predict(x_test)\n",
    "rf_hyper_model.score(x_test,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "9ce4bdf6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# DECISION TREE CLASSIFIER\n",
    "\n",
    "from sklearn.tree import DecisionTreeClassifier \n",
    "\n",
    "# Create Decision Tree classifer object\n",
    "clf = DecisionTreeClassifier()\n",
    "\n",
    "# Train Decision Tree Classifer\n",
    "clf = clf.fit(x_train,y_train)\n",
    "\n",
    "#Predict the response for test dataset\n",
    "y_pred = clf.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "acb7225b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.795\n"
     ]
    }
   ],
   "source": [
    "# Model Accuracy\n",
    "\n",
    "print(\"Accuracy:\",metrics.accuracy_score(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "6a01ef48",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8093333333333333"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# K NEIGHBOURS CLASSIFIER\n",
    "\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "neigh = KNeighborsClassifier(n_neighbors=3)\n",
    "neigh.fit(x_train,y_train)\n",
    "\n",
    "neigh.score(x_test,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "a0bd6f02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8093333333333333"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred = neigh.predict(x_test)\n",
    "neigh.score(x_test,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "c0a36ea4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.795"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# GRADIENT BOOSTING CLASSIFIER\n",
    "\n",
    "from sklearn.ensemble import GradientBoostingClassifier\n",
    "lf = GradientBoostingClassifier(n_estimators=100, learning_rate=1.0,\n",
    "                                max_depth=1, random_state=0).fit(x_train, y_train)\n",
    "clf.score(x_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "fbd34f51",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8093333333333333"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred = neigh.predict(x_test)\n",
    "neigh.score(x_test,y_test)"
   ]
  }
 ],
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