Classification_2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "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>Merchant_id</th>\n",
       "      <th>Transaction date</th>\n",
       "      <th>Average Amount/transaction/day</th>\n",
       "      <th>Transaction_amount</th>\n",
       "      <th>Is declined</th>\n",
       "      <th>Total Number of declines/day</th>\n",
       "      <th>isForeignTransaction</th>\n",
       "      <th>isHighRiskCountry</th>\n",
       "      <th>Daily_chargeback_avg_amt</th>\n",
       "      <th>6_month_avg_chbk_amt</th>\n",
       "      <th>6-month_chbk_freq</th>\n",
       "      <th>isFradulent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3160040998</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.0</td>\n",
       "      <td>3000.0</td>\n",
       "      <td>N</td>\n",
       "      <td>5</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3160040998</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.0</td>\n",
       "      <td>4300.0</td>\n",
       "      <td>N</td>\n",
       "      <td>5</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3160041896</td>\n",
       "      <td>NaN</td>\n",
       "      <td>185.5</td>\n",
       "      <td>4823.0</td>\n",
       "      <td>Y</td>\n",
       "      <td>5</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3160141996</td>\n",
       "      <td>NaN</td>\n",
       "      <td>185.5</td>\n",
       "      <td>5008.5</td>\n",
       "      <td>Y</td>\n",
       "      <td>8</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3160241992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>500.0</td>\n",
       "      <td>26000.0</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>800</td>\n",
       "      <td>677.2</td>\n",
       "      <td>6</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Merchant_id  Transaction date  Average Amount/transaction/day  \\\n",
       "0   3160040998               NaN                           100.0   \n",
       "1   3160040998               NaN                           100.0   \n",
       "2   3160041896               NaN                           185.5   \n",
       "3   3160141996               NaN                           185.5   \n",
       "4   3160241992               NaN                           500.0   \n",
       "\n",
       "   Transaction_amount Is declined  Total Number of declines/day  \\\n",
       "0              3000.0           N                             5   \n",
       "1              4300.0           N                             5   \n",
       "2              4823.0           Y                             5   \n",
       "3              5008.5           Y                             8   \n",
       "4             26000.0           N                             0   \n",
       "\n",
       "  isForeignTransaction isHighRiskCountry  Daily_chargeback_avg_amt  \\\n",
       "0                    Y                 Y                         0   \n",
       "1                    Y                 Y                         0   \n",
       "2                    N                 N                         0   \n",
       "3                    N                 N                         0   \n",
       "4                    Y                 Y                       800   \n",
       "\n",
       "   6_month_avg_chbk_amt  6-month_chbk_freq isFradulent  \n",
       "0                   0.0                  0           Y  \n",
       "1                   0.0                  0           Y  \n",
       "2                   0.0                  0           Y  \n",
       "3                   0.0                  0           Y  \n",
       "4                 677.2                  6           Y  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "df = pd.read_csv(\"./creditcardcsvpresent.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Merchant_id                       3075\n",
       "Transaction date                     0\n",
       "Average Amount/transaction/day    3075\n",
       "Transaction_amount                3075\n",
       "Is declined                       3075\n",
       "Total Number of declines/day      3075\n",
       "isForeignTransaction              3075\n",
       "isHighRiskCountry                 3075\n",
       "Daily_chargeback_avg_amt          3075\n",
       "6_month_avg_chbk_amt              3075\n",
       "6-month_chbk_freq                 3075\n",
       "isFradulent                       3075\n",
       "dtype: int64"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3075, 11)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop(\"Transaction date\", axis =1, inplace = True)\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 3075 entries, 0 to 3074\n",
      "Data columns (total 11 columns):\n",
      " #   Column                          Non-Null Count  Dtype  \n",
      "---  ------                          --------------  -----  \n",
      " 0   Merchant_id                     3075 non-null   int64  \n",
      " 1   Average Amount/transaction/day  3075 non-null   float64\n",
      " 2   Transaction_amount              3075 non-null   float64\n",
      " 3   Is declined                     3075 non-null   object \n",
      " 4   Total Number of declines/day    3075 non-null   int64  \n",
      " 5   isForeignTransaction            3075 non-null   object \n",
      " 6   isHighRiskCountry               3075 non-null   object \n",
      " 7   Daily_chargeback_avg_amt        3075 non-null   int64  \n",
      " 8   6_month_avg_chbk_amt            3075 non-null   float64\n",
      " 9   6-month_chbk_freq               3075 non-null   int64  \n",
      " 10  isFradulent                     3075 non-null   object \n",
      "dtypes: float64(3), int64(4), object(4)\n",
      "memory usage: 264.4+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0     2384\n",
      "1      134\n",
      "6       96\n",
      "2       92\n",
      "5       87\n",
      "3       82\n",
      "4       69\n",
      "9       46\n",
      "8       45\n",
      "7       37\n",
      "20       3\n",
      "Name: Total Number of declines/day, dtype: int64\n",
      "0    2857\n",
      "7      77\n",
      "4      21\n",
      "3      20\n",
      "6      18\n",
      "9      17\n",
      "5      17\n",
      "1      16\n",
      "8      16\n",
      "2      16\n",
      "Name: 6-month_chbk_freq, dtype: int64\n",
      "6661273532    13\n",
      "6661273533    12\n",
      "6661273531    12\n",
      "6661273529     8\n",
      "6661273530     7\n",
      "              ..\n",
      "3514946201     1\n",
      "6239313639     1\n",
      "6524453525     1\n",
      "3479876243     1\n",
      "4838852609     1\n",
      "Name: Merchant_id, Length: 3015, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(df['Total Number of declines/day'].value_counts())\n",
    "print(df['6-month_chbk_freq'].value_counts())\n",
    "print(df['Merchant_id'].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.isnull().sum().plot(kind='barh', color='darkblue', figsize=(6,4))\n",
    "plt.title(\"Missing value counts\")\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from operator import eq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1008 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1008 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1008 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1008 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1008 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14, 14))\n",
    "plt.subplot(5, 1, 1)\n",
    "plt.title('Average Amount/transaction/day', fontsize=15)\n",
    "sns.distplot(df[eq(df['isFradulent'],str('Y'))]['Average Amount/transaction/day'], hist=True, rug=True, label=\"Y\")\n",
    "sns.distplot(df[eq(df['isFradulent'],str('N'))]['Average Amount/transaction/day'], hist=True, rug=True, label=\"N\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "# plt.rc('font', size=15)\n",
    "plt.figure(figsize=(14, 14))\n",
    "plt.subplot(5, 1, 2)\n",
    "plt.title('Transaction_amount', fontsize=15)\n",
    "sns.distplot(df[eq(df['isFradulent'],str('Y'))].Transaction_amount, hist=True, rug=True, label=\"Y\")\n",
    "sns.distplot(df[eq(df['isFradulent'],str('N'))].Transaction_amount, hist=True, rug=True, label=\"N\")\n",
    "plt.legend()\n",
    "\n",
    "plt.figure(figsize=(14, 14))\n",
    "plt.subplot(5, 1, 3)\n",
    "plt.title('6_month_avg_chbk_amt', fontsize=15)\n",
    "sns.kdeplot(df[df.isFradulent == 'Y'][\"6_month_avg_chbk_amt\"],bw=1.5)\n",
    "sns.kdeplot(df[df.isFradulent == 'N'][\"6_month_avg_chbk_amt\"],bw=1.5)\n",
    "plt.legend(['Y','N'])\n",
    "\n",
    "plt.figure(figsize=(14, 14))\n",
    "plt.subplot(5, 1, 4)\n",
    "plt.title('Daily_chargeback_avg_amt', fontsize=15)\n",
    "sns.kdeplot(df[df.isFradulent == 'Y'][\"Daily_chargeback_avg_amt\"],bw=1.5)\n",
    "sns.kdeplot(df[df.isFradulent == 'N'][\"Daily_chargeback_avg_amt\"],bw=1.5)\n",
    "plt.legend(['Y','N'])\n",
    "\n",
    "\n",
    "plt.figure(figsize=(14, 14))\n",
    "plt.subplot(5, 1, 5)\n",
    "plt.title(' Merchant_id', fontsize=15)\n",
    "sns.kdeplot(df[df.isFradulent == 'Y'][\"Merchant_id\"],bw=1.5)\n",
    "sns.kdeplot(df[df.isFradulent == 'N'][\"Merchant_id\"],bw=1.5)\n",
    "plt.legend(['Y','N'])\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1008x1008 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1008 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1008 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1008 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14, 14))\n",
    "\n",
    "plt.figure(figsize=(14, 14))\n",
    "plt.subplot(5, 1, 3)\n",
    "plt.title('Total Number of declines/day', fontsize=15)\n",
    "sns.kdeplot(df[df.isFradulent == 'Y'][\"Total Number of declines/day\"],bw=1.5)\n",
    "sns.kdeplot(df[df.isFradulent == 'N'][\"Total Number of declines/day\"],bw=1.5)\n",
    "plt.legend(['Y','N'])\n",
    "\n",
    "plt.figure(figsize=(14, 14))\n",
    "plt.subplot(5, 1, 4)\n",
    "plt.title(' 6-month_chbk_freq', fontsize=15)\n",
    "sns.kdeplot(df[df.isFradulent == 'Y'][\"6-month_chbk_freq\"],bw=1.5)\n",
    "sns.kdeplot(df[df.isFradulent == 'N'][\"6-month_chbk_freq\"],bw=1.5)\n",
    "plt.legend(['Y','N'])\n",
    "\n",
    "\n",
    "plt.figure(figsize=(14, 14))\n",
    "plt.subplot(5, 1, 5)\n",
    "plt.title(' 6-month_chbk_freq', fontsize=15)\n",
    "sns.kdeplot(df[df.isFradulent == 'Y'][\"6-month_chbk_freq\"],bw=1.5)\n",
    "sns.kdeplot(df[df.isFradulent == 'N'][\"6-month_chbk_freq\"],bw=1.5)\n",
    "plt.legend(['Y','N'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x21f39632c88>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1008 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rc('font', size=13)\n",
    "plt.figure(figsize=(14, 14))\n",
    "\n",
    "plt.rc('font', size=13)\n",
    "plt.subplot(4, 2, 1);\n",
    "sns.countplot('Is declined', hue='isFradulent', data=df)\n",
    "plt.subplots_adjust(top = 1.2)\n",
    "\n",
    "plt.subplot(4, 2, 2);\n",
    "sns.countplot('isForeignTransaction', hue='isFradulent', data=df)\n",
    "\n",
    "plt.subplot(4, 2, 3);\n",
    "sns.countplot('isHighRiskCountry', hue='isFradulent', data=df)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(3075, 10) (3075,)\n"
     ]
    }
   ],
   "source": [
    "X = df.drop(\"isFradulent\", axis =1, inplace = False)\n",
    "y = df[\"isFradulent\"]\n",
    "\n",
    "print(X.shape, y.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "X['Is declined'].replace('Y',1,inplace=True)\n",
    "X['Is declined'].replace('N',0,inplace=True)\n",
    "                         \n",
    "X['isForeignTransaction'].replace('Y',1,inplace=True)\n",
    "X['isForeignTransaction'].replace('N',0,inplace=True)\n",
    "\n",
    "X['isHighRiskCountry'].replace('Y',1,inplace=True)\n",
    "X['isHighRiskCountry'].replace('N',0,inplace=True)\n",
    "\n",
    "y.replace('Y',1, inplace=True)\n",
    "y.replace('N',0, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gradient Boosting Classifier\n",
      "Accuracy of Training set: 0.979\n",
      "Accuracy of Test set: 0.977\n"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import GradientBoostingClassifier\n",
    "\n",
    "gbrt = GradientBoostingClassifier(random_state=42, max_depth=1,learning_rate = 0.1)\n",
    "gbrt.fit(X_train, y_train)\n",
    "\n",
    "\n",
    "print('Gradient Boosting Classifier')\n",
    "print(\"Accuracy of Training set: {:.3f}\".format(gbrt.score(X_train, y_train)))\n",
    "print(\"Accuracy of Test set: {:.3f}\".format(gbrt.score(X_test, y_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decision Tree Classifier\n",
      "Accuracy of Training set: 1.000\n",
      "Accuaracy of Test set: 0.975\n"
     ]
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n",
    "classifier = DecisionTreeClassifier(criterion = 'entropy', random_state = 0)\n",
    "classifier.fit(X_train, y_train)\n",
    "\n",
    "print('Decision Tree Classifier')\n",
    "print('Accuracy of Training set: {:.3f}'.format(classifier.score(X_train,y_train)))\n",
    "print('Accuaracy of Test set: {:.3f}'.format(classifier.score(X_test, y_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Naive Bayes Classifier\n",
      "Accuracy of Training set: 0.852\n",
      "Accuaracy of Test set: 0.865\n"
     ]
    }
   ],
   "source": [
    "from sklearn.naive_bayes import GaussianNB\n",
    "NBC = GaussianNB()\n",
    "NBC.fit(X_train, y_train)\n",
    "\n",
    "print('Naive Bayes Classifier')\n",
    "print('Accuracy of Training set: {:.3f}'.format(NBC.score(X_train,y_train)))\n",
    "print('Accuaracy of Test set: {:.3f}'.format(NBC.score(X_test, y_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RandomForest Classifier\n",
      "Accuracy of Training set: 1.000\n",
      "Accuracy of Test set: 0.984\n"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "forest = RandomForestClassifier(n_estimators=1000, random_state=0)\n",
    "forest.fit(X_train, y_train)\n",
    "print('RandomForest Classifier')\n",
    "print(\"Accuracy of Training set: {:.3f}\".format(forest.score(X_train, y_train)))\n",
    "print(\"Accuracy of Test set: {:.3f}\".format(forest.score(X_test, y_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RandomForest Classifier Cross Validation\n",
      "Accuracy: 0.98 (+/- 0.03)\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "scores = cross_val_score(forest, X, y, cv=15)\n",
    "print('RandomForest Classifier Cross Validation')\n",
    "print(\"Accuracy: %0.2f (+/- %0.2f)\" % (scores.mean(), scores.std() * 2))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train accuracy :  1.0\n",
      "test accuracy :  0.9843953185955787\n",
      "\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           N       0.99      0.99      0.99       664\n",
      "           Y       0.96      0.92      0.94       105\n",
      "\n",
      "    accuracy                           0.98       769\n",
      "   macro avg       0.97      0.96      0.97       769\n",
      "weighted avg       0.98      0.98      0.98       769\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "y_train_hat = forest.predict(X_train)\n",
    "print('train accuracy : ',accuracy_score(y_train, y_train_hat))\n",
    "y_test_hat = forest.predict(X_test)\n",
    "print('test accuracy : ',accuracy_score(y_test, y_test_hat))\n",
    "\n",
    "from sklearn.metrics import classification_report\n",
    "print('\\n')\n",
    "class_names = ['N','Y']\n",
    "print(classification_report(y_test, y_test_hat, target_names=class_names))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import roc_curve, auc\n",
    "\n",
    "fpr, tpr, thresholds = roc_curve(y, forest.predict_proba(X)[:,1])\n",
    "\n",
    "plt.plot(fpr, tpr, 'o-', label=\"Random Forest Classifier\")\n",
    "plt.plot([0, 1], [0, 1], 'k--', label=\"Random Guess\")\n",
    "plt.legend()\n",
    "plt.xlabel('Fall-Out')\n",
    "plt.ylabel('Recall')\n",
    "plt.title('ROC Curve')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}