credit-card-fraud-detection.ipynb

{
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   "source": [
    "import datetime\n",
    "import numpy as np \n",
    "import pandas as pd \n",
    "import matplotlib.pyplot as plt \n",
    "import seaborn as sns \n",
    "from sklearn.model_selection import train_test_split \n",
    "from sklearn.svm import SVC\n",
    "from sklearn.metrics import accuracy_score \n",
    "from sklearn.preprocessing import LabelEncoder"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "275f8a38",
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    "tags": []
   },
   "source": [
    "# **1-Read a data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b9db8e7e",
   "metadata": {
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     "status": "completed"
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    "tags": []
   },
   "outputs": [],
   "source": [
    "train_data = pd.read_csv(\"/kaggle/input/fraud-detection/fraudTrain.csv\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "874a414b",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1296675 entries, 0 to 1296674\n",
      "Data columns (total 23 columns):\n",
      " #   Column                 Non-Null Count    Dtype  \n",
      "---  ------                 --------------    -----  \n",
      " 0   Unnamed: 0             1296675 non-null  int64  \n",
      " 1   trans_date_trans_time  1296675 non-null  object \n",
      " 2   cc_num                 1296675 non-null  int64  \n",
      " 3   merchant               1296675 non-null  object \n",
      " 4   category               1296675 non-null  object \n",
      " 5   amt                    1296675 non-null  float64\n",
      " 6   first                  1296675 non-null  object \n",
      " 7   last                   1296675 non-null  object \n",
      " 8   gender                 1296675 non-null  object \n",
      " 9   street                 1296675 non-null  object \n",
      " 10  city                   1296675 non-null  object \n",
      " 11  state                  1296675 non-null  object \n",
      " 12  zip                    1296675 non-null  int64  \n",
      " 13  lat                    1296675 non-null  float64\n",
      " 14  long                   1296675 non-null  float64\n",
      " 15  city_pop               1296675 non-null  int64  \n",
      " 16  job                    1296675 non-null  object \n",
      " 17  dob                    1296675 non-null  object \n",
      " 18  trans_num              1296675 non-null  object \n",
      " 19  unix_time              1296675 non-null  int64  \n",
      " 20  merch_lat              1296675 non-null  float64\n",
      " 21  merch_long             1296675 non-null  float64\n",
      " 22  is_fraud               1296675 non-null  int64  \n",
      "dtypes: float64(5), int64(6), object(12)\n",
      "memory usage: 227.5+ MB\n"
     ]
    }
   ],
   "source": [
    "train_data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2aac433f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-08T22:13:48.468742Z",
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     "status": "completed"
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   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>cc_num</th>\n",
       "      <th>amt</th>\n",
       "      <th>zip</th>\n",
       "      <th>lat</th>\n",
       "      <th>long</th>\n",
       "      <th>city_pop</th>\n",
       "      <th>unix_time</th>\n",
       "      <th>merch_lat</th>\n",
       "      <th>merch_long</th>\n",
       "      <th>is_fraud</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1.296675e+06</td>\n",
       "      <td>1.296675e+06</td>\n",
       "      <td>1.296675e+06</td>\n",
       "      <td>1.296675e+06</td>\n",
       "      <td>1.296675e+06</td>\n",
       "      <td>1.296675e+06</td>\n",
       "      <td>1.296675e+06</td>\n",
       "      <td>1.296675e+06</td>\n",
       "      <td>1.296675e+06</td>\n",
       "      <td>1.296675e+06</td>\n",
       "      <td>1.296675e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>6.483370e+05</td>\n",
       "      <td>4.171920e+17</td>\n",
       "      <td>7.035104e+01</td>\n",
       "      <td>4.880067e+04</td>\n",
       "      <td>3.853762e+01</td>\n",
       "      <td>-9.022634e+01</td>\n",
       "      <td>8.882444e+04</td>\n",
       "      <td>1.349244e+09</td>\n",
       "      <td>3.853734e+01</td>\n",
       "      <td>-9.022646e+01</td>\n",
       "      <td>5.788652e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.743180e+05</td>\n",
       "      <td>1.308806e+18</td>\n",
       "      <td>1.603160e+02</td>\n",
       "      <td>2.689322e+04</td>\n",
       "      <td>5.075808e+00</td>\n",
       "      <td>1.375908e+01</td>\n",
       "      <td>3.019564e+05</td>\n",
       "      <td>1.284128e+07</td>\n",
       "      <td>5.109788e+00</td>\n",
       "      <td>1.377109e+01</td>\n",
       "      <td>7.586269e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>6.041621e+10</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.257000e+03</td>\n",
       "      <td>2.002710e+01</td>\n",
       "      <td>-1.656723e+02</td>\n",
       "      <td>2.300000e+01</td>\n",
       "      <td>1.325376e+09</td>\n",
       "      <td>1.902779e+01</td>\n",
       "      <td>-1.666712e+02</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3.241685e+05</td>\n",
       "      <td>1.800429e+14</td>\n",
       "      <td>9.650000e+00</td>\n",
       "      <td>2.623700e+04</td>\n",
       "      <td>3.462050e+01</td>\n",
       "      <td>-9.679800e+01</td>\n",
       "      <td>7.430000e+02</td>\n",
       "      <td>1.338751e+09</td>\n",
       "      <td>3.473357e+01</td>\n",
       "      <td>-9.689728e+01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>6.483370e+05</td>\n",
       "      <td>3.521417e+15</td>\n",
       "      <td>4.752000e+01</td>\n",
       "      <td>4.817400e+04</td>\n",
       "      <td>3.935430e+01</td>\n",
       "      <td>-8.747690e+01</td>\n",
       "      <td>2.456000e+03</td>\n",
       "      <td>1.349250e+09</td>\n",
       "      <td>3.936568e+01</td>\n",
       "      <td>-8.743839e+01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>9.725055e+05</td>\n",
       "      <td>4.642255e+15</td>\n",
       "      <td>8.314000e+01</td>\n",
       "      <td>7.204200e+04</td>\n",
       "      <td>4.194040e+01</td>\n",
       "      <td>-8.015800e+01</td>\n",
       "      <td>2.032800e+04</td>\n",
       "      <td>1.359385e+09</td>\n",
       "      <td>4.195716e+01</td>\n",
       "      <td>-8.023680e+01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.296674e+06</td>\n",
       "      <td>4.992346e+18</td>\n",
       "      <td>2.894890e+04</td>\n",
       "      <td>9.978300e+04</td>\n",
       "      <td>6.669330e+01</td>\n",
       "      <td>-6.795030e+01</td>\n",
       "      <td>2.906700e+06</td>\n",
       "      <td>1.371817e+09</td>\n",
       "      <td>6.751027e+01</td>\n",
       "      <td>-6.695090e+01</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "         Unnamed: 0        cc_num           amt           zip           lat  \\\n",
       "count  1.296675e+06  1.296675e+06  1.296675e+06  1.296675e+06  1.296675e+06   \n",
       "mean   6.483370e+05  4.171920e+17  7.035104e+01  4.880067e+04  3.853762e+01   \n",
       "std    3.743180e+05  1.308806e+18  1.603160e+02  2.689322e+04  5.075808e+00   \n",
       "min    0.000000e+00  6.041621e+10  1.000000e+00  1.257000e+03  2.002710e+01   \n",
       "25%    3.241685e+05  1.800429e+14  9.650000e+00  2.623700e+04  3.462050e+01   \n",
       "50%    6.483370e+05  3.521417e+15  4.752000e+01  4.817400e+04  3.935430e+01   \n",
       "75%    9.725055e+05  4.642255e+15  8.314000e+01  7.204200e+04  4.194040e+01   \n",
       "max    1.296674e+06  4.992346e+18  2.894890e+04  9.978300e+04  6.669330e+01   \n",
       "\n",
       "               long      city_pop     unix_time     merch_lat    merch_long  \\\n",
       "count  1.296675e+06  1.296675e+06  1.296675e+06  1.296675e+06  1.296675e+06   \n",
       "mean  -9.022634e+01  8.882444e+04  1.349244e+09  3.853734e+01 -9.022646e+01   \n",
       "std    1.375908e+01  3.019564e+05  1.284128e+07  5.109788e+00  1.377109e+01   \n",
       "min   -1.656723e+02  2.300000e+01  1.325376e+09  1.902779e+01 -1.666712e+02   \n",
       "25%   -9.679800e+01  7.430000e+02  1.338751e+09  3.473357e+01 -9.689728e+01   \n",
       "50%   -8.747690e+01  2.456000e+03  1.349250e+09  3.936568e+01 -8.743839e+01   \n",
       "75%   -8.015800e+01  2.032800e+04  1.359385e+09  4.195716e+01 -8.023680e+01   \n",
       "max   -6.795030e+01  2.906700e+06  1.371817e+09  6.751027e+01 -6.695090e+01   \n",
       "\n",
       "           is_fraud  \n",
       "count  1.296675e+06  \n",
       "mean   5.788652e-03  \n",
       "std    7.586269e-02  \n",
       "min    0.000000e+00  \n",
       "25%    0.000000e+00  \n",
       "50%    0.000000e+00  \n",
       "75%    0.000000e+00  \n",
       "max    1.000000e+00  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.describe()"
   ]
  },
  {
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   "id": "672d9a2f",
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    "tags": []
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "Unnamed: 0                 int64\n",
       "trans_date_trans_time     object\n",
       "cc_num                     int64\n",
       "merchant                  object\n",
       "category                  object\n",
       "amt                      float64\n",
       "first                     object\n",
       "last                      object\n",
       "gender                    object\n",
       "street                    object\n",
       "city                      object\n",
       "state                     object\n",
       "zip                        int64\n",
       "lat                      float64\n",
       "long                     float64\n",
       "city_pop                   int64\n",
       "job                       object\n",
       "dob                       object\n",
       "trans_num                 object\n",
       "unix_time                  int64\n",
       "merch_lat                float64\n",
       "merch_long               float64\n",
       "is_fraud                   int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.dtypes"
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  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "53b0b450",
   "metadata": {
    "execution": {
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'trans_date_trans_time', 'cc_num', 'merchant', 'category',\n",
       "       'amt', 'first', 'last', 'gender', 'street', 'city', 'state', 'zip',\n",
       "       'lat', 'long', 'city_pop', 'job', 'dob', 'trans_num', 'unix_time',\n",
       "       'merch_lat', 'merch_long', 'is_fraud'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ffc44bd",
   "metadata": {
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     "duration": 0.010209,
     "end_time": "2024-01-08T22:13:49.221639",
     "exception": false,
     "start_time": "2024-01-08T22:13:49.211430",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# **2-Preprocessing**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2d8cc158",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-08T22:13:49.244994Z",
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     "status": "completed"
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   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>trans_date_trans_time</th>\n",
       "      <th>cc_num</th>\n",
       "      <th>merchant</th>\n",
       "      <th>category</th>\n",
       "      <th>amt</th>\n",
       "      <th>first</th>\n",
       "      <th>last</th>\n",
       "      <th>gender</th>\n",
       "      <th>street</th>\n",
       "      <th>...</th>\n",
       "      <th>lat</th>\n",
       "      <th>long</th>\n",
       "      <th>city_pop</th>\n",
       "      <th>job</th>\n",
       "      <th>dob</th>\n",
       "      <th>trans_num</th>\n",
       "      <th>unix_time</th>\n",
       "      <th>merch_lat</th>\n",
       "      <th>merch_long</th>\n",
       "      <th>is_fraud</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2019-01-01 00:00:18</td>\n",
       "      <td>2703186189652095</td>\n",
       "      <td>fraud_Rippin, Kub and Mann</td>\n",
       "      <td>misc_net</td>\n",
       "      <td>4.97</td>\n",
       "      <td>Jennifer</td>\n",
       "      <td>Banks</td>\n",
       "      <td>F</td>\n",
       "      <td>561 Perry Cove</td>\n",
       "      <td>...</td>\n",
       "      <td>36.0788</td>\n",
       "      <td>-81.1781</td>\n",
       "      <td>3495</td>\n",
       "      <td>Psychologist, counselling</td>\n",
       "      <td>1988-03-09</td>\n",
       "      <td>0b242abb623afc578575680df30655b9</td>\n",
       "      <td>1325376018</td>\n",
       "      <td>36.011293</td>\n",
       "      <td>-82.048315</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2019-01-01 00:00:44</td>\n",
       "      <td>630423337322</td>\n",
       "      <td>fraud_Heller, Gutmann and Zieme</td>\n",
       "      <td>grocery_pos</td>\n",
       "      <td>107.23</td>\n",
       "      <td>Stephanie</td>\n",
       "      <td>Gill</td>\n",
       "      <td>F</td>\n",
       "      <td>43039 Riley Greens Suite 393</td>\n",
       "      <td>...</td>\n",
       "      <td>48.8878</td>\n",
       "      <td>-118.2105</td>\n",
       "      <td>149</td>\n",
       "      <td>Special educational needs teacher</td>\n",
       "      <td>1978-06-21</td>\n",
       "      <td>1f76529f8574734946361c461b024d99</td>\n",
       "      <td>1325376044</td>\n",
       "      <td>49.159047</td>\n",
       "      <td>-118.186462</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2019-01-01 00:00:51</td>\n",
       "      <td>38859492057661</td>\n",
       "      <td>fraud_Lind-Buckridge</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>220.11</td>\n",
       "      <td>Edward</td>\n",
       "      <td>Sanchez</td>\n",
       "      <td>M</td>\n",
       "      <td>594 White Dale Suite 530</td>\n",
       "      <td>...</td>\n",
       "      <td>42.1808</td>\n",
       "      <td>-112.2620</td>\n",
       "      <td>4154</td>\n",
       "      <td>Nature conservation officer</td>\n",
       "      <td>1962-01-19</td>\n",
       "      <td>a1a22d70485983eac12b5b88dad1cf95</td>\n",
       "      <td>1325376051</td>\n",
       "      <td>43.150704</td>\n",
       "      <td>-112.154481</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2019-01-01 00:01:16</td>\n",
       "      <td>3534093764340240</td>\n",
       "      <td>fraud_Kutch, Hermiston and Farrell</td>\n",
       "      <td>gas_transport</td>\n",
       "      <td>45.00</td>\n",
       "      <td>Jeremy</td>\n",
       "      <td>White</td>\n",
       "      <td>M</td>\n",
       "      <td>9443 Cynthia Court Apt. 038</td>\n",
       "      <td>...</td>\n",
       "      <td>46.2306</td>\n",
       "      <td>-112.1138</td>\n",
       "      <td>1939</td>\n",
       "      <td>Patent attorney</td>\n",
       "      <td>1967-01-12</td>\n",
       "      <td>6b849c168bdad6f867558c3793159a81</td>\n",
       "      <td>1325376076</td>\n",
       "      <td>47.034331</td>\n",
       "      <td>-112.561071</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>2019-01-01 00:03:06</td>\n",
       "      <td>375534208663984</td>\n",
       "      <td>fraud_Keeling-Crist</td>\n",
       "      <td>misc_pos</td>\n",
       "      <td>41.96</td>\n",
       "      <td>Tyler</td>\n",
       "      <td>Garcia</td>\n",
       "      <td>M</td>\n",
       "      <td>408 Bradley Rest</td>\n",
       "      <td>...</td>\n",
       "      <td>38.4207</td>\n",
       "      <td>-79.4629</td>\n",
       "      <td>99</td>\n",
       "      <td>Dance movement psychotherapist</td>\n",
       "      <td>1986-03-28</td>\n",
       "      <td>a41d7549acf90789359a9aa5346dcb46</td>\n",
       "      <td>1325376186</td>\n",
       "      <td>38.674999</td>\n",
       "      <td>-78.632459</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",
       "      <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>1296670</th>\n",
       "      <td>1296670</td>\n",
       "      <td>2020-06-21 12:12:08</td>\n",
       "      <td>30263540414123</td>\n",
       "      <td>fraud_Reichel Inc</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>15.56</td>\n",
       "      <td>Erik</td>\n",
       "      <td>Patterson</td>\n",
       "      <td>M</td>\n",
       "      <td>162 Jessica Row Apt. 072</td>\n",
       "      <td>...</td>\n",
       "      <td>37.7175</td>\n",
       "      <td>-112.4777</td>\n",
       "      <td>258</td>\n",
       "      <td>Geoscientist</td>\n",
       "      <td>1961-11-24</td>\n",
       "      <td>440b587732da4dc1a6395aba5fb41669</td>\n",
       "      <td>1371816728</td>\n",
       "      <td>36.841266</td>\n",
       "      <td>-111.690765</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296671</th>\n",
       "      <td>1296671</td>\n",
       "      <td>2020-06-21 12:12:19</td>\n",
       "      <td>6011149206456997</td>\n",
       "      <td>fraud_Abernathy and Sons</td>\n",
       "      <td>food_dining</td>\n",
       "      <td>51.70</td>\n",
       "      <td>Jeffrey</td>\n",
       "      <td>White</td>\n",
       "      <td>M</td>\n",
       "      <td>8617 Holmes Terrace Suite 651</td>\n",
       "      <td>...</td>\n",
       "      <td>39.2667</td>\n",
       "      <td>-77.5101</td>\n",
       "      <td>100</td>\n",
       "      <td>Production assistant, television</td>\n",
       "      <td>1979-12-11</td>\n",
       "      <td>278000d2e0d2277d1de2f890067dcc0a</td>\n",
       "      <td>1371816739</td>\n",
       "      <td>38.906881</td>\n",
       "      <td>-78.246528</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296672</th>\n",
       "      <td>1296672</td>\n",
       "      <td>2020-06-21 12:12:32</td>\n",
       "      <td>3514865930894695</td>\n",
       "      <td>fraud_Stiedemann Ltd</td>\n",
       "      <td>food_dining</td>\n",
       "      <td>105.93</td>\n",
       "      <td>Christopher</td>\n",
       "      <td>Castaneda</td>\n",
       "      <td>M</td>\n",
       "      <td>1632 Cohen Drive Suite 639</td>\n",
       "      <td>...</td>\n",
       "      <td>32.9396</td>\n",
       "      <td>-105.8189</td>\n",
       "      <td>899</td>\n",
       "      <td>Naval architect</td>\n",
       "      <td>1967-08-30</td>\n",
       "      <td>483f52fe67fabef353d552c1e662974c</td>\n",
       "      <td>1371816752</td>\n",
       "      <td>33.619513</td>\n",
       "      <td>-105.130529</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296673</th>\n",
       "      <td>1296673</td>\n",
       "      <td>2020-06-21 12:13:36</td>\n",
       "      <td>2720012583106919</td>\n",
       "      <td>fraud_Reinger, Weissnat and Strosin</td>\n",
       "      <td>food_dining</td>\n",
       "      <td>74.90</td>\n",
       "      <td>Joseph</td>\n",
       "      <td>Murray</td>\n",
       "      <td>M</td>\n",
       "      <td>42933 Ryan Underpass</td>\n",
       "      <td>...</td>\n",
       "      <td>43.3526</td>\n",
       "      <td>-102.5411</td>\n",
       "      <td>1126</td>\n",
       "      <td>Volunteer coordinator</td>\n",
       "      <td>1980-08-18</td>\n",
       "      <td>d667cdcbadaaed3da3f4020e83591c83</td>\n",
       "      <td>1371816816</td>\n",
       "      <td>42.788940</td>\n",
       "      <td>-103.241160</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296674</th>\n",
       "      <td>1296674</td>\n",
       "      <td>2020-06-21 12:13:37</td>\n",
       "      <td>4292902571056973207</td>\n",
       "      <td>fraud_Langosh, Wintheiser and Hyatt</td>\n",
       "      <td>food_dining</td>\n",
       "      <td>4.30</td>\n",
       "      <td>Jeffrey</td>\n",
       "      <td>Smith</td>\n",
       "      <td>M</td>\n",
       "      <td>135 Joseph Mountains</td>\n",
       "      <td>...</td>\n",
       "      <td>45.8433</td>\n",
       "      <td>-113.8748</td>\n",
       "      <td>218</td>\n",
       "      <td>Therapist, horticultural</td>\n",
       "      <td>1995-08-16</td>\n",
       "      <td>8f7c8e4ab7f25875d753b422917c98c9</td>\n",
       "      <td>1371816817</td>\n",
       "      <td>46.565983</td>\n",
       "      <td>-114.186110</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1296675 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Unnamed: 0 trans_date_trans_time               cc_num  \\\n",
       "0                 0   2019-01-01 00:00:18     2703186189652095   \n",
       "1                 1   2019-01-01 00:00:44         630423337322   \n",
       "2                 2   2019-01-01 00:00:51       38859492057661   \n",
       "3                 3   2019-01-01 00:01:16     3534093764340240   \n",
       "4                 4   2019-01-01 00:03:06      375534208663984   \n",
       "...             ...                   ...                  ...   \n",
       "1296670     1296670   2020-06-21 12:12:08       30263540414123   \n",
       "1296671     1296671   2020-06-21 12:12:19     6011149206456997   \n",
       "1296672     1296672   2020-06-21 12:12:32     3514865930894695   \n",
       "1296673     1296673   2020-06-21 12:13:36     2720012583106919   \n",
       "1296674     1296674   2020-06-21 12:13:37  4292902571056973207   \n",
       "\n",
       "                                    merchant       category     amt  \\\n",
       "0                 fraud_Rippin, Kub and Mann       misc_net    4.97   \n",
       "1            fraud_Heller, Gutmann and Zieme    grocery_pos  107.23   \n",
       "2                       fraud_Lind-Buckridge  entertainment  220.11   \n",
       "3         fraud_Kutch, Hermiston and Farrell  gas_transport   45.00   \n",
       "4                        fraud_Keeling-Crist       misc_pos   41.96   \n",
       "...                                      ...            ...     ...   \n",
       "1296670                    fraud_Reichel Inc  entertainment   15.56   \n",
       "1296671             fraud_Abernathy and Sons    food_dining   51.70   \n",
       "1296672                 fraud_Stiedemann Ltd    food_dining  105.93   \n",
       "1296673  fraud_Reinger, Weissnat and Strosin    food_dining   74.90   \n",
       "1296674  fraud_Langosh, Wintheiser and Hyatt    food_dining    4.30   \n",
       "\n",
       "               first       last gender                         street  ...  \\\n",
       "0           Jennifer      Banks      F                 561 Perry Cove  ...   \n",
       "1          Stephanie       Gill      F   43039 Riley Greens Suite 393  ...   \n",
       "2             Edward    Sanchez      M       594 White Dale Suite 530  ...   \n",
       "3             Jeremy      White      M    9443 Cynthia Court Apt. 038  ...   \n",
       "4              Tyler     Garcia      M               408 Bradley Rest  ...   \n",
       "...              ...        ...    ...                            ...  ...   \n",
       "1296670         Erik  Patterson      M       162 Jessica Row Apt. 072  ...   \n",
       "1296671      Jeffrey      White      M  8617 Holmes Terrace Suite 651  ...   \n",
       "1296672  Christopher  Castaneda      M     1632 Cohen Drive Suite 639  ...   \n",
       "1296673       Joseph     Murray      M           42933 Ryan Underpass  ...   \n",
       "1296674      Jeffrey      Smith      M           135 Joseph Mountains  ...   \n",
       "\n",
       "             lat      long  city_pop                                job  \\\n",
       "0        36.0788  -81.1781      3495          Psychologist, counselling   \n",
       "1        48.8878 -118.2105       149  Special educational needs teacher   \n",
       "2        42.1808 -112.2620      4154        Nature conservation officer   \n",
       "3        46.2306 -112.1138      1939                    Patent attorney   \n",
       "4        38.4207  -79.4629        99     Dance movement psychotherapist   \n",
       "...          ...       ...       ...                                ...   \n",
       "1296670  37.7175 -112.4777       258                       Geoscientist   \n",
       "1296671  39.2667  -77.5101       100   Production assistant, television   \n",
       "1296672  32.9396 -105.8189       899                    Naval architect   \n",
       "1296673  43.3526 -102.5411      1126              Volunteer coordinator   \n",
       "1296674  45.8433 -113.8748       218           Therapist, horticultural   \n",
       "\n",
       "               dob                         trans_num   unix_time  merch_lat  \\\n",
       "0       1988-03-09  0b242abb623afc578575680df30655b9  1325376018  36.011293   \n",
       "1       1978-06-21  1f76529f8574734946361c461b024d99  1325376044  49.159047   \n",
       "2       1962-01-19  a1a22d70485983eac12b5b88dad1cf95  1325376051  43.150704   \n",
       "3       1967-01-12  6b849c168bdad6f867558c3793159a81  1325376076  47.034331   \n",
       "4       1986-03-28  a41d7549acf90789359a9aa5346dcb46  1325376186  38.674999   \n",
       "...            ...                               ...         ...        ...   \n",
       "1296670 1961-11-24  440b587732da4dc1a6395aba5fb41669  1371816728  36.841266   \n",
       "1296671 1979-12-11  278000d2e0d2277d1de2f890067dcc0a  1371816739  38.906881   \n",
       "1296672 1967-08-30  483f52fe67fabef353d552c1e662974c  1371816752  33.619513   \n",
       "1296673 1980-08-18  d667cdcbadaaed3da3f4020e83591c83  1371816816  42.788940   \n",
       "1296674 1995-08-16  8f7c8e4ab7f25875d753b422917c98c9  1371816817  46.565983   \n",
       "\n",
       "         merch_long  is_fraud  \n",
       "0        -82.048315         0  \n",
       "1       -118.186462         0  \n",
       "2       -112.154481         0  \n",
       "3       -112.561071         0  \n",
       "4        -78.632459         0  \n",
       "...             ...       ...  \n",
       "1296670 -111.690765         0  \n",
       "1296671  -78.246528         0  \n",
       "1296672 -105.130529         0  \n",
       "1296673 -103.241160         0  \n",
       "1296674 -114.186110         0  \n",
       "\n",
       "[1296675 rows x 23 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data[\"trans_date_trans_time\"] = pd.to_datetime(train_data[\"trans_date_trans_time\"])\n",
    "train_data[\"dob\"] = pd.to_datetime(train_data[\"dob\"])\n",
    "train_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e676b574",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-08T22:13:51.239455Z",
     "iopub.status.busy": "2024-01-08T22:13:51.238637Z",
     "iopub.status.idle": "2024-01-08T22:13:51.486971Z",
     "shell.execute_reply": "2024-01-08T22:13:51.485713Z"
    },
    "papermill": {
     "duration": 0.263886,
     "end_time": "2024-01-08T22:13:51.489439",
     "exception": false,
     "start_time": "2024-01-08T22:13:51.225553",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>merchant</th>\n",
       "      <th>category</th>\n",
       "      <th>amt</th>\n",
       "      <th>gender</th>\n",
       "      <th>lat</th>\n",
       "      <th>long</th>\n",
       "      <th>city_pop</th>\n",
       "      <th>job</th>\n",
       "      <th>unix_time</th>\n",
       "      <th>merch_lat</th>\n",
       "      <th>merch_long</th>\n",
       "      <th>is_fraud</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>fraud_Rippin, Kub and Mann</td>\n",
       "      <td>misc_net</td>\n",
       "      <td>4.97</td>\n",
       "      <td>F</td>\n",
       "      <td>36.0788</td>\n",
       "      <td>-81.1781</td>\n",
       "      <td>3495</td>\n",
       "      <td>Psychologist, counselling</td>\n",
       "      <td>1325376018</td>\n",
       "      <td>36.011293</td>\n",
       "      <td>-82.048315</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>fraud_Heller, Gutmann and Zieme</td>\n",
       "      <td>grocery_pos</td>\n",
       "      <td>107.23</td>\n",
       "      <td>F</td>\n",
       "      <td>48.8878</td>\n",
       "      <td>-118.2105</td>\n",
       "      <td>149</td>\n",
       "      <td>Special educational needs teacher</td>\n",
       "      <td>1325376044</td>\n",
       "      <td>49.159047</td>\n",
       "      <td>-118.186462</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>fraud_Lind-Buckridge</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>220.11</td>\n",
       "      <td>M</td>\n",
       "      <td>42.1808</td>\n",
       "      <td>-112.2620</td>\n",
       "      <td>4154</td>\n",
       "      <td>Nature conservation officer</td>\n",
       "      <td>1325376051</td>\n",
       "      <td>43.150704</td>\n",
       "      <td>-112.154481</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>fraud_Kutch, Hermiston and Farrell</td>\n",
       "      <td>gas_transport</td>\n",
       "      <td>45.00</td>\n",
       "      <td>M</td>\n",
       "      <td>46.2306</td>\n",
       "      <td>-112.1138</td>\n",
       "      <td>1939</td>\n",
       "      <td>Patent attorney</td>\n",
       "      <td>1325376076</td>\n",
       "      <td>47.034331</td>\n",
       "      <td>-112.561071</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>fraud_Keeling-Crist</td>\n",
       "      <td>misc_pos</td>\n",
       "      <td>41.96</td>\n",
       "      <td>M</td>\n",
       "      <td>38.4207</td>\n",
       "      <td>-79.4629</td>\n",
       "      <td>99</td>\n",
       "      <td>Dance movement psychotherapist</td>\n",
       "      <td>1325376186</td>\n",
       "      <td>38.674999</td>\n",
       "      <td>-78.632459</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",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>1296670</th>\n",
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       "      <td>15.56</td>\n",
       "      <td>M</td>\n",
       "      <td>37.7175</td>\n",
       "      <td>-112.4777</td>\n",
       "      <td>258</td>\n",
       "      <td>Geoscientist</td>\n",
       "      <td>1371816728</td>\n",
       "      <td>36.841266</td>\n",
       "      <td>-111.690765</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296671</th>\n",
       "      <td>fraud_Abernathy and Sons</td>\n",
       "      <td>food_dining</td>\n",
       "      <td>51.70</td>\n",
       "      <td>M</td>\n",
       "      <td>39.2667</td>\n",
       "      <td>-77.5101</td>\n",
       "      <td>100</td>\n",
       "      <td>Production assistant, television</td>\n",
       "      <td>1371816739</td>\n",
       "      <td>38.906881</td>\n",
       "      <td>-78.246528</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296672</th>\n",
       "      <td>fraud_Stiedemann Ltd</td>\n",
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       "      <td>105.93</td>\n",
       "      <td>M</td>\n",
       "      <td>32.9396</td>\n",
       "      <td>-105.8189</td>\n",
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       "      <td>Naval architect</td>\n",
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       "      <td>43.3526</td>\n",
       "      <td>-102.5411</td>\n",
       "      <td>1126</td>\n",
       "      <td>Volunteer coordinator</td>\n",
       "      <td>1371816816</td>\n",
       "      <td>42.788940</td>\n",
       "      <td>-103.241160</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296674</th>\n",
       "      <td>fraud_Langosh, Wintheiser and Hyatt</td>\n",
       "      <td>food_dining</td>\n",
       "      <td>4.30</td>\n",
       "      <td>M</td>\n",
       "      <td>45.8433</td>\n",
       "      <td>-113.8748</td>\n",
       "      <td>218</td>\n",
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       "      <td>1371816817</td>\n",
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       "      <td>-114.186110</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1296675 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    merchant       category     amt gender  \\\n",
       "0                 fraud_Rippin, Kub and Mann       misc_net    4.97      F   \n",
       "1            fraud_Heller, Gutmann and Zieme    grocery_pos  107.23      F   \n",
       "2                       fraud_Lind-Buckridge  entertainment  220.11      M   \n",
       "3         fraud_Kutch, Hermiston and Farrell  gas_transport   45.00      M   \n",
       "4                        fraud_Keeling-Crist       misc_pos   41.96      M   \n",
       "...                                      ...            ...     ...    ...   \n",
       "1296670                    fraud_Reichel Inc  entertainment   15.56      M   \n",
       "1296671             fraud_Abernathy and Sons    food_dining   51.70      M   \n",
       "1296672                 fraud_Stiedemann Ltd    food_dining  105.93      M   \n",
       "1296673  fraud_Reinger, Weissnat and Strosin    food_dining   74.90      M   \n",
       "1296674  fraud_Langosh, Wintheiser and Hyatt    food_dining    4.30      M   \n",
       "\n",
       "             lat      long  city_pop                                job  \\\n",
       "0        36.0788  -81.1781      3495          Psychologist, counselling   \n",
       "1        48.8878 -118.2105       149  Special educational needs teacher   \n",
       "2        42.1808 -112.2620      4154        Nature conservation officer   \n",
       "3        46.2306 -112.1138      1939                    Patent attorney   \n",
       "4        38.4207  -79.4629        99     Dance movement psychotherapist   \n",
       "...          ...       ...       ...                                ...   \n",
       "1296670  37.7175 -112.4777       258                       Geoscientist   \n",
       "1296671  39.2667  -77.5101       100   Production assistant, television   \n",
       "1296672  32.9396 -105.8189       899                    Naval architect   \n",
       "1296673  43.3526 -102.5411      1126              Volunteer coordinator   \n",
       "1296674  45.8433 -113.8748       218           Therapist, horticultural   \n",
       "\n",
       "          unix_time  merch_lat  merch_long  is_fraud  \n",
       "0        1325376018  36.011293  -82.048315         0  \n",
       "1        1325376044  49.159047 -118.186462         0  \n",
       "2        1325376051  43.150704 -112.154481         0  \n",
       "3        1325376076  47.034331 -112.561071         0  \n",
       "4        1325376186  38.674999  -78.632459         0  \n",
       "...             ...        ...         ...       ...  \n",
       "1296670  1371816728  36.841266 -111.690765         0  \n",
       "1296671  1371816739  38.906881  -78.246528         0  \n",
       "1296672  1371816752  33.619513 -105.130529         0  \n",
       "1296673  1371816816  42.788940 -103.241160         0  \n",
       "1296674  1371816817  46.565983 -114.186110         0  \n",
       "\n",
       "[1296675 rows x 12 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.drop(columns=['Unnamed: 0','cc_num','first', 'last', 'street', 'city', 'state', 'zip', 'dob', 'trans_num','trans_date_trans_time'],inplace=True)\n",
    "train_data"
   ]
  },
  {
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       "      <td>42.1808</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>45.00</td>\n",
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       "      <td>15.56</td>\n",
       "      <td>M</td>\n",
       "      <td>37.7175</td>\n",
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       "      <td>food_dining</td>\n",
       "      <td>51.70</td>\n",
       "      <td>M</td>\n",
       "      <td>39.2667</td>\n",
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       "      <td>100</td>\n",
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       "      <td>0</td>\n",
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       "      <td>105.93</td>\n",
       "      <td>M</td>\n",
       "      <td>32.9396</td>\n",
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       "      <td>43.3526</td>\n",
       "      <td>-102.5411</td>\n",
       "      <td>1126</td>\n",
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       "      <td>1371816816</td>\n",
       "      <td>42.788940</td>\n",
       "      <td>-103.241160</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
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       "      <td>fraud_Langosh, Wintheiser and Hyatt</td>\n",
       "      <td>food_dining</td>\n",
       "      <td>4.30</td>\n",
       "      <td>M</td>\n",
       "      <td>45.8433</td>\n",
       "      <td>-113.8748</td>\n",
       "      <td>218</td>\n",
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       "      <td>46.565983</td>\n",
       "      <td>-114.186110</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1296675 rows × 12 columns</p>\n",
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      ],
      "text/plain": [
       "                                    merchant       category     amt gender  \\\n",
       "0                 fraud_Rippin, Kub and Mann       misc_net    4.97      F   \n",
       "1            fraud_Heller, Gutmann and Zieme    grocery_pos  107.23      F   \n",
       "2                       fraud_Lind-Buckridge  entertainment  220.11      M   \n",
       "3         fraud_Kutch, Hermiston and Farrell  gas_transport   45.00      M   \n",
       "4                        fraud_Keeling-Crist       misc_pos   41.96      M   \n",
       "...                                      ...            ...     ...    ...   \n",
       "1296670                    fraud_Reichel Inc  entertainment   15.56      M   \n",
       "1296671             fraud_Abernathy and Sons    food_dining   51.70      M   \n",
       "1296672                 fraud_Stiedemann Ltd    food_dining  105.93      M   \n",
       "1296673  fraud_Reinger, Weissnat and Strosin    food_dining   74.90      M   \n",
       "1296674  fraud_Langosh, Wintheiser and Hyatt    food_dining    4.30      M   \n",
       "\n",
       "             lat      long  city_pop                                job  \\\n",
       "0        36.0788  -81.1781      3495          Psychologist, counselling   \n",
       "1        48.8878 -118.2105       149  Special educational needs teacher   \n",
       "2        42.1808 -112.2620      4154        Nature conservation officer   \n",
       "3        46.2306 -112.1138      1939                    Patent attorney   \n",
       "4        38.4207  -79.4629        99     Dance movement psychotherapist   \n",
       "...          ...       ...       ...                                ...   \n",
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       "1296671  39.2667  -77.5101       100   Production assistant, television   \n",
       "1296672  32.9396 -105.8189       899                    Naval architect   \n",
       "1296673  43.3526 -102.5411      1126              Volunteer coordinator   \n",
       "1296674  45.8433 -113.8748       218           Therapist, horticultural   \n",
       "\n",
       "          unix_time  merch_lat  merch_long  is_fraud  \n",
       "0        1325376018  36.011293  -82.048315         0  \n",
       "1        1325376044  49.159047 -118.186462         0  \n",
       "2        1325376051  43.150704 -112.154481         0  \n",
       "3        1325376076  47.034331 -112.561071         0  \n",
       "4        1325376186  38.674999  -78.632459         0  \n",
       "...             ...        ...         ...       ...  \n",
       "1296670  1371816728  36.841266 -111.690765         0  \n",
       "1296671  1371816739  38.906881  -78.246528         0  \n",
       "1296672  1371816752  33.619513 -105.130529         0  \n",
       "1296673  1371816816  42.788940 -103.241160         0  \n",
       "1296674  1371816817  46.565983 -114.186110         0  \n",
       "\n",
       "[1296675 rows x 12 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Drop all rows that contain missing values \n",
    "train_data.dropna(ignore_index=True)\n",
    "train_data"
   ]
  },
  {
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   "execution_count": 10,
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>fraud_Rippin, Kub and Mann</td>\n",
       "      <td>misc_net</td>\n",
       "      <td>4.97</td>\n",
       "      <td>F</td>\n",
       "      <td>36.0788</td>\n",
       "      <td>-81.1781</td>\n",
       "      <td>3495</td>\n",
       "      <td>Psychologist, counselling</td>\n",
       "      <td>1325376018</td>\n",
       "      <td>36.011293</td>\n",
       "      <td>-82.048315</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>fraud_Heller, Gutmann and Zieme</td>\n",
       "      <td>grocery_pos</td>\n",
       "      <td>107.23</td>\n",
       "      <td>F</td>\n",
       "      <td>48.8878</td>\n",
       "      <td>-118.2105</td>\n",
       "      <td>149</td>\n",
       "      <td>Special educational needs teacher</td>\n",
       "      <td>1325376044</td>\n",
       "      <td>49.159047</td>\n",
       "      <td>-118.186462</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>fraud_Lind-Buckridge</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>220.11</td>\n",
       "      <td>M</td>\n",
       "      <td>42.1808</td>\n",
       "      <td>-112.2620</td>\n",
       "      <td>4154</td>\n",
       "      <td>Nature conservation officer</td>\n",
       "      <td>1325376051</td>\n",
       "      <td>43.150704</td>\n",
       "      <td>-112.154481</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>fraud_Kutch, Hermiston and Farrell</td>\n",
       "      <td>gas_transport</td>\n",
       "      <td>45.00</td>\n",
       "      <td>M</td>\n",
       "      <td>46.2306</td>\n",
       "      <td>-112.1138</td>\n",
       "      <td>1939</td>\n",
       "      <td>Patent attorney</td>\n",
       "      <td>1325376076</td>\n",
       "      <td>47.034331</td>\n",
       "      <td>-112.561071</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>fraud_Keeling-Crist</td>\n",
       "      <td>misc_pos</td>\n",
       "      <td>41.96</td>\n",
       "      <td>M</td>\n",
       "      <td>38.4207</td>\n",
       "      <td>-79.4629</td>\n",
       "      <td>99</td>\n",
       "      <td>Dance movement psychotherapist</td>\n",
       "      <td>1325376186</td>\n",
       "      <td>38.674999</td>\n",
       "      <td>-78.632459</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296670</th>\n",
       "      <td>fraud_Reichel Inc</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>15.56</td>\n",
       "      <td>M</td>\n",
       "      <td>37.7175</td>\n",
       "      <td>-112.4777</td>\n",
       "      <td>258</td>\n",
       "      <td>Geoscientist</td>\n",
       "      <td>1371816728</td>\n",
       "      <td>36.841266</td>\n",
       "      <td>-111.690765</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296671</th>\n",
       "      <td>fraud_Abernathy and Sons</td>\n",
       "      <td>food_dining</td>\n",
       "      <td>51.70</td>\n",
       "      <td>M</td>\n",
       "      <td>39.2667</td>\n",
       "      <td>-77.5101</td>\n",
       "      <td>100</td>\n",
       "      <td>Production assistant, television</td>\n",
       "      <td>1371816739</td>\n",
       "      <td>38.906881</td>\n",
       "      <td>-78.246528</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296672</th>\n",
       "      <td>fraud_Stiedemann Ltd</td>\n",
       "      <td>food_dining</td>\n",
       "      <td>105.93</td>\n",
       "      <td>M</td>\n",
       "      <td>32.9396</td>\n",
       "      <td>-105.8189</td>\n",
       "      <td>899</td>\n",
       "      <td>Naval architect</td>\n",
       "      <td>1371816752</td>\n",
       "      <td>33.619513</td>\n",
       "      <td>-105.130529</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296673</th>\n",
       "      <td>fraud_Reinger, Weissnat and Strosin</td>\n",
       "      <td>food_dining</td>\n",
       "      <td>74.90</td>\n",
       "      <td>M</td>\n",
       "      <td>43.3526</td>\n",
       "      <td>-102.5411</td>\n",
       "      <td>1126</td>\n",
       "      <td>Volunteer coordinator</td>\n",
       "      <td>1371816816</td>\n",
       "      <td>42.788940</td>\n",
       "      <td>-103.241160</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296674</th>\n",
       "      <td>fraud_Langosh, Wintheiser and Hyatt</td>\n",
       "      <td>food_dining</td>\n",
       "      <td>4.30</td>\n",
       "      <td>M</td>\n",
       "      <td>45.8433</td>\n",
       "      <td>-113.8748</td>\n",
       "      <td>218</td>\n",
       "      <td>Therapist, horticultural</td>\n",
       "      <td>1371816817</td>\n",
       "      <td>46.565983</td>\n",
       "      <td>-114.186110</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1296675 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    merchant       category     amt gender  \\\n",
       "0                 fraud_Rippin, Kub and Mann       misc_net    4.97      F   \n",
       "1            fraud_Heller, Gutmann and Zieme    grocery_pos  107.23      F   \n",
       "2                       fraud_Lind-Buckridge  entertainment  220.11      M   \n",
       "3         fraud_Kutch, Hermiston and Farrell  gas_transport   45.00      M   \n",
       "4                        fraud_Keeling-Crist       misc_pos   41.96      M   \n",
       "...                                      ...            ...     ...    ...   \n",
       "1296670                    fraud_Reichel Inc  entertainment   15.56      M   \n",
       "1296671             fraud_Abernathy and Sons    food_dining   51.70      M   \n",
       "1296672                 fraud_Stiedemann Ltd    food_dining  105.93      M   \n",
       "1296673  fraud_Reinger, Weissnat and Strosin    food_dining   74.90      M   \n",
       "1296674  fraud_Langosh, Wintheiser and Hyatt    food_dining    4.30      M   \n",
       "\n",
       "             lat      long  city_pop                                job  \\\n",
       "0        36.0788  -81.1781      3495          Psychologist, counselling   \n",
       "1        48.8878 -118.2105       149  Special educational needs teacher   \n",
       "2        42.1808 -112.2620      4154        Nature conservation officer   \n",
       "3        46.2306 -112.1138      1939                    Patent attorney   \n",
       "4        38.4207  -79.4629        99     Dance movement psychotherapist   \n",
       "...          ...       ...       ...                                ...   \n",
       "1296670  37.7175 -112.4777       258                       Geoscientist   \n",
       "1296671  39.2667  -77.5101       100   Production assistant, television   \n",
       "1296672  32.9396 -105.8189       899                    Naval architect   \n",
       "1296673  43.3526 -102.5411      1126              Volunteer coordinator   \n",
       "1296674  45.8433 -113.8748       218           Therapist, horticultural   \n",
       "\n",
       "          unix_time  merch_lat  merch_long  is_fraud  \n",
       "0        1325376018  36.011293  -82.048315         0  \n",
       "1        1325376044  49.159047 -118.186462         0  \n",
       "2        1325376051  43.150704 -112.154481         0  \n",
       "3        1325376076  47.034331 -112.561071         0  \n",
       "4        1325376186  38.674999  -78.632459         0  \n",
       "...             ...        ...         ...       ...  \n",
       "1296670  1371816728  36.841266 -111.690765         0  \n",
       "1296671  1371816739  38.906881  -78.246528         0  \n",
       "1296672  1371816752  33.619513 -105.130529         0  \n",
       "1296673  1371816816  42.788940 -103.241160         0  \n",
       "1296674  1371816817  46.565983 -114.186110         0  \n",
       "\n",
       "[1296675 rows x 12 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.dropna(ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "15c84a78",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-08T22:13:52.879546Z",
     "iopub.status.busy": "2024-01-08T22:13:52.878347Z",
     "iopub.status.idle": "2024-01-08T22:13:54.522742Z",
     "shell.execute_reply": "2024-01-08T22:13:54.521446Z"
    },
    "papermill": {
     "duration": 1.661576,
     "end_time": "2024-01-08T22:13:54.525655",
     "exception": false,
     "start_time": "2024-01-08T22:13:52.864079",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "encoder = LabelEncoder()\n",
    "train_data[\"merchant\"] = encoder.fit_transform(train_data[\"merchant\"])\n",
    "train_data[\"category\"] = encoder.fit_transform(train_data[\"category\"])\n",
    "train_data[\"gender\"] = encoder.fit_transform(train_data[\"gender\"])\n",
    "train_data[\"job\"] = encoder.fit_transform(train_data[\"job\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "45cf7129",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-08T22:13:54.553042Z",
     "iopub.status.busy": "2024-01-08T22:13:54.552521Z",
     "iopub.status.idle": "2024-01-08T22:13:54.580727Z",
     "shell.execute_reply": "2024-01-08T22:13:54.579222Z"
    },
    "papermill": {
     "duration": 0.04572,
     "end_time": "2024-01-08T22:13:54.584232",
     "exception": false,
     "start_time": "2024-01-08T22:13:54.538512",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>merchant</th>\n",
       "      <th>category</th>\n",
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       "<p>1296675 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         merchant  category     amt  gender      lat      long  city_pop  job  \\\n",
       "0             514         8    4.97       0  36.0788  -81.1781      3495  370   \n",
       "1             241         4  107.23       0  48.8878 -118.2105       149  428   \n",
       "2             390         0  220.11       1  42.1808 -112.2620      4154  307   \n",
       "3             360         2   45.00       1  46.2306 -112.1138      1939  328   \n",
       "4             297         9   41.96       1  38.4207  -79.4629        99  116   \n",
       "...           ...       ...     ...     ...      ...       ...       ...  ...   \n",
       "1296670       499         0   15.56       1  37.7175 -112.4777       258  215   \n",
       "1296671         2         1   51.70       1  39.2667  -77.5101       100  360   \n",
       "1296672       599         1  105.93       1  32.9396 -105.8189       899  308   \n",
       "1296673       509         1   74.90       1  43.3526 -102.5411      1126  485   \n",
       "1296674       370         1    4.30       1  45.8433 -113.8748       218  467   \n",
       "\n",
       "          unix_time  merch_lat  merch_long  is_fraud  \n",
       "0        1325376018  36.011293  -82.048315         0  \n",
       "1        1325376044  49.159047 -118.186462         0  \n",
       "2        1325376051  43.150704 -112.154481         0  \n",
       "3        1325376076  47.034331 -112.561071         0  \n",
       "4        1325376186  38.674999  -78.632459         0  \n",
       "...             ...        ...         ...       ...  \n",
       "1296670  1371816728  36.841266 -111.690765         0  \n",
       "1296671  1371816739  38.906881  -78.246528         0  \n",
       "1296672  1371816752  33.619513 -105.130529         0  \n",
       "1296673  1371816816  42.788940 -103.241160         0  \n",
       "1296674  1371816817  46.565983 -114.186110         0  \n",
       "\n",
       "[1296675 rows x 12 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28878f4b",
   "metadata": {
    "papermill": {
     "duration": 0.012541,
     "end_time": "2024-01-08T22:13:54.613125",
     "exception": false,
     "start_time": "2024-01-08T22:13:54.600584",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# **3-EDA**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "37005c04",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-08T22:13:54.640591Z",
     "iopub.status.busy": "2024-01-08T22:13:54.640086Z",
     "iopub.status.idle": "2024-01-08T22:13:54.964800Z",
     "shell.execute_reply": "2024-01-08T22:13:54.963262Z"
    },
    "papermill": {
     "duration": 0.343116,
     "end_time": "2024-01-08T22:13:54.968854",
     "exception": false,
     "start_time": "2024-01-08T22:13:54.625738",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "exit_counts = train_data[\"is_fraud\"].value_counts()\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.subplot(1, 2, 1)  # Subplot for the pie chart\n",
    "plt.pie(exit_counts, labels=[\"No\", \"YES\"], autopct=\"%0.0f%%\")\n",
    "plt.title(\"is_fraud Counts\")\n",
    "plt.tight_layout()  # Adjust layout to prevent overlapping\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af368eab",
   "metadata": {
    "papermill": {
     "duration": 0.01286,
     "end_time": "2024-01-08T22:13:55.001330",
     "exception": false,
     "start_time": "2024-01-08T22:13:54.988470",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# **4-Train the Model**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5e9bd2d5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-08T22:13:55.030905Z",
     "iopub.status.busy": "2024-01-08T22:13:55.030156Z",
     "iopub.status.idle": "2024-01-08T22:13:55.093198Z",
     "shell.execute_reply": "2024-01-08T22:13:55.092254Z"
    },
    "papermill": {
     "duration": 0.080773,
     "end_time": "2024-01-08T22:13:55.095826",
     "exception": false,
     "start_time": "2024-01-08T22:13:55.015053",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "X = train_data.drop(columns=[\"is_fraud\"], inplace = False)\n",
    "Y = train_data[\"is_fraud\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "08e3db80",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-08T22:13:55.126049Z",
     "iopub.status.busy": "2024-01-08T22:13:55.125206Z",
     "iopub.status.idle": "2024-01-08T22:34:07.883818Z",
     "shell.execute_reply": "2024-01-08T22:34:07.882346Z"
    },
    "papermill": {
     "duration": 1212.791081,
     "end_time": "2024-01-08T22:34:07.900067",
     "exception": false,
     "start_time": "2024-01-08T22:13:55.108986",
     "status": "completed"
    },
    "tags": []
   },
   "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>SVC()</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\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">SVC</label><div class=\"sk-toggleable__content\"><pre>SVC()</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "SVC()"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = SVC()\n",
    "model.fit(X, Y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "212b4411",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-08T22:34:07.930695Z",
     "iopub.status.busy": "2024-01-08T22:34:07.930046Z",
     "iopub.status.idle": "2024-01-08T22:53:15.045373Z",
     "shell.execute_reply": "2024-01-08T22:53:15.044180Z"
    },
    "papermill": {
     "duration": 1147.147431,
     "end_time": "2024-01-08T22:53:15.061388",
     "exception": false,
     "start_time": "2024-01-08T22:34:07.913957",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9942113482561166"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.score(X, Y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2a267f2",
   "metadata": {
    "papermill": {
     "duration": 0.013789,
     "end_time": "2024-01-08T22:53:15.089273",
     "exception": false,
     "start_time": "2024-01-08T22:53:15.075484",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# **4-Test the model**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "9522637e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-08T22:53:15.119660Z",
     "iopub.status.busy": "2024-01-08T22:53:15.118824Z",
     "iopub.status.idle": "2024-01-08T22:53:21.893790Z",
     "shell.execute_reply": "2024-01-08T22:53:21.892267Z"
    },
    "papermill": {
     "duration": 6.792999,
     "end_time": "2024-01-08T22:53:21.896451",
     "exception": false,
     "start_time": "2024-01-08T22:53:15.103452",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
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       "      <td>fraud_Breitenberg LLC</td>\n",
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       "      <td>Eric</td>\n",
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       "      <th>555718</th>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>555719 rows × 23 columns</p>\n",
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       "        Unnamed: 0 trans_date_trans_time            cc_num  \\\n",
       "0                0   2020-06-21 12:14:25  2291163933867244   \n",
       "1                1   2020-06-21 12:14:33  3573030041201292   \n",
       "2                2   2020-06-21 12:14:53  3598215285024754   \n",
       "3                3   2020-06-21 12:15:15  3591919803438423   \n",
       "4                4   2020-06-21 12:15:17  3526826139003047   \n",
       "...            ...                   ...               ...   \n",
       "555714      555714   2020-12-31 23:59:07    30560609640617   \n",
       "555715      555715   2020-12-31 23:59:09  3556613125071656   \n",
       "555716      555716   2020-12-31 23:59:15  6011724471098086   \n",
       "555717      555717   2020-12-31 23:59:24     4079773899158   \n",
       "555718      555718   2020-12-31 23:59:34  4170689372027579   \n",
       "\n",
       "                                    merchant        category     amt    first  \\\n",
       "0                      fraud_Kirlin and Sons   personal_care    2.86     Jeff   \n",
       "1                       fraud_Sporer-Keebler   personal_care   29.84   Joanne   \n",
       "2       fraud_Swaniawski, Nitzsche and Welch  health_fitness   41.28   Ashley   \n",
       "3                          fraud_Haley Group        misc_pos   60.05    Brian   \n",
       "4                      fraud_Johnston-Casper          travel    3.19   Nathan   \n",
       "...                                      ...             ...     ...      ...   \n",
       "555714                 fraud_Reilly and Sons  health_fitness   43.77  Michael   \n",
       "555715                  fraud_Hoppe-Parisian       kids_pets  111.84     Jose   \n",
       "555716                       fraud_Rau-Robel       kids_pets   86.88      Ann   \n",
       "555717                 fraud_Breitenberg LLC          travel    7.99     Eric   \n",
       "555718                     fraud_Dare-Marvin   entertainment   38.13   Samuel   \n",
       "\n",
       "            last gender                       street  ...      lat      long  \\\n",
       "0        Elliott      M            351 Darlene Green  ...  33.9659  -80.9355   \n",
       "1       Williams      F             3638 Marsh Union  ...  40.3207 -110.4360   \n",
       "2          Lopez      F         9333 Valentine Point  ...  40.6729  -73.5365   \n",
       "3       Williams      M  32941 Krystal Mill Apt. 552  ...  28.5697  -80.8191   \n",
       "4         Massey      M     5783 Evan Roads Apt. 465  ...  44.2529  -85.0170   \n",
       "...          ...    ...                          ...  ...      ...       ...   \n",
       "555714     Olson      M          558 Michael Estates  ...  40.4931  -91.8912   \n",
       "555715   Vasquez      M          572 Davis Mountains  ...  29.0393  -95.4401   \n",
       "555716    Lawson      F   144 Evans Islands Apt. 683  ...  46.1966 -118.9017   \n",
       "555717   Preston      M   7020 Doyle Stream Apt. 951  ...  44.6255 -116.4493   \n",
       "555718      Frey      M     830 Myers Plaza Apt. 384  ...  35.6665  -97.4798   \n",
       "\n",
       "        city_pop                     job         dob  \\\n",
       "0         333497     Mechanical engineer  1968-03-19   \n",
       "1            302  Sales professional, IT  1990-01-17   \n",
       "2          34496       Librarian, public  1970-10-21   \n",
       "3          54767            Set designer  1987-07-25   \n",
       "4           1126      Furniture designer  1955-07-06   \n",
       "...          ...                     ...         ...   \n",
       "555714       519            Town planner  1966-02-13   \n",
       "555715     28739          Futures trader  1999-12-27   \n",
       "555716      3684                Musician  1981-11-29   \n",
       "555717       129            Cartographer  1965-12-15   \n",
       "555718    116001             Media buyer  1993-05-10   \n",
       "\n",
       "                               trans_num   unix_time  merch_lat  merch_long  \\\n",
       "0       2da90c7d74bd46a0caf3777415b3ebd3  1371816865  33.986391  -81.200714   \n",
       "1       324cc204407e99f51b0d6ca0055005e7  1371816873  39.450498 -109.960431   \n",
       "2       c81755dbbbea9d5c77f094348a7579be  1371816893  40.495810  -74.196111   \n",
       "3       2159175b9efe66dc301f149d3d5abf8c  1371816915  28.812398  -80.883061   \n",
       "4       57ff021bd3f328f8738bb535c302a31b  1371816917  44.959148  -85.884734   \n",
       "...                                  ...         ...        ...         ...   \n",
       "555714  9b1f753c79894c9f4b71f04581835ada  1388534347  39.946837  -91.333331   \n",
       "555715  2090647dac2c89a1d86c514c427f5b91  1388534349  29.661049  -96.186633   \n",
       "555716  6c5b7c8add471975aa0fec023b2e8408  1388534355  46.658340 -119.715054   \n",
       "555717  14392d723bb7737606b2700ac791b7aa  1388534364  44.470525 -117.080888   \n",
       "555718  1765bb45b3aa3224b4cdcb6e7a96cee3  1388534374  36.210097  -97.036372   \n",
       "\n",
       "        is_fraud  \n",
       "0              0  \n",
       "1              0  \n",
       "2              0  \n",
       "3              0  \n",
       "4              0  \n",
       "...          ...  \n",
       "555714         0  \n",
       "555715         0  \n",
       "555716         0  \n",
       "555717         0  \n",
       "555718         0  \n",
       "\n",
       "[555719 rows x 23 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data = pd.read_csv(\"/kaggle/input/fraud-detection/fraudTest.csv\")\n",
    "test_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d5b8a2d2",
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    },
    "tags": []
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>merchant</th>\n",
       "      <th>category</th>\n",
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       "      <td>40.495810</td>\n",
       "      <td>-74.196111</td>\n",
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       "      <td>-80.883061</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>44.2529</td>\n",
       "      <td>-85.0170</td>\n",
       "      <td>1126</td>\n",
       "      <td>Furniture designer</td>\n",
       "      <td>1371816917</td>\n",
       "      <td>44.959148</td>\n",
       "      <td>-85.884734</td>\n",
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       "      <td>40.4931</td>\n",
       "      <td>-91.8912</td>\n",
       "      <td>519</td>\n",
       "      <td>Town planner</td>\n",
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       "      <td>fraud_Hoppe-Parisian</td>\n",
       "      <td>kids_pets</td>\n",
       "      <td>111.84</td>\n",
       "      <td>M</td>\n",
       "      <td>29.0393</td>\n",
       "      <td>-95.4401</td>\n",
       "      <td>28739</td>\n",
       "      <td>Futures trader</td>\n",
       "      <td>1388534349</td>\n",
       "      <td>29.661049</td>\n",
       "      <td>-96.186633</td>\n",
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       "      <td>86.88</td>\n",
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       "      <td>46.1966</td>\n",
       "      <td>-118.9017</td>\n",
       "      <td>3684</td>\n",
       "      <td>Musician</td>\n",
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       "      <td>46.658340</td>\n",
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       "      <td>7.99</td>\n",
       "      <td>M</td>\n",
       "      <td>44.6255</td>\n",
       "      <td>-116.4493</td>\n",
       "      <td>129</td>\n",
       "      <td>Cartographer</td>\n",
       "      <td>1388534364</td>\n",
       "      <td>44.470525</td>\n",
       "      <td>-117.080888</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
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       "      <td>36.210097</td>\n",
       "      <td>-97.036372</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
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       "</table>\n",
       "<p>555719 rows × 12 columns</p>\n",
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      ],
      "text/plain": [
       "                                    merchant        category     amt gender  \\\n",
       "0                      fraud_Kirlin and Sons   personal_care    2.86      M   \n",
       "1                       fraud_Sporer-Keebler   personal_care   29.84      F   \n",
       "2       fraud_Swaniawski, Nitzsche and Welch  health_fitness   41.28      F   \n",
       "3                          fraud_Haley Group        misc_pos   60.05      M   \n",
       "4                      fraud_Johnston-Casper          travel    3.19      M   \n",
       "...                                      ...             ...     ...    ...   \n",
       "555714                 fraud_Reilly and Sons  health_fitness   43.77      M   \n",
       "555715                  fraud_Hoppe-Parisian       kids_pets  111.84      M   \n",
       "555716                       fraud_Rau-Robel       kids_pets   86.88      F   \n",
       "555717                 fraud_Breitenberg LLC          travel    7.99      M   \n",
       "555718                     fraud_Dare-Marvin   entertainment   38.13      M   \n",
       "\n",
       "            lat      long  city_pop                     job   unix_time  \\\n",
       "0       33.9659  -80.9355    333497     Mechanical engineer  1371816865   \n",
       "1       40.3207 -110.4360       302  Sales professional, IT  1371816873   \n",
       "2       40.6729  -73.5365     34496       Librarian, public  1371816893   \n",
       "3       28.5697  -80.8191     54767            Set designer  1371816915   \n",
       "4       44.2529  -85.0170      1126      Furniture designer  1371816917   \n",
       "...         ...       ...       ...                     ...         ...   \n",
       "555714  40.4931  -91.8912       519            Town planner  1388534347   \n",
       "555715  29.0393  -95.4401     28739          Futures trader  1388534349   \n",
       "555716  46.1966 -118.9017      3684                Musician  1388534355   \n",
       "555717  44.6255 -116.4493       129            Cartographer  1388534364   \n",
       "555718  35.6665  -97.4798    116001             Media buyer  1388534374   \n",
       "\n",
       "        merch_lat  merch_long  is_fraud  \n",
       "0       33.986391  -81.200714         0  \n",
       "1       39.450498 -109.960431         0  \n",
       "2       40.495810  -74.196111         0  \n",
       "3       28.812398  -80.883061         0  \n",
       "4       44.959148  -85.884734         0  \n",
       "...           ...         ...       ...  \n",
       "555714  39.946837  -91.333331         0  \n",
       "555715  29.661049  -96.186633         0  \n",
       "555716  46.658340 -119.715054         0  \n",
       "555717  44.470525 -117.080888         0  \n",
       "555718  36.210097  -97.036372         0  \n",
       "\n",
       "[555719 rows x 12 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data.drop(columns=['Unnamed: 0','cc_num','first', 'last', 'street', 'city', 'state', 'zip', 'dob', 'trans_num','trans_date_trans_time'],inplace=True)\n",
    "test_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "667d3b68",
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    "execution": {
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     "status": "completed"
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   "outputs": [],
   "source": [
    "encoder = LabelEncoder()\n",
    "test_data[\"merchant\"] = encoder.fit_transform(test_data[\"merchant\"])\n",
    "test_data[\"category\"] = encoder.fit_transform(test_data[\"category\"])\n",
    "test_data[\"gender\"] = encoder.fit_transform(test_data[\"gender\"])\n",
    "test_data[\"job\"] = encoder.fit_transform(test_data[\"job\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d0224943",
   "metadata": {
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   "outputs": [
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       "      <td>28.812398</td>\n",
       "      <td>-80.883061</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>292</td>\n",
       "      <td>13</td>\n",
       "      <td>3.19</td>\n",
       "      <td>1</td>\n",
       "      <td>44.2529</td>\n",
       "      <td>-85.0170</td>\n",
       "      <td>1126</td>\n",
       "      <td>196</td>\n",
       "      <td>1371816917</td>\n",
       "      <td>44.959148</td>\n",
       "      <td>-85.884734</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>555714</th>\n",
       "      <td>507</td>\n",
       "      <td>5</td>\n",
       "      <td>43.77</td>\n",
       "      <td>1</td>\n",
       "      <td>40.4931</td>\n",
       "      <td>-91.8912</td>\n",
       "      <td>519</td>\n",
       "      <td>460</td>\n",
       "      <td>1388534347</td>\n",
       "      <td>39.946837</td>\n",
       "      <td>-91.333331</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>555715</th>\n",
       "      <td>264</td>\n",
       "      <td>7</td>\n",
       "      <td>111.84</td>\n",
       "      <td>1</td>\n",
       "      <td>29.0393</td>\n",
       "      <td>-95.4401</td>\n",
       "      <td>28739</td>\n",
       "      <td>198</td>\n",
       "      <td>1388534349</td>\n",
       "      <td>29.661049</td>\n",
       "      <td>-96.186633</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>555716</th>\n",
       "      <td>496</td>\n",
       "      <td>7</td>\n",
       "      <td>86.88</td>\n",
       "      <td>0</td>\n",
       "      <td>46.1966</td>\n",
       "      <td>-118.9017</td>\n",
       "      <td>3684</td>\n",
       "      <td>294</td>\n",
       "      <td>1388534355</td>\n",
       "      <td>46.658340</td>\n",
       "      <td>-119.715054</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>555717</th>\n",
       "      <td>75</td>\n",
       "      <td>13</td>\n",
       "      <td>7.99</td>\n",
       "      <td>1</td>\n",
       "      <td>44.6255</td>\n",
       "      <td>-116.4493</td>\n",
       "      <td>129</td>\n",
       "      <td>58</td>\n",
       "      <td>1388534364</td>\n",
       "      <td>44.470525</td>\n",
       "      <td>-117.080888</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>555718</th>\n",
       "      <td>125</td>\n",
       "      <td>0</td>\n",
       "      <td>38.13</td>\n",
       "      <td>1</td>\n",
       "      <td>35.6665</td>\n",
       "      <td>-97.4798</td>\n",
       "      <td>116001</td>\n",
       "      <td>276</td>\n",
       "      <td>1388534374</td>\n",
       "      <td>36.210097</td>\n",
       "      <td>-97.036372</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>555719 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        merchant  category     amt  gender      lat      long  city_pop  job  \\\n",
       "0            319        10    2.86       1  33.9659  -80.9355    333497  275   \n",
       "1            591        10   29.84       0  40.3207 -110.4360       302  392   \n",
       "2            611         5   41.28       0  40.6729  -73.5365     34496  259   \n",
       "3            222         9   60.05       1  28.5697  -80.8191     54767  407   \n",
       "4            292        13    3.19       1  44.2529  -85.0170      1126  196   \n",
       "...          ...       ...     ...     ...      ...       ...       ...  ...   \n",
       "555714       507         5   43.77       1  40.4931  -91.8912       519  460   \n",
       "555715       264         7  111.84       1  29.0393  -95.4401     28739  198   \n",
       "555716       496         7   86.88       0  46.1966 -118.9017      3684  294   \n",
       "555717        75        13    7.99       1  44.6255 -116.4493       129   58   \n",
       "555718       125         0   38.13       1  35.6665  -97.4798    116001  276   \n",
       "\n",
       "         unix_time  merch_lat  merch_long  is_fraud  \n",
       "0       1371816865  33.986391  -81.200714         0  \n",
       "1       1371816873  39.450498 -109.960431         0  \n",
       "2       1371816893  40.495810  -74.196111         0  \n",
       "3       1371816915  28.812398  -80.883061         0  \n",
       "4       1371816917  44.959148  -85.884734         0  \n",
       "...            ...        ...         ...       ...  \n",
       "555714  1388534347  39.946837  -91.333331         0  \n",
       "555715  1388534349  29.661049  -96.186633         0  \n",
       "555716  1388534355  46.658340 -119.715054         0  \n",
       "555717  1388534364  44.470525 -117.080888         0  \n",
       "555718  1388534374  36.210097  -97.036372         0  \n",
       "\n",
       "[555719 rows x 12 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data"
   ]
  },
  {
   "cell_type": "code",
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   "id": "76d0a76a",
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     "iopub.execute_input": "2024-01-08T22:53:22.875587Z",
     "iopub.status.busy": "2024-01-08T22:53:22.875195Z",
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "X_test = test_data.drop(columns=[\"is_fraud\"], inplace = False)\n",
    "Y_test = test_data[\"is_fraud\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "35da2feb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-08T22:53:22.944397Z",
     "iopub.status.busy": "2024-01-08T22:53:22.943611Z",
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, ..., 0, 0, 0])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred = model.predict(X_test)\n",
    "y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "0083a623",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-08T23:01:33.202846Z",
     "iopub.status.busy": "2024-01-08T23:01:33.202361Z",
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     "shell.execute_reply": "2024-01-08T23:01:33.261918Z"
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     "exception": false,
     "start_time": "2024-01-08T23:01:33.184505",
     "status": "completed"
    },
    "tags": []
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9961401355721147"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy = accuracy_score(test_data['is_fraud'],y_pred)\n",
    "accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6b90f4cf",
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