fraud_detection.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "**fraud detection**"
      ],
      "metadata": {
        "id": "l1bvOsM_8NH6"
      },
      "id": "l1bvOsM_8NH6"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "cdda987d-45c0-44e5-869e-84279577a38b"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import pandas as pd"
      ],
      "id": "cdda987d-45c0-44e5-869e-84279577a38b"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "6a8b4ab0"
      },
      "outputs": [],
      "source": [
        "# do some preprocessing "
      ],
      "id": "6a8b4ab0"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "3f24eb72-9be5-4124-a656-0fc34a93a771",
        "outputId": "b2a93a72-d3f1-470d-f01a-8e488a169c52",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         Time        V1        V2        V3        V4        V5        V6  \\\n",
              "0      8365.0 -0.655093  1.102283  1.610914  2.542440  0.928295  0.344427   \n",
              "1     10222.0 -0.643681  0.953126  2.223666  1.134587 -0.198051  0.435065   \n",
              "2     35866.0 -2.044489  3.368306 -3.937111  5.623120 -3.079232 -1.253474   \n",
              "3     10836.0  1.020913 -0.400279  0.662579  0.341929 -0.656141 -0.021927   \n",
              "4        69.0  0.298503  2.142722 -1.542143  1.561332  0.938108 -2.145673   \n",
              "...       ...       ...       ...       ...       ...       ...       ...   \n",
              "7835   5838.0 -1.494748  1.374609  1.739505 -0.404363  0.337228 -0.353954   \n",
              "7836  11005.0  1.308485  0.069616  0.545896  0.115439 -0.312410 -0.324753   \n",
              "7837   8827.0 -1.746494 -0.022183  1.700978 -3.494827 -0.538017 -0.800348   \n",
              "7838   2097.0 -0.612088  0.568390  1.207450 -2.126447  0.378698 -0.712041   \n",
              "7839   6754.0  1.055224 -0.841109 -0.136485 -0.494300 -0.619118 -0.632461   \n",
              "\n",
              "            V7        V8        V9  ...       V21       V22       V23  \\\n",
              "0     0.340831 -0.004130 -0.039325  ...  0.025710  0.297263 -0.195074   \n",
              "1     0.221857  0.017773  1.931767  ... -0.066355  0.684519 -0.210179   \n",
              "2    -5.778880  1.707428 -4.467103  ...  1.483594  0.834311 -0.148486   \n",
              "3    -0.386604  0.054592  1.820545  ... -0.131286 -0.065529 -0.067101   \n",
              "4     1.405569 -0.778459  0.328636  ... -0.290987 -0.000235  0.092174   \n",
              "...        ...       ...       ...  ...       ...       ...       ...   \n",
              "7835  0.564640  0.103308  0.928487  ... -0.366262 -0.806897 -0.032148   \n",
              "7836 -0.373901 -0.216854  1.610789  ... -0.108423  0.013710 -0.132407   \n",
              "7837 -0.106467  0.517637  2.786295  ...  0.152429  0.571973 -0.334028   \n",
              "7838  0.776533  0.027359  0.202120  ...  0.217032  0.676543 -0.324870   \n",
              "7839 -0.105590 -0.344353 -0.096634  ...  0.157926  0.207187 -0.325495   \n",
              "\n",
              "           V24       V25       V26       V27       V28  Amount  Class  \n",
              "0    -0.476353 -0.269339  0.154728 -0.004028  0.155044   16.93    0.0  \n",
              "1     0.036703 -0.126450 -0.199370  0.377610  0.033734   20.24    0.0  \n",
              "2     0.001669 -0.038996  0.389526  1.300236  0.549940    7.61    1.0  \n",
              "3     0.260703  0.253718  1.066000 -0.096361 -0.005774   79.95    0.0  \n",
              "4     0.586205 -0.397314 -0.480949  0.251145 -0.242279    0.78    0.0  \n",
              "...        ...       ...       ...       ...       ...     ...    ...  \n",
              "7835  0.084964  0.148915 -0.015621  0.064359  0.193122    5.99    0.0  \n",
              "7836 -0.392797  0.360448  1.078788 -0.082476 -0.000158   14.95    0.0  \n",
              "7837 -0.019782  0.949107 -0.907445  0.167863 -0.020605   74.11    0.0  \n",
              "7838  0.030754  0.271729 -0.752923  0.126115  0.097501    1.00    0.0  \n",
              "7839  0.015611  0.617489 -0.205207 -0.078457  0.021740  200.88    0.0  \n",
              "\n",
              "[7840 rows x 31 columns]"
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Time</th>\n",
              "      <th>V1</th>\n",
              "      <th>V2</th>\n",
              "      <th>V3</th>\n",
              "      <th>V4</th>\n",
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              "      <th>V21</th>\n",
              "      <th>V22</th>\n",
              "      <th>V23</th>\n",
              "      <th>V24</th>\n",
              "      <th>V25</th>\n",
              "      <th>V26</th>\n",
              "      <th>V27</th>\n",
              "      <th>V28</th>\n",
              "      <th>Amount</th>\n",
              "      <th>Class</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>8365.0</td>\n",
              "      <td>-0.655093</td>\n",
              "      <td>1.102283</td>\n",
              "      <td>1.610914</td>\n",
              "      <td>2.542440</td>\n",
              "      <td>0.928295</td>\n",
              "      <td>0.344427</td>\n",
              "      <td>0.340831</td>\n",
              "      <td>-0.004130</td>\n",
              "      <td>-0.039325</td>\n",
              "      <td>...</td>\n",
              "      <td>0.025710</td>\n",
              "      <td>0.297263</td>\n",
              "      <td>-0.195074</td>\n",
              "      <td>-0.476353</td>\n",
              "      <td>-0.269339</td>\n",
              "      <td>0.154728</td>\n",
              "      <td>-0.004028</td>\n",
              "      <td>0.155044</td>\n",
              "      <td>16.93</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10222.0</td>\n",
              "      <td>-0.643681</td>\n",
              "      <td>0.953126</td>\n",
              "      <td>2.223666</td>\n",
              "      <td>1.134587</td>\n",
              "      <td>-0.198051</td>\n",
              "      <td>0.435065</td>\n",
              "      <td>0.221857</td>\n",
              "      <td>0.017773</td>\n",
              "      <td>1.931767</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.066355</td>\n",
              "      <td>0.684519</td>\n",
              "      <td>-0.210179</td>\n",
              "      <td>0.036703</td>\n",
              "      <td>-0.126450</td>\n",
              "      <td>-0.199370</td>\n",
              "      <td>0.377610</td>\n",
              "      <td>0.033734</td>\n",
              "      <td>20.24</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>35866.0</td>\n",
              "      <td>-2.044489</td>\n",
              "      <td>3.368306</td>\n",
              "      <td>-3.937111</td>\n",
              "      <td>5.623120</td>\n",
              "      <td>-3.079232</td>\n",
              "      <td>-1.253474</td>\n",
              "      <td>-5.778880</td>\n",
              "      <td>1.707428</td>\n",
              "      <td>-4.467103</td>\n",
              "      <td>...</td>\n",
              "      <td>1.483594</td>\n",
              "      <td>0.834311</td>\n",
              "      <td>-0.148486</td>\n",
              "      <td>0.001669</td>\n",
              "      <td>-0.038996</td>\n",
              "      <td>0.389526</td>\n",
              "      <td>1.300236</td>\n",
              "      <td>0.549940</td>\n",
              "      <td>7.61</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>10836.0</td>\n",
              "      <td>1.020913</td>\n",
              "      <td>-0.400279</td>\n",
              "      <td>0.662579</td>\n",
              "      <td>0.341929</td>\n",
              "      <td>-0.656141</td>\n",
              "      <td>-0.021927</td>\n",
              "      <td>-0.386604</td>\n",
              "      <td>0.054592</td>\n",
              "      <td>1.820545</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.131286</td>\n",
              "      <td>-0.065529</td>\n",
              "      <td>-0.067101</td>\n",
              "      <td>0.260703</td>\n",
              "      <td>0.253718</td>\n",
              "      <td>1.066000</td>\n",
              "      <td>-0.096361</td>\n",
              "      <td>-0.005774</td>\n",
              "      <td>79.95</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>69.0</td>\n",
              "      <td>0.298503</td>\n",
              "      <td>2.142722</td>\n",
              "      <td>-1.542143</td>\n",
              "      <td>1.561332</td>\n",
              "      <td>0.938108</td>\n",
              "      <td>-2.145673</td>\n",
              "      <td>1.405569</td>\n",
              "      <td>-0.778459</td>\n",
              "      <td>0.328636</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.290987</td>\n",
              "      <td>-0.000235</td>\n",
              "      <td>0.092174</td>\n",
              "      <td>0.586205</td>\n",
              "      <td>-0.397314</td>\n",
              "      <td>-0.480949</td>\n",
              "      <td>0.251145</td>\n",
              "      <td>-0.242279</td>\n",
              "      <td>0.78</td>\n",
              "      <td>0.0</td>\n",
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              "      <th>...</th>\n",
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              "      <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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              "      <th>7835</th>\n",
              "      <td>5838.0</td>\n",
              "      <td>-1.494748</td>\n",
              "      <td>1.374609</td>\n",
              "      <td>1.739505</td>\n",
              "      <td>-0.404363</td>\n",
              "      <td>0.337228</td>\n",
              "      <td>-0.353954</td>\n",
              "      <td>0.564640</td>\n",
              "      <td>0.103308</td>\n",
              "      <td>0.928487</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.366262</td>\n",
              "      <td>-0.806897</td>\n",
              "      <td>-0.032148</td>\n",
              "      <td>0.084964</td>\n",
              "      <td>0.148915</td>\n",
              "      <td>-0.015621</td>\n",
              "      <td>0.064359</td>\n",
              "      <td>0.193122</td>\n",
              "      <td>5.99</td>\n",
              "      <td>0.0</td>\n",
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              "      <th>7836</th>\n",
              "      <td>11005.0</td>\n",
              "      <td>1.308485</td>\n",
              "      <td>0.069616</td>\n",
              "      <td>0.545896</td>\n",
              "      <td>0.115439</td>\n",
              "      <td>-0.312410</td>\n",
              "      <td>-0.324753</td>\n",
              "      <td>-0.373901</td>\n",
              "      <td>-0.216854</td>\n",
              "      <td>1.610789</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.108423</td>\n",
              "      <td>0.013710</td>\n",
              "      <td>-0.132407</td>\n",
              "      <td>-0.392797</td>\n",
              "      <td>0.360448</td>\n",
              "      <td>1.078788</td>\n",
              "      <td>-0.082476</td>\n",
              "      <td>-0.000158</td>\n",
              "      <td>14.95</td>\n",
              "      <td>0.0</td>\n",
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              "      <th>7837</th>\n",
              "      <td>8827.0</td>\n",
              "      <td>-1.746494</td>\n",
              "      <td>-0.022183</td>\n",
              "      <td>1.700978</td>\n",
              "      <td>-3.494827</td>\n",
              "      <td>-0.538017</td>\n",
              "      <td>-0.800348</td>\n",
              "      <td>-0.106467</td>\n",
              "      <td>0.517637</td>\n",
              "      <td>2.786295</td>\n",
              "      <td>...</td>\n",
              "      <td>0.152429</td>\n",
              "      <td>0.571973</td>\n",
              "      <td>-0.334028</td>\n",
              "      <td>-0.019782</td>\n",
              "      <td>0.949107</td>\n",
              "      <td>-0.907445</td>\n",
              "      <td>0.167863</td>\n",
              "      <td>-0.020605</td>\n",
              "      <td>74.11</td>\n",
              "      <td>0.0</td>\n",
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              "      <th>7838</th>\n",
              "      <td>2097.0</td>\n",
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              "      <td>0.568390</td>\n",
              "      <td>1.207450</td>\n",
              "      <td>-2.126447</td>\n",
              "      <td>0.378698</td>\n",
              "      <td>-0.712041</td>\n",
              "      <td>0.776533</td>\n",
              "      <td>0.027359</td>\n",
              "      <td>0.202120</td>\n",
              "      <td>...</td>\n",
              "      <td>0.217032</td>\n",
              "      <td>0.676543</td>\n",
              "      <td>-0.324870</td>\n",
              "      <td>0.030754</td>\n",
              "      <td>0.271729</td>\n",
              "      <td>-0.752923</td>\n",
              "      <td>0.126115</td>\n",
              "      <td>0.097501</td>\n",
              "      <td>1.00</td>\n",
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              "      <th>7839</th>\n",
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              "      <td>-0.096634</td>\n",
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              "      <td>-0.205207</td>\n",
              "      <td>-0.078457</td>\n",
              "      <td>0.021740</td>\n",
              "      <td>200.88</td>\n",
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              "          document.querySelector('#df-de9c4ee6-bc69-421e-a8f9-b14cfa687f17 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-de9c4ee6-bc69-421e-a8f9-b14cfa687f17');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ],
      "source": [
        "train_data = pd.read_csv('fraud_train.csv')\n",
        "train_data"
      ],
      "id": "3f24eb72-9be5-4124-a656-0fc34a93a771"
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "kLaId8wfZtmc"
      },
      "id": "kLaId8wfZtmc",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "87165f90",
        "outputId": "c9dc0475-c7e3-46a8-8292-7e4c5936313c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         Time        V1        V2        V3        V4        V5        V6  \\\n",
              "0      2618.0 -1.906672 -1.437287  1.871960 -2.277146  0.224878 -0.137438   \n",
              "1       742.0  1.304437 -0.709851 -0.112405 -2.207912 -0.355304  0.170636   \n",
              "2      9218.0  1.153876 -0.203609  0.878412  0.879436 -0.477480  0.664532   \n",
              "3     11262.0 -0.654664  0.658514  1.923801 -1.440155  1.206681  0.397940   \n",
              "4         2.0 -1.158233  0.877737  1.548718  0.403034 -0.407193  0.095921   \n",
              "...       ...       ...       ...       ...       ...       ...       ...   \n",
              "2609  14272.0  1.249014  0.449678  0.196640  1.140253  0.284454 -0.136601   \n",
              "2610   3017.0 -0.873406  0.996277  1.370080  1.314848 -0.289889  0.244702   \n",
              "2611   5822.0 -1.746504  2.336897  2.211292  3.887689 -0.401255  1.462920   \n",
              "2612   7559.0 -0.683262  2.184431  0.086991  1.474910  1.195123 -1.304462   \n",
              "2613  10996.0  1.143699 -0.198893  0.931460  0.288985 -1.000110 -0.652050   \n",
              "\n",
              "            V7        V8        V9  ...       V20       V21       V22  \\\n",
              "0    -0.436180  0.447350  1.398436  ... -0.105557  0.324344  0.927203   \n",
              "1    -0.518525  0.050055  2.470382  ... -0.012647  0.065871  0.610271   \n",
              "2    -0.739738  0.290105  2.184308  ... -0.258792 -0.254076 -0.182890   \n",
              "3     0.861397 -0.465204  1.301399  ...  0.089678 -0.379451 -0.528356   \n",
              "4     0.592941 -0.270533  0.817739  ...  0.408542 -0.009431  0.798278   \n",
              "...        ...       ...       ...  ...       ...       ...       ...   \n",
              "2609  0.053458 -0.158091  1.252740  ... -0.188196 -0.129143 -0.016091   \n",
              "2610  0.136410  0.704062 -0.730132  ... -0.125464  0.095403  0.227194   \n",
              "2611 -0.853872 -1.090633 -0.109370  ... -0.073322  1.508737 -0.127188   \n",
              "2612  1.143837 -0.219464 -0.059003  ...  0.041409 -0.228812 -0.484496   \n",
              "2613 -0.579970 -0.012022  1.630406  ... -0.101879 -0.000246  0.115612   \n",
              "\n",
              "           V23       V24       V25       V26       V27       V28  Amount  \n",
              "0    -0.060459 -0.241201  0.035111 -0.009894 -0.018061  0.239372  129.00  \n",
              "1    -0.375163 -1.229720  0.948828 -0.485356  0.111789  0.012819   25.95  \n",
              "2    -0.055363 -0.314974  0.398081  0.525719 -0.024923 -0.013459    0.01  \n",
              "3    -0.466774 -1.316150  0.181729  0.826051 -0.499333 -0.429874   11.00  \n",
              "4    -0.137458  0.141267 -0.206010  0.502292  0.219422  0.215153   69.99  \n",
              "...        ...       ...       ...       ...       ...       ...     ...  \n",
              "2609 -0.124864 -0.504412  0.675462 -0.304683  0.005531  0.005172    0.89  \n",
              "2610 -0.110924  0.200514  0.049422 -0.215075  0.007172  0.029088   28.06  \n",
              "2611  0.188788 -0.087296 -0.365483  0.143746  0.043014 -0.022648   20.64  \n",
              "2612 -0.463930  0.130512  0.555804 -0.240149 -0.077529  0.137752    0.89  \n",
              "2613 -0.009653  0.522929  0.102863  1.002485 -0.104637 -0.000706   39.00  \n",
              "\n",
              "[2614 rows x 30 columns]"
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Time</th>\n",
              "      <th>V1</th>\n",
              "      <th>V2</th>\n",
              "      <th>V3</th>\n",
              "      <th>V4</th>\n",
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              "      <th>V8</th>\n",
              "      <th>V9</th>\n",
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              "      <th>V20</th>\n",
              "      <th>V21</th>\n",
              "      <th>V22</th>\n",
              "      <th>V23</th>\n",
              "      <th>V24</th>\n",
              "      <th>V25</th>\n",
              "      <th>V26</th>\n",
              "      <th>V27</th>\n",
              "      <th>V28</th>\n",
              "      <th>Amount</th>\n",
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              "  </thead>\n",
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              "      <th>0</th>\n",
              "      <td>2618.0</td>\n",
              "      <td>-1.906672</td>\n",
              "      <td>-1.437287</td>\n",
              "      <td>1.871960</td>\n",
              "      <td>-2.277146</td>\n",
              "      <td>0.224878</td>\n",
              "      <td>-0.137438</td>\n",
              "      <td>-0.436180</td>\n",
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              "      <td>-0.105557</td>\n",
              "      <td>0.324344</td>\n",
              "      <td>0.927203</td>\n",
              "      <td>-0.060459</td>\n",
              "      <td>-0.241201</td>\n",
              "      <td>0.035111</td>\n",
              "      <td>-0.009894</td>\n",
              "      <td>-0.018061</td>\n",
              "      <td>0.239372</td>\n",
              "      <td>129.00</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>742.0</td>\n",
              "      <td>1.304437</td>\n",
              "      <td>-0.709851</td>\n",
              "      <td>-0.112405</td>\n",
              "      <td>-2.207912</td>\n",
              "      <td>-0.355304</td>\n",
              "      <td>0.170636</td>\n",
              "      <td>-0.518525</td>\n",
              "      <td>0.050055</td>\n",
              "      <td>2.470382</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.012647</td>\n",
              "      <td>0.065871</td>\n",
              "      <td>0.610271</td>\n",
              "      <td>-0.375163</td>\n",
              "      <td>-1.229720</td>\n",
              "      <td>0.948828</td>\n",
              "      <td>-0.485356</td>\n",
              "      <td>0.111789</td>\n",
              "      <td>0.012819</td>\n",
              "      <td>25.95</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>9218.0</td>\n",
              "      <td>1.153876</td>\n",
              "      <td>-0.203609</td>\n",
              "      <td>0.878412</td>\n",
              "      <td>0.879436</td>\n",
              "      <td>-0.477480</td>\n",
              "      <td>0.664532</td>\n",
              "      <td>-0.739738</td>\n",
              "      <td>0.290105</td>\n",
              "      <td>2.184308</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.258792</td>\n",
              "      <td>-0.254076</td>\n",
              "      <td>-0.182890</td>\n",
              "      <td>-0.055363</td>\n",
              "      <td>-0.314974</td>\n",
              "      <td>0.398081</td>\n",
              "      <td>0.525719</td>\n",
              "      <td>-0.024923</td>\n",
              "      <td>-0.013459</td>\n",
              "      <td>0.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>11262.0</td>\n",
              "      <td>-0.654664</td>\n",
              "      <td>0.658514</td>\n",
              "      <td>1.923801</td>\n",
              "      <td>-1.440155</td>\n",
              "      <td>1.206681</td>\n",
              "      <td>0.397940</td>\n",
              "      <td>0.861397</td>\n",
              "      <td>-0.465204</td>\n",
              "      <td>1.301399</td>\n",
              "      <td>...</td>\n",
              "      <td>0.089678</td>\n",
              "      <td>-0.379451</td>\n",
              "      <td>-0.528356</td>\n",
              "      <td>-0.466774</td>\n",
              "      <td>-1.316150</td>\n",
              "      <td>0.181729</td>\n",
              "      <td>0.826051</td>\n",
              "      <td>-0.499333</td>\n",
              "      <td>-0.429874</td>\n",
              "      <td>11.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2.0</td>\n",
              "      <td>-1.158233</td>\n",
              "      <td>0.877737</td>\n",
              "      <td>1.548718</td>\n",
              "      <td>0.403034</td>\n",
              "      <td>-0.407193</td>\n",
              "      <td>0.095921</td>\n",
              "      <td>0.592941</td>\n",
              "      <td>-0.270533</td>\n",
              "      <td>0.817739</td>\n",
              "      <td>...</td>\n",
              "      <td>0.408542</td>\n",
              "      <td>-0.009431</td>\n",
              "      <td>0.798278</td>\n",
              "      <td>-0.137458</td>\n",
              "      <td>0.141267</td>\n",
              "      <td>-0.206010</td>\n",
              "      <td>0.502292</td>\n",
              "      <td>0.219422</td>\n",
              "      <td>0.215153</td>\n",
              "      <td>69.99</td>\n",
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              "      <th>2609</th>\n",
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              "      <td>0.284454</td>\n",
              "      <td>-0.136601</td>\n",
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              "      <td>1.252740</td>\n",
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              "      <td>-0.188196</td>\n",
              "      <td>-0.129143</td>\n",
              "      <td>-0.016091</td>\n",
              "      <td>-0.124864</td>\n",
              "      <td>-0.504412</td>\n",
              "      <td>0.675462</td>\n",
              "      <td>-0.304683</td>\n",
              "      <td>0.005531</td>\n",
              "      <td>0.005172</td>\n",
              "      <td>0.89</td>\n",
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              "    <tr>\n",
              "      <th>2610</th>\n",
              "      <td>3017.0</td>\n",
              "      <td>-0.873406</td>\n",
              "      <td>0.996277</td>\n",
              "      <td>1.370080</td>\n",
              "      <td>1.314848</td>\n",
              "      <td>-0.289889</td>\n",
              "      <td>0.244702</td>\n",
              "      <td>0.136410</td>\n",
              "      <td>0.704062</td>\n",
              "      <td>-0.730132</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.125464</td>\n",
              "      <td>0.095403</td>\n",
              "      <td>0.227194</td>\n",
              "      <td>-0.110924</td>\n",
              "      <td>0.200514</td>\n",
              "      <td>0.049422</td>\n",
              "      <td>-0.215075</td>\n",
              "      <td>0.007172</td>\n",
              "      <td>0.029088</td>\n",
              "      <td>28.06</td>\n",
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              "    <tr>\n",
              "      <th>2611</th>\n",
              "      <td>5822.0</td>\n",
              "      <td>-1.746504</td>\n",
              "      <td>2.336897</td>\n",
              "      <td>2.211292</td>\n",
              "      <td>3.887689</td>\n",
              "      <td>-0.401255</td>\n",
              "      <td>1.462920</td>\n",
              "      <td>-0.853872</td>\n",
              "      <td>-1.090633</td>\n",
              "      <td>-0.109370</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.073322</td>\n",
              "      <td>1.508737</td>\n",
              "      <td>-0.127188</td>\n",
              "      <td>0.188788</td>\n",
              "      <td>-0.087296</td>\n",
              "      <td>-0.365483</td>\n",
              "      <td>0.143746</td>\n",
              "      <td>0.043014</td>\n",
              "      <td>-0.022648</td>\n",
              "      <td>20.64</td>\n",
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              "    <tr>\n",
              "      <th>2612</th>\n",
              "      <td>7559.0</td>\n",
              "      <td>-0.683262</td>\n",
              "      <td>2.184431</td>\n",
              "      <td>0.086991</td>\n",
              "      <td>1.474910</td>\n",
              "      <td>1.195123</td>\n",
              "      <td>-1.304462</td>\n",
              "      <td>1.143837</td>\n",
              "      <td>-0.219464</td>\n",
              "      <td>-0.059003</td>\n",
              "      <td>...</td>\n",
              "      <td>0.041409</td>\n",
              "      <td>-0.228812</td>\n",
              "      <td>-0.484496</td>\n",
              "      <td>-0.463930</td>\n",
              "      <td>0.130512</td>\n",
              "      <td>0.555804</td>\n",
              "      <td>-0.240149</td>\n",
              "      <td>-0.077529</td>\n",
              "      <td>0.137752</td>\n",
              "      <td>0.89</td>\n",
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              "    <tr>\n",
              "      <th>2613</th>\n",
              "      <td>10996.0</td>\n",
              "      <td>1.143699</td>\n",
              "      <td>-0.198893</td>\n",
              "      <td>0.931460</td>\n",
              "      <td>0.288985</td>\n",
              "      <td>-1.000110</td>\n",
              "      <td>-0.652050</td>\n",
              "      <td>-0.579970</td>\n",
              "      <td>-0.012022</td>\n",
              "      <td>1.630406</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.101879</td>\n",
              "      <td>-0.000246</td>\n",
              "      <td>0.115612</td>\n",
              "      <td>-0.009653</td>\n",
              "      <td>0.522929</td>\n",
              "      <td>0.102863</td>\n",
              "      <td>1.002485</td>\n",
              "      <td>-0.104637</td>\n",
              "      <td>-0.000706</td>\n",
              "      <td>39.00</td>\n",
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              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-45ab7f28-a4d1-4906-876f-6128f7a4c73c button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-45ab7f28-a4d1-4906-876f-6128f7a4c73c');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ],
      "source": [
        "test_data = pd.read_csv('fraud_test.csv')\n",
        "test_data"
      ],
      "id": "87165f90"
    },
    {
      "cell_type": "code",
      "source": [
        "train_data.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AeqwyGkFOIZA",
        "outputId": "a680f5bc-2b4a-465e-a5fc-7ee7a842df9d"
      },
      "id": "AeqwyGkFOIZA",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Time      0\n",
              "V1        0\n",
              "V2        0\n",
              "V3        0\n",
              "V4        0\n",
              "V5        0\n",
              "V6        0\n",
              "V7        0\n",
              "V8        0\n",
              "V9        0\n",
              "V10       0\n",
              "V11       0\n",
              "V12       0\n",
              "V13       0\n",
              "V14       0\n",
              "V15       0\n",
              "V16       0\n",
              "V17       0\n",
              "V18       0\n",
              "V19       0\n",
              "V20       0\n",
              "V21       0\n",
              "V22       0\n",
              "V23       0\n",
              "V24       0\n",
              "V25       0\n",
              "V26       0\n",
              "V27       0\n",
              "V28       0\n",
              "Amount    0\n",
              "Class     0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "train_data = train_data.dropna(axis=0, how='all', subset=['Class'])"
      ],
      "metadata": {
        "id": "V6WnmHGUOnGC"
      },
      "id": "V6WnmHGUOnGC",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "train_data.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8atY96SdQK_C",
        "outputId": "950428af-0737-40ab-8754-32f561c28f43"
      },
      "id": "8atY96SdQK_C",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(7840, 31)"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in train_data.columns :\n",
        "  Q1 = train_data[i].quantile(.25)\n",
        "  Q3 = train_data[i].quantile(.75)\n",
        "  IQR = Q3 - Q1\n",
        "  train_data[(train_data[i]> Q1 - (1.5 * IQR)) & (train_data[i]< Q3 + (1.5 * IQR))]"
      ],
      "metadata": {
        "id": "t0Jk0VfePTj2"
      },
      "id": "t0Jk0VfePTj2",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.preprocessing import StandardScaler\n",
        "\n",
        "scaler = StandardScaler()\n",
        "\n",
        "train_data[['Time']] = scaler.fit_transform(train_data[['Time']])\n",
        "train_data[['Amount']] = scaler.fit_transform(train_data[['Amount']])\n",
        "\n",
        "test_data[['Time']] = scaler.fit_transform(test_data[['Time']])\n",
        "test_data[['Amount']] = scaler.fit_transform(test_data[['Amount']])"
      ],
      "metadata": {
        "id": "aJO3MaOEOIhq"
      },
      "id": "aJO3MaOEOIhq",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**mode**"
      ],
      "metadata": {
        "id": "zLPDPy_y8pEG"
      },
      "id": "zLPDPy_y8pEG"
    },
    {
      "cell_type": "code",
      "source": [
        "y=  train_data[['Class']]"
      ],
      "metadata": {
        "id": "Gy6-VPevRHxV"
      },
      "id": "Gy6-VPevRHxV",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x = train_data.copy()\n",
        "x.drop(columns= ['Class'], inplace= True)"
      ],
      "metadata": {
        "id": "Yku3iiuVRH8N"
      },
      "id": "Yku3iiuVRH8N",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "83cca2e5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a894ac2f-eee4-4c9e-d42f-e5b741d890b9"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/sklearn/utils/validation.py:993: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
            "  y = column_or_1d(y, warn=True)\n"
          ]
        }
      ],
      "source": [
        "from sklearn.svm import SVC\n",
        "\n",
        "model = SVC(C=3)\n",
        "model.fit(x, y)\n",
        "y_pred = model.predict(x)"
      ],
      "id": "83cca2e5"
    },
    {
      "cell_type": "markdown",
      "source": [
        "**evaluate the model**"
      ],
      "metadata": {
        "id": "m6iOIh7a8tiu"
      },
      "id": "m6iOIh7a8tiu"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "84fc255b",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b1c58fd3-f3b5-4d05-eb9c-e8f0f9e357f4"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.9997445684236828"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ],
      "source": [
        "# evaluate your model\n",
        "from sklearn.metrics import f1_score, classification_report\n",
        "f1_score(y, y_pred, average='weighted')"
      ],
      "id": "84fc255b"
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "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": "3.8.6"
    },
    "vscode": {
      "interpreter": {
        "hash": "45efbd2215c372e1dad45abd5af7507e40fba3930613cc2a55269c9b505d98e4"
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}