Credit_Card_Fraud_detection.ipynb

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      "source": [
        "import numpy as np\n",
        "import pandas as pd"
      ]
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      "source": [
        "data=pd.read_csv('/content/creditcard.csv')"
      ],
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        "data.head(5)"
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              "   Time        V1        V2        V3        V4        V5        V6        V7  \\\n",
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              "4     2 -1.158233  0.877737  1.548718  0.403034 -0.407193  0.095921  0.592941   \n",
              "\n",
              "         V8        V9  ...       V21       V22       V23       V24       V25  \\\n",
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              "4 -0.270533  0.817739  ... -0.009431  0.798278 -0.137458  0.141267 -0.206010   \n",
              "\n",
              "        V26       V27       V28  Amount  Class  \n",
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            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 27819 entries, 0 to 27818\n",
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            " 14  V14     27818 non-null  float64\n",
            " 15  V15     27818 non-null  float64\n",
            " 16  V16     27818 non-null  float64\n",
            " 17  V17     27818 non-null  float64\n",
            " 18  V18     27818 non-null  float64\n",
            " 19  V19     27818 non-null  float64\n",
            " 20  V20     27818 non-null  float64\n",
            " 21  V21     27818 non-null  float64\n",
            " 22  V22     27818 non-null  float64\n",
            " 23  V23     27818 non-null  float64\n",
            " 24  V24     27818 non-null  float64\n",
            " 25  V25     27818 non-null  float64\n",
            " 26  V26     27818 non-null  float64\n",
            " 27  V27     27818 non-null  float64\n",
            " 28  V28     27818 non-null  float64\n",
            " 29  Amount  27818 non-null  float64\n",
            " 30  Class   27818 non-null  float64\n",
            "dtypes: float64(30), int64(1)\n",
            "memory usage: 6.6 MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "I4RKcIt7GSd5",
        "outputId": "7c3946f2-45a9-473a-ddba-79594e680f5a"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Time      0\n",
              "V1        1\n",
              "V2        1\n",
              "V3        1\n",
              "V4        1\n",
              "V5        1\n",
              "V6        1\n",
              "V7        1\n",
              "V8        1\n",
              "V9        1\n",
              "V10       1\n",
              "V11       1\n",
              "V12       1\n",
              "V13       1\n",
              "V14       1\n",
              "V15       1\n",
              "V16       1\n",
              "V17       1\n",
              "V18       1\n",
              "V19       1\n",
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              "V21       1\n",
              "V22       1\n",
              "V23       1\n",
              "V24       1\n",
              "V25       1\n",
              "V26       1\n",
              "V27       1\n",
              "V28       1\n",
              "Amount    1\n",
              "Class     1\n",
              "dtype: int64"
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              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V20</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V21</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V22</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V23</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V24</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V25</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V26</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V27</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>V28</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amount</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Class</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> int64</label>"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.preprocessing import StandardScaler"
      ],
      "metadata": {
        "id": "52IaarzRGV2V"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sc=StandardScaler()\n",
        "data['Amount']=sc.fit_transform(pd.DataFrame(data['Amount']))"
      ],
      "metadata": {
        "id": "6AA5pyKDGdyo"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 255
        },
        "id": "UH0RZR7TGg23",
        "outputId": "ca5b6edd-e467-4830-b74d-385f7ccc01db"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
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              "2     1 -1.358354 -1.340163  1.773209  0.379780 -0.503198  1.800499  0.791461   \n",
              "3     1 -0.966272 -0.185226  1.792993 -0.863291 -0.010309  1.247203  0.237609   \n",
              "4     2 -1.158233  0.877737  1.548718  0.403034 -0.407193  0.095921  0.592941   \n",
              "\n",
              "         V8        V9  ...       V21       V22       V23       V24       V25  \\\n",
              "0  0.098698  0.363787  ... -0.018307  0.277838 -0.110474  0.066928  0.128539   \n",
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              "4 -0.270533  0.817739  ... -0.009431  0.798278 -0.137458  0.141267 -0.206010   \n",
              "\n",
              "        V26       V27       V28    Amount  Class  \n",
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              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-5b5d8779-3b36-4da4-b916-aac4df3a3f34 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "data"
            }
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data=data.drop(['Time'],axis=1)"
      ],
      "metadata": {
        "id": "7CcehSdKGsab"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "G5u0-8ovGxj-",
        "outputId": "04deebb9-0c97-4829-8a9b-a4201426d949"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(27819, 30)"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.duplicated().any()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rK8k2rOoG1Bg",
        "outputId": "b35cd28b-dd3f-455f-f0cd-720f5e5f73b3"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data=data.drop_duplicates()"
      ],
      "metadata": {
        "id": "AnI_MPDgG6CP"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "W-APIzWZG-a2",
        "outputId": "4c819040-8d85-4a3c-f7c1-1dd1ad327939"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(27111, 30)"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data['Class'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 178
        },
        "id": "gBcm-ekhHAah",
        "outputId": "c1c5a633-7651-4398-8376-0bd0e9a2a1e4"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Class\n",
              "0.0    27017\n",
              "1.0       93\n",
              "Name: count, dtype: int64"
            ],
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Class</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0.0</th>\n",
              "      <td>27017</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1.0</th>\n",
              "      <td>93</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> int64</label>"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import seaborn as sns"
      ],
      "metadata": {
        "id": "0Kwv7oSjHLDE"
      },
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sns.countplot(data['Class'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "id": "MsXmPvy6HSBs",
        "outputId": "d8d88a72-5b29-462f-ee64-cd94139e6459"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: ylabel='count'>"
            ]
          },
          "metadata": {},
          "execution_count": 23
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X = data.drop('Class',axis=1)\n",
        "y = data['Class']"
      ],
      "metadata": {
        "id": "jHiQYO8-HVK5"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.20,random_state=42)\n",
        "\n"
      ],
      "metadata": {
        "id": "_BgVhFQ6HYGV"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "normal = data[data['Class']==0]\n",
        "fraud = data[data['Class']==1]"
      ],
      "metadata": {
        "id": "53M_cXpXHdf_"
      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "normal.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sfPsOmJwHiJf",
        "outputId": "1f6ac979-b89f-4556-f68b-ad9f2f17b550"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(27017, 30)"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fraud.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2g78PQaDHkiE",
        "outputId": "2cc638f7-77db-43da-a75a-addd5be0dcbc"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(93, 30)"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "normal_sample=normal.sample(n=473)"
      ],
      "metadata": {
        "id": "o112FPbFHo0J"
      },
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "normal_sample.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rdIPQmf1HqFQ",
        "outputId": "98d884a8-b47a-4bb4-c372-55d56769dab0"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(473, 30)"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "new_data = pd.concat([normal_sample,fraud],ignore_index=True)"
      ],
      "metadata": {
        "id": "Neoo3gHDHtEo"
      },
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "new_data['Class'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 178
        },
        "id": "jX0X1B0WHvb9",
        "outputId": "1cd5cc04-4306-4956-8196-07a0fd3ea5f4"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Class\n",
              "0.0    473\n",
              "1.0     93\n",
              "Name: count, dtype: int64"
            ],
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Class</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0.0</th>\n",
              "      <td>473</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1.0</th>\n",
              "      <td>93</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> int64</label>"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "new_data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 255
        },
        "id": "TkLePBWBHxko",
        "outputId": "e1c71e0e-1dd9-49e4-ccfc-a28862a55257"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         V1        V2        V3        V4        V5        V6        V7  \\\n",
              "0  1.297209  0.750957 -0.682946  1.147814  0.552670 -0.748080  0.339017   \n",
              "1  1.121093  0.111322  0.498386  1.328600 -0.272976  0.001349 -0.110423   \n",
              "2  1.189598  0.289716  0.516757  0.942567 -0.435072 -0.785810 -0.200526   \n",
              "3  1.047051  0.055205  1.598788  2.944703 -0.837250  0.660946 -0.711426   \n",
              "4  1.146619 -0.466438  0.948458  0.065914 -0.877668  0.447087 -0.932231   \n",
              "\n",
              "         V8        V9       V10  ...       V21       V22       V23       V24  \\\n",
              "0 -0.229265 -0.133449 -0.699750  ... -0.115328 -0.222498 -0.235285 -0.570828   \n",
              "1  0.179641  0.174675  0.077668  ... -0.053130  0.012710 -0.030376  0.216249   \n",
              "2 -0.062029  1.570873 -0.644168  ... -0.409582 -0.993680  0.231981  0.248527   \n",
              "3  0.349164  0.506210  0.353771  ...  0.064240  0.557378 -0.052925  0.442928   \n",
              "4  0.396400  0.891311 -0.134078  ...  0.125968  0.457356 -0.051646 -0.245949   \n",
              "\n",
              "        V25       V26       V27       V28    Amount  Class  \n",
              "0  0.825514 -0.277546  0.038467  0.050407 -0.347362    0.0  \n",
              "1  0.573753 -0.338610  0.030965  0.004415 -0.347362    0.0  \n",
              "2  0.013788  0.071387 -0.045194  0.020543 -0.338302    0.0  \n",
              "3  0.484869  0.224058  0.062520  0.025824 -0.351915    0.0  \n",
              "4  0.156889  0.945173 -0.016843 -0.000678 -0.296372    0.0  \n",
              "\n",
              "[5 rows x 30 columns]"
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>V1</th>\n",
              "      <th>V2</th>\n",
              "      <th>V3</th>\n",
              "      <th>V4</th>\n",
              "      <th>V5</th>\n",
              "      <th>V6</th>\n",
              "      <th>V7</th>\n",
              "      <th>V8</th>\n",
              "      <th>V9</th>\n",
              "      <th>V10</th>\n",
              "      <th>...</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",
              "      <th>Class</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1.297209</td>\n",
              "      <td>0.750957</td>\n",
              "      <td>-0.682946</td>\n",
              "      <td>1.147814</td>\n",
              "      <td>0.552670</td>\n",
              "      <td>-0.748080</td>\n",
              "      <td>0.339017</td>\n",
              "      <td>-0.229265</td>\n",
              "      <td>-0.133449</td>\n",
              "      <td>-0.699750</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.115328</td>\n",
              "      <td>-0.222498</td>\n",
              "      <td>-0.235285</td>\n",
              "      <td>-0.570828</td>\n",
              "      <td>0.825514</td>\n",
              "      <td>-0.277546</td>\n",
              "      <td>0.038467</td>\n",
              "      <td>0.050407</td>\n",
              "      <td>-0.347362</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1.121093</td>\n",
              "      <td>0.111322</td>\n",
              "      <td>0.498386</td>\n",
              "      <td>1.328600</td>\n",
              "      <td>-0.272976</td>\n",
              "      <td>0.001349</td>\n",
              "      <td>-0.110423</td>\n",
              "      <td>0.179641</td>\n",
              "      <td>0.174675</td>\n",
              "      <td>0.077668</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.053130</td>\n",
              "      <td>0.012710</td>\n",
              "      <td>-0.030376</td>\n",
              "      <td>0.216249</td>\n",
              "      <td>0.573753</td>\n",
              "      <td>-0.338610</td>\n",
              "      <td>0.030965</td>\n",
              "      <td>0.004415</td>\n",
              "      <td>-0.347362</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1.189598</td>\n",
              "      <td>0.289716</td>\n",
              "      <td>0.516757</td>\n",
              "      <td>0.942567</td>\n",
              "      <td>-0.435072</td>\n",
              "      <td>-0.785810</td>\n",
              "      <td>-0.200526</td>\n",
              "      <td>-0.062029</td>\n",
              "      <td>1.570873</td>\n",
              "      <td>-0.644168</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.409582</td>\n",
              "      <td>-0.993680</td>\n",
              "      <td>0.231981</td>\n",
              "      <td>0.248527</td>\n",
              "      <td>0.013788</td>\n",
              "      <td>0.071387</td>\n",
              "      <td>-0.045194</td>\n",
              "      <td>0.020543</td>\n",
              "      <td>-0.338302</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1.047051</td>\n",
              "      <td>0.055205</td>\n",
              "      <td>1.598788</td>\n",
              "      <td>2.944703</td>\n",
              "      <td>-0.837250</td>\n",
              "      <td>0.660946</td>\n",
              "      <td>-0.711426</td>\n",
              "      <td>0.349164</td>\n",
              "      <td>0.506210</td>\n",
              "      <td>0.353771</td>\n",
              "      <td>...</td>\n",
              "      <td>0.064240</td>\n",
              "      <td>0.557378</td>\n",
              "      <td>-0.052925</td>\n",
              "      <td>0.442928</td>\n",
              "      <td>0.484869</td>\n",
              "      <td>0.224058</td>\n",
              "      <td>0.062520</td>\n",
              "      <td>0.025824</td>\n",
              "      <td>-0.351915</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1.146619</td>\n",
              "      <td>-0.466438</td>\n",
              "      <td>0.948458</td>\n",
              "      <td>0.065914</td>\n",
              "      <td>-0.877668</td>\n",
              "      <td>0.447087</td>\n",
              "      <td>-0.932231</td>\n",
              "      <td>0.396400</td>\n",
              "      <td>0.891311</td>\n",
              "      <td>-0.134078</td>\n",
              "      <td>...</td>\n",
              "      <td>0.125968</td>\n",
              "      <td>0.457356</td>\n",
              "      <td>-0.051646</td>\n",
              "      <td>-0.245949</td>\n",
              "      <td>0.156889</td>\n",
              "      <td>0.945173</td>\n",
              "      <td>-0.016843</td>\n",
              "      <td>-0.000678</td>\n",
              "      <td>-0.296372</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 30 columns</p>\n",
              "</div>\n",
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              "      padding: 0 0 0 0;\n",
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "        document.querySelector('#df-ed149edb-84ca-4ffc-ab1f-a1a0e69e4c85 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-ed149edb-84ca-4ffc-ab1f-a1a0e69e4c85');\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",
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              "\n",
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              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
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              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-ddd8ed69-7e49-4f95-8a60-c53746b0ab08 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "new_data"
            }
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X = new_data.drop('Class',axis=1)\n",
        "y = new_data['Class']"
      ],
      "metadata": {
        "id": "GfQ3YI4MHzi3"
      },
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.20,random_state=42)\n",
        ""
      ],
      "metadata": {
        "id": "sMbWngXoH2C5"
      },
      "execution_count": 35,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.ensemble import RandomForestClassifier\n",
        "rf = RandomForestClassifier()\n",
        "rf.fit(X_train,y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 80
        },
        "id": "Kij27voyH8hL",
        "outputId": "55554e4e-66d0-47eb-bc0b-c733745b9e0c"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "RandomForestClassifier()"
            ],
            "text/html": [
              "<style>#sk-container-id-1 {\n",
              "  /* Definition of color scheme common for light and dark mode */\n",
              "  --sklearn-color-text: black;\n",
              "  --sklearn-color-line: gray;\n",
              "  /* Definition of color scheme for unfitted estimators */\n",
              "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
              "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
              "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
              "  --sklearn-color-unfitted-level-3: chocolate;\n",
              "  /* Definition of color scheme for fitted estimators */\n",
              "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
              "  --sklearn-color-fitted-level-1: #d4ebff;\n",
              "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
              "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
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              "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
              "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
              "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
              "  --sklearn-color-icon: #696969;\n",
              "\n",
              "  @media (prefers-color-scheme: dark) {\n",
              "    /* Redefinition of color scheme for dark theme */\n",
              "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
              "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
              "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
              "    --sklearn-color-icon: #878787;\n",
              "  }\n",
              "}\n",
              "\n",
              "#sk-container-id-1 {\n",
              "  color: var(--sklearn-color-text);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 pre {\n",
              "  padding: 0;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 input.sk-hidden--visually {\n",
              "  border: 0;\n",
              "  clip: rect(1px 1px 1px 1px);\n",
              "  clip: rect(1px, 1px, 1px, 1px);\n",
              "  height: 1px;\n",
              "  margin: -1px;\n",
              "  overflow: hidden;\n",
              "  padding: 0;\n",
              "  position: absolute;\n",
              "  width: 1px;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-dashed-wrapped {\n",
              "  border: 1px dashed var(--sklearn-color-line);\n",
              "  margin: 0 0.4em 0.5em 0.4em;\n",
              "  box-sizing: border-box;\n",
              "  padding-bottom: 0.4em;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-container {\n",
              "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
              "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
              "     so we also need the `!important` here to be able to override the\n",
              "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
              "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
              "  display: inline-block !important;\n",
              "  position: relative;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-text-repr-fallback {\n",
              "  display: none;\n",
              "}\n",
              "\n",
              "div.sk-parallel-item,\n",
              "div.sk-serial,\n",
              "div.sk-item {\n",
              "  /* draw centered vertical line to link estimators */\n",
              "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
              "  background-size: 2px 100%;\n",
              "  background-repeat: no-repeat;\n",
              "  background-position: center center;\n",
              "}\n",
              "\n",
              "/* Parallel-specific style estimator block */\n",
              "\n",
              "#sk-container-id-1 div.sk-parallel-item::after {\n",
              "  content: \"\";\n",
              "  width: 100%;\n",
              "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
              "  flex-grow: 1;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-parallel {\n",
              "  display: flex;\n",
              "  align-items: stretch;\n",
              "  justify-content: center;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "  position: relative;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-parallel-item {\n",
              "  display: flex;\n",
              "  flex-direction: column;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
              "  align-self: flex-end;\n",
              "  width: 50%;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
              "  align-self: flex-start;\n",
              "  width: 50%;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
              "  width: 0;\n",
              "}\n",
              "\n",
              "/* Serial-specific style estimator block */\n",
              "\n",
              "#sk-container-id-1 div.sk-serial {\n",
              "  display: flex;\n",
              "  flex-direction: column;\n",
              "  align-items: center;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "  padding-right: 1em;\n",
              "  padding-left: 1em;\n",
              "}\n",
              "\n",
              "\n",
              "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
              "clickable and can be expanded/collapsed.\n",
              "- Pipeline and ColumnTransformer use this feature and define the default style\n",
              "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
              "*/\n",
              "\n",
              "/* Pipeline and ColumnTransformer style (default) */\n",
              "\n",
              "#sk-container-id-1 div.sk-toggleable {\n",
              "  /* Default theme specific background. It is overwritten whether we have a\n",
              "  specific estimator or a Pipeline/ColumnTransformer */\n",
              "  background-color: var(--sklearn-color-background);\n",
              "}\n",
              "\n",
              "/* Toggleable label */\n",
              "#sk-container-id-1 label.sk-toggleable__label {\n",
              "  cursor: pointer;\n",
              "  display: block;\n",
              "  width: 100%;\n",
              "  margin-bottom: 0;\n",
              "  padding: 0.5em;\n",
              "  box-sizing: border-box;\n",
              "  text-align: center;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
              "  /* Arrow on the left of the label */\n",
              "  content: \"▸\";\n",
              "  float: left;\n",
              "  margin-right: 0.25em;\n",
              "  color: var(--sklearn-color-icon);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
              "  color: var(--sklearn-color-text);\n",
              "}\n",
              "\n",
              "/* Toggleable content - dropdown */\n",
              "\n",
              "#sk-container-id-1 div.sk-toggleable__content {\n",
              "  max-height: 0;\n",
              "  max-width: 0;\n",
              "  overflow: hidden;\n",
              "  text-align: left;\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-toggleable__content pre {\n",
              "  margin: 0.2em;\n",
              "  border-radius: 0.25em;\n",
              "  color: var(--sklearn-color-text);\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
              "  /* Expand drop-down */\n",
              "  max-height: 200px;\n",
              "  max-width: 100%;\n",
              "  overflow: auto;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
              "  content: \"▾\";\n",
              "}\n",
              "\n",
              "/* Pipeline/ColumnTransformer-specific style */\n",
              "\n",
              "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
              "  color: var(--sklearn-color-text);\n",
              "  background-color: var(--sklearn-color-unfitted-level-2);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
              "  background-color: var(--sklearn-color-fitted-level-2);\n",
              "}\n",
              "\n",
              "/* Estimator-specific style */\n",
              "\n",
              "/* Colorize estimator box */\n",
              "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-2);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-2);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
              "#sk-container-id-1 div.sk-label label {\n",
              "  /* The background is the default theme color */\n",
              "  color: var(--sklearn-color-text-on-default-background);\n",
              "}\n",
              "\n",
              "/* On hover, darken the color of the background */\n",
              "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
              "  color: var(--sklearn-color-text);\n",
              "  background-color: var(--sklearn-color-unfitted-level-2);\n",
              "}\n",
              "\n",
              "/* Label box, darken color on hover, fitted */\n",
              "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
              "  color: var(--sklearn-color-text);\n",
              "  background-color: var(--sklearn-color-fitted-level-2);\n",
              "}\n",
              "\n",
              "/* Estimator label */\n",
              "\n",
              "#sk-container-id-1 div.sk-label label {\n",
              "  font-family: monospace;\n",
              "  font-weight: bold;\n",
              "  display: inline-block;\n",
              "  line-height: 1.2em;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-label-container {\n",
              "  text-align: center;\n",
              "}\n",
              "\n",
              "/* Estimator-specific */\n",
              "#sk-container-id-1 div.sk-estimator {\n",
              "  font-family: monospace;\n",
              "  border: 1px dotted var(--sklearn-color-border-box);\n",
              "  border-radius: 0.25em;\n",
              "  box-sizing: border-box;\n",
              "  margin-bottom: 0.5em;\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-estimator.fitted {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-0);\n",
              "}\n",
              "\n",
              "/* on hover */\n",
              "#sk-container-id-1 div.sk-estimator:hover {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-2);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-2);\n",
              "}\n",
              "\n",
              "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
              "\n",
              "/* Common style for \"i\" and \"?\" */\n",
              "\n",
              ".sk-estimator-doc-link,\n",
              "a:link.sk-estimator-doc-link,\n",
              "a:visited.sk-estimator-doc-link {\n",
              "  float: right;\n",
              "  font-size: smaller;\n",
              "  line-height: 1em;\n",
              "  font-family: monospace;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "  border-radius: 1em;\n",
              "  height: 1em;\n",
              "  width: 1em;\n",
              "  text-decoration: none !important;\n",
              "  margin-left: 1ex;\n",
              "  /* unfitted */\n",
              "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
              "  color: var(--sklearn-color-unfitted-level-1);\n",
              "}\n",
              "\n",
              ".sk-estimator-doc-link.fitted,\n",
              "a:link.sk-estimator-doc-link.fitted,\n",
              "a:visited.sk-estimator-doc-link.fitted {\n",
              "  /* fitted */\n",
              "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
              "  color: var(--sklearn-color-fitted-level-1);\n",
              "}\n",
              "\n",
              "/* On hover */\n",
              "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
              ".sk-estimator-doc-link:hover,\n",
              "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
              ".sk-estimator-doc-link:hover {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-3);\n",
              "  color: var(--sklearn-color-background);\n",
              "  text-decoration: none;\n",
              "}\n",
              "\n",
              "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
              ".sk-estimator-doc-link.fitted:hover,\n",
              "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
              ".sk-estimator-doc-link.fitted:hover {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-3);\n",
              "  color: var(--sklearn-color-background);\n",
              "  text-decoration: none;\n",
              "}\n",
              "\n",
              "/* Span, style for the box shown on hovering the info icon */\n",
              ".sk-estimator-doc-link span {\n",
              "  display: none;\n",
              "  z-index: 9999;\n",
              "  position: relative;\n",
              "  font-weight: normal;\n",
              "  right: .2ex;\n",
              "  padding: .5ex;\n",
              "  margin: .5ex;\n",
              "  width: min-content;\n",
              "  min-width: 20ex;\n",
              "  max-width: 50ex;\n",
              "  color: var(--sklearn-color-text);\n",
              "  box-shadow: 2pt 2pt 4pt #999;\n",
              "  /* unfitted */\n",
              "  background: var(--sklearn-color-unfitted-level-0);\n",
              "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
              "}\n",
              "\n",
              ".sk-estimator-doc-link.fitted span {\n",
              "  /* fitted */\n",
              "  background: var(--sklearn-color-fitted-level-0);\n",
              "  border: var(--sklearn-color-fitted-level-3);\n",
              "}\n",
              "\n",
              ".sk-estimator-doc-link:hover span {\n",
              "  display: block;\n",
              "}\n",
              "\n",
              "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
              "\n",
              "#sk-container-id-1 a.estimator_doc_link {\n",
              "  float: right;\n",
              "  font-size: 1rem;\n",
              "  line-height: 1em;\n",
              "  font-family: monospace;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "  border-radius: 1rem;\n",
              "  height: 1rem;\n",
              "  width: 1rem;\n",
              "  text-decoration: none;\n",
              "  /* unfitted */\n",
              "  color: var(--sklearn-color-unfitted-level-1);\n",
              "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
              "  /* fitted */\n",
              "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
              "  color: var(--sklearn-color-fitted-level-1);\n",
              "}\n",
              "\n",
              "/* On hover */\n",
              "#sk-container-id-1 a.estimator_doc_link:hover {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-3);\n",
              "  color: var(--sklearn-color-background);\n",
              "  text-decoration: none;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-3);\n",
              "}\n",
              "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomForestClassifier()</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 fitted 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 fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;RandomForestClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.RandomForestClassifier.html\">?<span>Documentation for RandomForestClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>RandomForestClassifier()</pre></div> </div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred = rf.predict(X_test)"
      ],
      "metadata": {
        "id": "AnumzM68H-9O"
      },
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import accuracy_score"
      ],
      "metadata": {
        "id": "XiqDR_qtI-Uo"
      },
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "accuracy_score(y_test,y_pred)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9cQiP37sIBLx",
        "outputId": "45992369-ae36-42a0-bc6e-cb296a3218bd"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.9824561403508771"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import precision_score,recall_score,f1_score"
      ],
      "metadata": {
        "id": "0pC5hHftJK_t"
      },
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "precision_score(y_test,y_pred)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Mdoy3l5cIbep",
        "outputId": "66def16a-499c-4912-9131-ad5a73a8dd4e"
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1.0"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "recall_score(y_test,y_pred)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YSzXllNiIdc6",
        "outputId": "fb21c842-d6bf-4126-e2ab-3e53125fecd0"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.8888888888888888"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "-or4mkT2JNkm"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}