credit card scam detection.ipynb

{
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  "metadata": {
    "colab": {
      "name": "ADS Experential learning 2.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "v4LOIeHFvmOV"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Tv0cJv46gLlP"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "127tS6pbgSd0"
      },
      "source": [
        "from sklearn.model_selection import train_test_split, cross_val_score\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.preprocessing import StandardScaler"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wVLTJSlUyYtK",
        "outputId": "668eab24-c751-4ecc-fadf-0638f9cdb70f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 226
        }
      },
      "source": [
        "df=pd.read_csv(\"/content/default of credit card clients.csv\")\n",
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ID</th>\n",
              "      <th>LIMIT_BAL</th>\n",
              "      <th>SEX</th>\n",
              "      <th>EDUCATION</th>\n",
              "      <th>MARRIAGE</th>\n",
              "      <th>AGE</th>\n",
              "      <th>PAY_1</th>\n",
              "      <th>PAY_2</th>\n",
              "      <th>PAY_3</th>\n",
              "      <th>PAY_4</th>\n",
              "      <th>PAY_5</th>\n",
              "      <th>PAY_6</th>\n",
              "      <th>BILL_AMT1</th>\n",
              "      <th>BILL_AMT2</th>\n",
              "      <th>BILL_AMT3</th>\n",
              "      <th>BILL_AMT4</th>\n",
              "      <th>BILL_AMT5</th>\n",
              "      <th>BILL_AMT6</th>\n",
              "      <th>PAY_AMT1</th>\n",
              "      <th>PAY_AMT2</th>\n",
              "      <th>PAY_AMT3</th>\n",
              "      <th>PAY_AMT4</th>\n",
              "      <th>PAY_AMT5</th>\n",
              "      <th>PAY_AMT6</th>\n",
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              "      <td>3</td>\n",
              "      <td>90000</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>34</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>29239</td>\n",
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            ],
            "text/plain": [
              "   ID  LIMIT_BAL  SEX  EDUCATION  ...  PAY_AMT4  PAY_AMT5  PAY_AMT6  dpnm\n",
              "0   1      20000    2          2  ...         0         0         0     1\n",
              "1   2     120000    2          2  ...      1000         0      2000     1\n",
              "2   3      90000    2          2  ...      1000      1000      5000     0\n",
              "3   4      50000    2          2  ...      1100      1069      1000     0\n",
              "4   5      50000    1          2  ...      9000       689       679     0\n",
              "\n",
              "[5 rows x 25 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GIme6nDCeFFM"
      },
      "source": [
        "original=df#to preserve the original data frame "
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_Fy2lLUNcVaR",
        "outputId": "af858384-ff53-4ecc-dcfd-c31c8182531d",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "df.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(30000, 25)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XP_zQGbddRoC"
      },
      "source": [
        "By shape of the data frame we can understand that there are 25 features(23 features, 1 label, 1 id) and there are 30,000 observations."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "h02sh-u7WQKg",
        "outputId": "d7f6cf4f-c4fc-48cf-d347-dba8194e2f98",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "df.info()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 30000 entries, 0 to 29999\n",
            "Data columns (total 25 columns):\n",
            " #   Column     Non-Null Count  Dtype\n",
            "---  ------     --------------  -----\n",
            " 0   ID         30000 non-null  int64\n",
            " 1   LIMIT_BAL  30000 non-null  int64\n",
            " 2   SEX        30000 non-null  int64\n",
            " 3   EDUCATION  30000 non-null  int64\n",
            " 4   MARRIAGE   30000 non-null  int64\n",
            " 5   AGE        30000 non-null  int64\n",
            " 6   PAY_1      30000 non-null  int64\n",
            " 7   PAY_2      30000 non-null  int64\n",
            " 8   PAY_3      30000 non-null  int64\n",
            " 9   PAY_4      30000 non-null  int64\n",
            " 10  PAY_5      30000 non-null  int64\n",
            " 11  PAY_6      30000 non-null  int64\n",
            " 12  BILL_AMT1  30000 non-null  int64\n",
            " 13  BILL_AMT2  30000 non-null  int64\n",
            " 14  BILL_AMT3  30000 non-null  int64\n",
            " 15  BILL_AMT4  30000 non-null  int64\n",
            " 16  BILL_AMT5  30000 non-null  int64\n",
            " 17  BILL_AMT6  30000 non-null  int64\n",
            " 18  PAY_AMT1   30000 non-null  int64\n",
            " 19  PAY_AMT2   30000 non-null  int64\n",
            " 20  PAY_AMT3   30000 non-null  int64\n",
            " 21  PAY_AMT4   30000 non-null  int64\n",
            " 22  PAY_AMT5   30000 non-null  int64\n",
            " 23  PAY_AMT6   30000 non-null  int64\n",
            " 24  dpnm       30000 non-null  int64\n",
            "dtypes: int64(25)\n",
            "memory usage: 5.7 MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Xsk1PUedeNsq",
        "outputId": "72f416a8-bdca-4f95-8876-58015bf96731",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "df.isna().sum().sum()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VnxXMbpOgbHK"
      },
      "source": [
        "no Nan or null values so data is complete."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AoJt29KJcoue"
      },
      "source": [
        "df.drop(\"ID\",axis=1,inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "I3zvS4gfcxou"
      },
      "source": [
        "removing non contributing factors like name id is priliminary step so dropping id column."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yhY1e6OB4Bq5",
        "outputId": "3f365f2e-680a-4733-d438-23b32e1a321b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 934
        }
      },
      "source": [
        "plt.figure(figsize=(20,15))\n",
        "sns.heatmap(df.corr(),annot=True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa30ba2beb8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x1080 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cNPL5rUo5Uis"
      },
      "source": [
        "bill amounts and pay attributes are highly related. So to prevent multi collinearity higly related attributes can be dropped. But even they are prportional we can let them be as they may have some hidden inferential feature in classification point of view."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dn_75t7j6IHU",
        "outputId": "3ac104b4-c456-4c0d-80ae-38da3cb2839d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        }
      },
      "source": [
        "sns.countplot(x='SEX',hue='dpnm',data=df)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa0d963fb00>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 65
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lTS7LJwq7XAz"
      },
      "source": [
        "1 - Male, 2- Female we can infer that higher percentage of men dont pay the credit card bills"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jUv8SS187vEQ",
        "outputId": "20cbb1f2-e94c-4c71-82c9-7f38668a04f8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        }
      },
      "source": [
        "sns.countplot(x='EDUCATION',hue='dpnm',data=df)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa0d94f6b38>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 66
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YYa7eV1j7-nY"
      },
      "source": [
        "education dosent tell much as at every level it relatively same"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KHrC4boN8HxC",
        "outputId": "c2a9ee7d-dc69-4299-cf89-f67366ec71d7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        }
      },
      "source": [
        "sns.countplot(x='MARRIAGE',hue='dpnm',data=df)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa0d7bffda0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 67
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NnvRoNeE8RK6"
      },
      "source": [
        "1- married, 2- single, 3- others, by the above plot we can say that higher percent of married people are not able to pay their credit bills back."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ao-m3UQpxM4h",
        "outputId": "ee2cd84a-5ccd-435f-d28d-f8709dc34e5c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 308
        }
      },
      "source": [
        "sns.violinplot(y=\"LIMIT_BAL\",x=\"dpnm\",data=df)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa30a9a4550>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 44
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zpc_KX-ByVqR"
      },
      "source": [
        "we can say that debts of smaller amounts are not paid compared to debts of higher amount."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VUdAX5h00T0g",
        "outputId": "75d718a4-fdea-47ec-8a25-0126f1b380de",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        }
      },
      "source": [
        "sns.violinplot(y=\"AGE\",x=\"dpnm\",data=df)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa30a849668>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "W1LxFaqi0gaI"
      },
      "source": [
        "younger people are more likely to keep bill dues than the elder one's."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DnWoMN2O23zQ",
        "outputId": "603800a1-04cf-4fe4-e79c-fa36466190c9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "fig = plt.figure(figsize = (15,20))\n",
        "ax = fig.gca()\n",
        "df.hist(ax = ax)\n",
        "plt.show()"
      ],
      "execution_count": 78,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:3: UserWarning: To output multiple subplots, the figure containing the passed axes is being cleared\n",
            "  This is separate from the ipykernel package so we can avoid doing imports until\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x1440 with 25 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "B5fx8AEe3MLM"
      },
      "source": [
        "1. only less than 30% of the people wont be able to pay the debt(default).\n",
        "2. all pay attributes have a peak at 1 which means most of the payments are done with a due of one month.\n",
        "3. \n",
        "we can observe unbalenced features and the wide range of values. which needs to be dealed."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gD0JZRKCWS2a"
      },
      "source": [
        "df.drop_duplicates(inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ERTQcZxTdoRz"
      },
      "source": [
        "As id is dropped similar data can be matched as there is no primary key now we can remove redundant info which adds no value in the training process. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7rGYiUQn06Xn",
        "outputId": "dba33e26-bbe8-47f1-d4d8-583065e0bec2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "df.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['LIMIT_BAL', 'SEX', 'EDUCATION', 'MARRIAGE', 'AGE', 'PAY_1', 'PAY_2',\n",
              "       'PAY_3', 'PAY_4', 'PAY_5', 'PAY_6', 'BILL_AMT1', 'BILL_AMT2',\n",
              "       'BILL_AMT3', 'BILL_AMT4', 'BILL_AMT5', 'BILL_AMT6', 'PAY_AMT1',\n",
              "       'PAY_AMT2', 'PAY_AMT3', 'PAY_AMT4', 'PAY_AMT5', 'PAY_AMT6', 'dpnm'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jkbzpNgZ37QW"
      },
      "source": [
        "there are many categorical features but only few are hot encoded beacause other attributes have wide range of discrete values which can be interpreted as real values."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J9kIceYYHp1I"
      },
      "source": [
        "df[[\"SEX\",\"MARRIAGE\"]]=df[[\"SEX\",\"MARRIAGE\"]].astype(str)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n90uoQiVHqAI"
      },
      "source": [
        "df1=pd.get_dummies(df,drop_first=True)"
      ],
      "execution_count": 91,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RMo3LDXxI-vS"
      },
      "source": [
        "scaling is a very important as learning rate is same for all features, data in large scale needs to be less sensitive and data in small range needs to be more sensitive so to deal with this we need to scale the data."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AWfBw1nA5wFD"
      },
      "source": [
        "from sklearn import preprocessing"
      ],
      "execution_count": 90,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TouAtKFEIIlA"
      },
      "source": [
        "X=df1\n",
        "Y=df1[\"dpnm\"]\n",
        "X=X.drop(\"dpnm\",axis=1)"
      ],
      "execution_count": 92,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5aD0d50oIhgi"
      },
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.3, random_state=25)"
      ],
      "execution_count": 93,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZY4StzBds66Y",
        "outputId": "ad6cc218-8d5a-46d8-bd6b-30349874c106",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "X_train=preprocessing.scale(X_train)\n",
        "X_test=preprocessing.scale(X_test)\n",
        "X_test"
      ],
      "execution_count": 95,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 0.24590725,  0.17473981, -0.71522554, ..., -0.94064699,\n",
              "         0.96398156, -0.10162576],\n",
              "       [-0.06278197, -1.08742573,  0.37850298, ..., -0.94064699,\n",
              "         0.96398156, -0.10162576],\n",
              "       [-1.06602194,  0.17473981, -0.16836128, ...,  1.06309807,\n",
              "        -1.03736424, -0.10162576],\n",
              "       ...,\n",
              "       [ 0.01439034,  0.17473981,  1.0347401 , ..., -0.94064699,\n",
              "         0.96398156, -0.10162576],\n",
              "       [ 1.09480262,  0.17473981, -0.05898843, ..., -0.94064699,\n",
              "         0.96398156, -0.10162576],\n",
              "       [-1.14319425,  0.17473981, -1.15271695, ..., -0.94064699,\n",
              "         0.96398156, -0.10162576]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 95
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nq7lTjSTQl4S"
      },
      "source": [
        "# Logistic Regression: model1"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Kh3gxK4JHpDV",
        "outputId": "fc1e8540-bf45-4bcd-867c-e8e90ae7cd2f",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "model1=LogisticRegression()\n",
        "model1.fit(X_train,y_train)"
      ],
      "execution_count": 96,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
              "                   intercept_scaling=1, l1_ratio=None, max_iter=100,\n",
              "                   multi_class='auto', n_jobs=None, penalty='l2',\n",
              "                   random_state=None, solver='lbfgs', tol=0.0001, verbose=0,\n",
              "                   warm_start=False)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 96
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V07e0sdDpmNP",
        "outputId": "a7bc3f0a-4adc-49ad-8e83-e2d4e13b88fe",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "model1.score(X_test,y_test)"
      ],
      "execution_count": 97,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.8103333333333333"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 97
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XmwrV-EZUq3D"
      },
      "source": [
        "score=cross_val_score(model1, X_train, y_train, cv=5).mean()"
      ],
      "execution_count": 98,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "djG9pmOKpFzE",
        "outputId": "54e58e9e-a843-4b9f-cda5-bee7317531c1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "score"
      ],
      "execution_count": 99,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.8115238095238094"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 99
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Iz7-3ob0pOtY",
        "outputId": "3d0d2237-bea9-4131-f8d4-aa272e4f8163",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "from sklearn.metrics import confusion_matrix\n",
        "conMatrix = confusion_matrix(y_test,model1.predict(X_test))\n",
        "conMatrix"
      ],
      "execution_count": 100,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[6800,  186],\n",
              "       [1521,  493]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 100
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yR4wR-gSquOf"
      },
      "source": [
        "we can see 1521 in (1,0) position which a not a very good sign which means our model is not much predicting positive for actually positive terms. The count is comparitively high so it will be better if further decreased."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UlgXzZNXVE7f",
        "outputId": "f0cd5e78-bd42-455c-fc22-7cd6847ccf03",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "print(\"correct predictions:\",conMatrix[0,0]+conMatrix[1,1])\n",
        "print(\"wrong predictions:\",conMatrix[0,1]+conMatrix[1,0])"
      ],
      "execution_count": 101,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "correct predictions: 7293\n",
            "wrong predictions: 1707\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0pprCvYuqUe1",
        "outputId": "1257e9e6-c91e-4de6-c929-b336a89e0b0c",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "model1.coef_"
      ],
      "execution_count": 105,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[-7.96917682e-02, -7.11453248e-02,  5.53872602e-02,\n",
              "         6.56486022e-01,  9.41416506e-02,  6.19855066e-02,\n",
              "         3.98676893e-02,  4.77860462e-02,  6.61138443e-03,\n",
              "        -4.12481649e-01,  2.00534868e-01, -3.36034825e-02,\n",
              "         1.02905274e-01,  3.84631918e-02,  2.72060807e-04,\n",
              "        -2.94903943e-01, -2.24637847e-01, -6.51439711e-02,\n",
              "        -3.70236573e-02, -3.84197847e-02, -4.65002506e-02,\n",
              "        -5.12693710e-02,  4.87371604e-01,  4.00065220e-01,\n",
              "         1.06626664e-01]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 105
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NcQYpcTorsNc"
      },
      "source": [
        "Observations:\n",
        "we can see that in |coef| none of the coef are comparitively very small so all are contributing to the model except 2.72060807e-04 so its clear that feature of this coefficient is not contributing much so can be dropped."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rCQ7GyqhvYEJ"
      },
      "source": [
        "# Decision Tree: model2"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KhgajajaKCQZ"
      },
      "source": [
        "from sklearn import tree\n",
        "import graphviz "
      ],
      "execution_count": 106,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gtSLRfI2t2P_",
        "outputId": "35ef2ea7-29ad-4c09-d6fb-ee1c4c3bc604",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "model2= tree.DecisionTreeClassifier(max_depth=4, criterion='gini', random_state=25)\n",
        "model2.fit(X_train, y_train)"
      ],
      "execution_count": 107,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\n",
              "                       max_depth=4, max_features=None, max_leaf_nodes=None,\n",
              "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
              "                       min_samples_leaf=1, min_samples_split=2,\n",
              "                       min_weight_fraction_leaf=0.0, presort='deprecated',\n",
              "                       random_state=25, splitter='best')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 107
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Etar88ODJz7U",
        "outputId": "08f0c51d-2eb1-43c8-c3d3-e182cb94202e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 677
        }
      },
      "source": [
        "dot_data = tree.export_graphviz(model2, out_file=None, feature_names=X.columns, filled=True, rounded=True, special_characters=True)  \n",
        "graph = graphviz.Source(dot_data)  \n",
        "graph "
      ],
      "execution_count": 108,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<graphviz.files.Source at 0x7fa307f32cc0>"
            ],
            "image/svg+xml": "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<!-- Generated by graphviz version 2.40.1 (20161225.0304)\n -->\n<!-- Title: Tree Pages: 1 -->\n<svg width=\"2260pt\" height=\"477pt\"\n viewBox=\"0.00 0.00 2260.00 477.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 473)\">\n<title>Tree</title>\n<polygon fill=\"#ffffff\" stroke=\"transparent\" points=\"-4,4 -4,-473 2256,-473 2256,4 -4,4\"/>\n<!-- 0 -->\n<g id=\"node1\" class=\"node\">\n<title>0</title>\n<path fill=\"#eca571\" stroke=\"#000000\" d=\"M1235.5,-469C1235.5,-469 1102.5,-469 1102.5,-469 1096.5,-469 1090.5,-463 1090.5,-457 1090.5,-457 1090.5,-413 1090.5,-413 1090.5,-407 1096.5,-401 1102.5,-401 1102.5,-401 1235.5,-401 1235.5,-401 1241.5,-401 1247.5,-407 1247.5,-413 1247.5,-413 1247.5,-457 1247.5,-457 1247.5,-463 1241.5,-469 1235.5,-469\"/>\n<text text-anchor=\"start\" x=\"1120.5\" y=\"-453.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">PAY_1 ≤ 1.358</text>\n<text text-anchor=\"start\" x=\"1131\" y=\"-438.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.343</text>\n<text text-anchor=\"start\" x=\"1113\" y=\"-423.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 21000</text>\n<text text-anchor=\"start\" x=\"1098.5\" y=\"-408.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [16378, 4622]</text>\n</g>\n<!-- 1 -->\n<g id=\"node2\" class=\"node\">\n<title>1</title>\n<path fill=\"#ea9a60\" stroke=\"#000000\" d=\"M973.5,-365C973.5,-365 840.5,-365 840.5,-365 834.5,-365 828.5,-359 828.5,-353 828.5,-353 828.5,-309 828.5,-309 828.5,-303 834.5,-297 840.5,-297 840.5,-297 973.5,-297 973.5,-297 979.5,-297 985.5,-303 985.5,-309 985.5,-309 985.5,-353 985.5,-353 985.5,-359 979.5,-365 973.5,-365\"/>\n<text text-anchor=\"start\" x=\"858.5\" y=\"-349.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">PAY_2 ≤ 1.373</text>\n<text text-anchor=\"start\" x=\"869\" y=\"-334.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.275</text>\n<text text-anchor=\"start\" x=\"851\" y=\"-319.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 18826</text>\n<text text-anchor=\"start\" x=\"836.5\" y=\"-304.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [15723, 3103]</text>\n</g>\n<!-- 0&#45;&gt;1 -->\n<g id=\"edge1\" class=\"edge\">\n<title>0&#45;&gt;1</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1090.3914,-403.7966C1060.3396,-391.8676 1025.8837,-378.1905 995.0106,-365.9355\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"996.139,-362.6178 985.5532,-362.1814 993.5564,-369.124 996.139,-362.6178\"/>\n<text text-anchor=\"middle\" x=\"995.4617\" y=\"-381.434\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">True</text>\n</g>\n<!-- 16 -->\n<g id=\"node17\" class=\"node\">\n<title>16</title>\n<path fill=\"#8ec7f0\" stroke=\"#000000\" d=\"M1519,-365C1519,-365 1403,-365 1403,-365 1397,-365 1391,-359 1391,-353 1391,-353 1391,-309 1391,-309 1391,-303 1397,-297 1403,-297 1403,-297 1519,-297 1519,-297 1525,-297 1531,-303 1531,-309 1531,-309 1531,-353 1531,-353 1531,-359 1525,-365 1519,-365\"/>\n<text text-anchor=\"start\" x=\"1412.5\" y=\"-349.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">PAY_5 ≤ 1.119</text>\n<text text-anchor=\"start\" x=\"1423\" y=\"-334.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.421</text>\n<text text-anchor=\"start\" x=\"1409\" y=\"-319.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 2174</text>\n<text text-anchor=\"start\" x=\"1399\" y=\"-304.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [655, 1519]</text>\n</g>\n<!-- 0&#45;&gt;16 -->\n<g id=\"edge16\" class=\"edge\">\n<title>0&#45;&gt;16</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1247.6348,-406.9931C1289.0065,-392.258 1339.6214,-374.2307 1381.1692,-359.4329\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"1382.4586,-362.6891 1390.7046,-356.0367 1380.1099,-356.0949 1382.4586,-362.6891\"/>\n<text text-anchor=\"middle\" x=\"1379.9828\" y=\"-374.9209\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">False</text>\n</g>\n<!-- 2 -->\n<g id=\"node3\" class=\"node\">\n<title>2</title>\n<path fill=\"#e9965a\" stroke=\"#000000\" d=\"M539.5,-261C539.5,-261 406.5,-261 406.5,-261 400.5,-261 394.5,-255 394.5,-249 394.5,-249 394.5,-205 394.5,-205 394.5,-199 400.5,-193 406.5,-193 406.5,-193 539.5,-193 539.5,-193 545.5,-193 551.5,-199 551.5,-205 551.5,-205 551.5,-249 551.5,-249 551.5,-255 545.5,-261 539.5,-261\"/>\n<text text-anchor=\"start\" x=\"407\" y=\"-245.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">PAY_AMT2 ≤ &#45;0.178</text>\n<text text-anchor=\"start\" x=\"435\" y=\"-230.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.245</text>\n<text text-anchor=\"start\" x=\"417\" y=\"-215.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 17247</text>\n<text text-anchor=\"start\" x=\"402.5\" y=\"-200.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [14783, 2464]</text>\n</g>\n<!-- 1&#45;&gt;2 -->\n<g id=\"edge2\" class=\"edge\">\n<title>1&#45;&gt;2</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M828.4059,-312.1664C753.2109,-294.1473 639.9613,-267.0092 561.599,-248.2311\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"562.2819,-244.7957 551.7415,-245.8689 560.6506,-251.603 562.2819,-244.7957\"/>\n</g>\n<!-- 9 -->\n<g id=\"node10\" class=\"node\">\n<title>9</title>\n<path fill=\"#f7d7c0\" stroke=\"#000000\" d=\"M967.5,-261C967.5,-261 846.5,-261 846.5,-261 840.5,-261 834.5,-255 834.5,-249 834.5,-249 834.5,-205 834.5,-205 834.5,-199 840.5,-193 846.5,-193 846.5,-193 967.5,-193 967.5,-193 973.5,-193 979.5,-199 979.5,-205 979.5,-205 979.5,-249 979.5,-249 979.5,-255 973.5,-261 967.5,-261\"/>\n<text text-anchor=\"start\" x=\"842.5\" y=\"-245.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">LIMIT_BAL ≤ &#45;0.941</text>\n<text text-anchor=\"start\" x=\"869\" y=\"-230.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.482</text>\n<text text-anchor=\"start\" x=\"855\" y=\"-215.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 1579</text>\n<text text-anchor=\"start\" x=\"849\" y=\"-200.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [940, 639]</text>\n</g>\n<!-- 1&#45;&gt;9 -->\n<g id=\"edge9\" class=\"edge\">\n<title>1&#45;&gt;9</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M907,-296.9465C907,-288.776 907,-279.9318 907,-271.3697\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"910.5001,-271.13 907,-261.13 903.5001,-271.13 910.5001,-271.13\"/>\n</g>\n<!-- 3 -->\n<g id=\"node4\" class=\"node\">\n<title>3</title>\n<path fill=\"#eca16b\" stroke=\"#000000\" d=\"M290.5,-157C290.5,-157 165.5,-157 165.5,-157 159.5,-157 153.5,-151 153.5,-145 153.5,-145 153.5,-101 153.5,-101 153.5,-95 159.5,-89 165.5,-89 165.5,-89 290.5,-89 290.5,-89 296.5,-89 302.5,-95 302.5,-101 302.5,-101 302.5,-145 302.5,-145 302.5,-151 296.5,-157 290.5,-157\"/>\n<text text-anchor=\"start\" x=\"162\" y=\"-141.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">PAY_AMT4 ≤ &#45;0.254</text>\n<text text-anchor=\"start\" x=\"190\" y=\"-126.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.322</text>\n<text text-anchor=\"start\" x=\"176\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 6372</text>\n<text text-anchor=\"start\" x=\"161.5\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [5089, 1283]</text>\n</g>\n<!-- 2&#45;&gt;3 -->\n<g id=\"edge3\" class=\"edge\">\n<title>2&#45;&gt;3</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M394.4695,-193.6646C368.1771,-182.5037 338.7688,-170.0202 312.0704,-158.687\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"313.3221,-155.4161 302.7494,-154.7304 310.5868,-161.8596 313.3221,-155.4161\"/>\n</g>\n<!-- 6 -->\n<g id=\"node7\" class=\"node\">\n<title>6</title>\n<path fill=\"#e89051\" stroke=\"#000000\" d=\"M535.5,-157C535.5,-157 410.5,-157 410.5,-157 404.5,-157 398.5,-151 398.5,-145 398.5,-145 398.5,-101 398.5,-101 398.5,-95 404.5,-89 410.5,-89 410.5,-89 535.5,-89 535.5,-89 541.5,-89 547.5,-95 547.5,-101 547.5,-101 547.5,-145 547.5,-145 547.5,-151 541.5,-157 535.5,-157\"/>\n<text text-anchor=\"start\" x=\"424.5\" y=\"-141.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">PAY_4 ≤ 1.476</text>\n<text text-anchor=\"start\" x=\"435\" y=\"-126.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.194</text>\n<text text-anchor=\"start\" x=\"417\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 10875</text>\n<text text-anchor=\"start\" x=\"406.5\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [9694, 1181]</text>\n</g>\n<!-- 2&#45;&gt;6 -->\n<g id=\"edge6\" class=\"edge\">\n<title>2&#45;&gt;6</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M473,-192.9465C473,-184.776 473,-175.9318 473,-167.3697\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"476.5001,-167.13 473,-157.13 469.5001,-167.13 476.5001,-167.13\"/>\n</g>\n<!-- 4 -->\n<g id=\"node5\" class=\"node\">\n<title>4</title>\n<path fill=\"#eda775\" stroke=\"#000000\" d=\"M128,-53C128,-53 12,-53 12,-53 6,-53 0,-47 0,-41 0,-41 0,-12 0,-12 0,-6 6,0 12,0 12,0 128,0 128,0 134,0 140,-6 140,-12 140,-12 140,-41 140,-41 140,-47 134,-53 128,-53\"/>\n<text text-anchor=\"start\" x=\"32\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.356</text>\n<text text-anchor=\"start\" x=\"18\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 4114</text>\n<text text-anchor=\"start\" x=\"8\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [3160, 954]</text>\n</g>\n<!-- 3&#45;&gt;4 -->\n<g id=\"edge4\" class=\"edge\">\n<title>3&#45;&gt;4</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M172.2951,-88.9777C156.028,-79.0424 138.3136,-68.2232 122.2674,-58.4228\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"123.9027,-55.3204 113.5442,-53.095 120.254,-61.2943 123.9027,-55.3204\"/>\n</g>\n<!-- 5 -->\n<g id=\"node6\" class=\"node\">\n<title>5</title>\n<path fill=\"#e9965b\" stroke=\"#000000\" d=\"M286,-53C286,-53 170,-53 170,-53 164,-53 158,-47 158,-41 158,-41 158,-12 158,-12 158,-6 164,0 170,0 170,0 286,0 286,0 292,0 298,-6 298,-12 298,-12 298,-41 298,-41 298,-47 292,-53 286,-53\"/>\n<text text-anchor=\"start\" x=\"190\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.249</text>\n<text text-anchor=\"start\" x=\"176\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 2258</text>\n<text text-anchor=\"start\" x=\"166\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [1929, 329]</text>\n</g>\n<!-- 3&#45;&gt;5 -->\n<g id=\"edge5\" class=\"edge\">\n<title>3&#45;&gt;5</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M228,-88.9777C228,-80.7364 228,-71.887 228,-63.5153\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"231.5001,-63.2484 228,-53.2485 224.5001,-63.2485 231.5001,-63.2484\"/>\n</g>\n<!-- 7 -->\n<g id=\"node8\" class=\"node\">\n<title>7</title>\n<path fill=\"#e88f4f\" stroke=\"#000000\" d=\"M453.5,-53C453.5,-53 328.5,-53 328.5,-53 322.5,-53 316.5,-47 316.5,-41 316.5,-41 316.5,-12 316.5,-12 316.5,-6 322.5,0 328.5,0 328.5,0 453.5,0 453.5,0 459.5,0 465.5,-6 465.5,-12 465.5,-12 465.5,-41 465.5,-41 465.5,-47 459.5,-53 453.5,-53\"/>\n<text text-anchor=\"start\" x=\"357.5\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.18</text>\n<text text-anchor=\"start\" x=\"335\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 10306</text>\n<text text-anchor=\"start\" x=\"324.5\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [9276, 1030]</text>\n</g>\n<!-- 6&#45;&gt;7 -->\n<g id=\"edge7\" class=\"edge\">\n<title>6&#45;&gt;7</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M444.0899,-88.9777C436.3866,-79.9123 428.0581,-70.111 420.3324,-61.0192\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"422.8718,-58.6025 413.7293,-53.2485 417.5375,-63.1352 422.8718,-58.6025\"/>\n</g>\n<!-- 8 -->\n<g id=\"node9\" class=\"node\">\n<title>8</title>\n<path fill=\"#eeaf81\" stroke=\"#000000\" d=\"M604,-53C604,-53 496,-53 496,-53 490,-53 484,-47 484,-41 484,-41 484,-12 484,-12 484,-6 490,0 496,0 496,0 604,0 604,0 610,0 616,-6 616,-12 616,-12 616,-41 616,-41 616,-47 610,-53 604,-53\"/>\n<text text-anchor=\"start\" x=\"516.5\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.39</text>\n<text text-anchor=\"start\" x=\"502\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 569</text>\n<text text-anchor=\"start\" x=\"492\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [418, 151]</text>\n</g>\n<!-- 6&#45;&gt;8 -->\n<g id=\"edge8\" class=\"edge\">\n<title>6&#45;&gt;8</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M500.1473,-88.9777C507.3078,-80.0039 515.0436,-70.3089 522.2361,-61.295\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"525.1554,-63.2481 528.6567,-53.2485 519.6837,-58.8821 525.1554,-63.2481\"/>\n</g>\n<!-- 10 -->\n<g id=\"node11\" class=\"node\">\n<title>10</title>\n<path fill=\"#fefbf9\" stroke=\"#000000\" d=\"M890,-157C890,-157 766,-157 766,-157 760,-157 754,-151 754,-145 754,-145 754,-101 754,-101 754,-95 760,-89 766,-89 766,-89 890,-89 890,-89 896,-89 902,-95 902,-101 902,-101 902,-145 902,-145 902,-151 896,-157 890,-157\"/>\n<text text-anchor=\"start\" x=\"762\" y=\"-141.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">PAY_AMT4 ≤ &#45;0.158</text>\n<text text-anchor=\"start\" x=\"798.5\" y=\"-126.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.5</text>\n<text text-anchor=\"start\" x=\"780\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 483</text>\n<text text-anchor=\"start\" x=\"770\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [245, 238]</text>\n</g>\n<!-- 9&#45;&gt;10 -->\n<g id=\"edge10\" class=\"edge\">\n<title>9&#45;&gt;10</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M881.1324,-192.9465C874.3804,-184.0578 867.0226,-174.3716 859.9941,-165.1188\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"862.7617,-162.976 853.9257,-157.13 857.1875,-167.2102 862.7617,-162.976\"/>\n</g>\n<!-- 13 -->\n<g id=\"node14\" class=\"node\">\n<title>13</title>\n<path fill=\"#f4caab\" stroke=\"#000000\" d=\"M1040,-157C1040,-157 932,-157 932,-157 926,-157 920,-151 920,-145 920,-145 920,-101 920,-101 920,-95 926,-89 932,-89 932,-89 1040,-89 1040,-89 1046,-89 1052,-95 1052,-101 1052,-101 1052,-145 1052,-145 1052,-151 1046,-157 1040,-157\"/>\n<text text-anchor=\"start\" x=\"937.5\" y=\"-141.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">PAY_5 ≤ 1.119</text>\n<text text-anchor=\"start\" x=\"948\" y=\"-126.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.464</text>\n<text text-anchor=\"start\" x=\"934\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 1096</text>\n<text text-anchor=\"start\" x=\"928\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [695, 401]</text>\n</g>\n<!-- 9&#45;&gt;13 -->\n<g id=\"edge13\" class=\"edge\">\n<title>9&#45;&gt;13</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M932.8676,-192.9465C939.6196,-184.0578 946.9774,-174.3716 954.0059,-165.1188\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"956.8125,-167.2102 960.0743,-157.13 951.2383,-162.976 956.8125,-167.2102\"/>\n</g>\n<!-- 11 -->\n<g id=\"node12\" class=\"node\">\n<title>11</title>\n<path fill=\"#f4f9fe\" stroke=\"#000000\" d=\"M754,-53C754,-53 646,-53 646,-53 640,-53 634,-47 634,-41 634,-41 634,-12 634,-12 634,-6 640,0 646,0 646,0 754,0 754,0 760,0 766,-6 766,-12 766,-12 766,-41 766,-41 766,-47 760,-53 754,-53\"/>\n<text text-anchor=\"start\" x=\"670.5\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.5</text>\n<text text-anchor=\"start\" x=\"652\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 445</text>\n<text text-anchor=\"start\" x=\"642\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [216, 229]</text>\n</g>\n<!-- 10&#45;&gt;11 -->\n<g id=\"edge11\" class=\"edge\">\n<title>10&#45;&gt;11</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M782.872,-88.9777C770.1187,-79.3629 756.2673,-68.9203 743.6053,-59.3743\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"745.5719,-56.4737 735.4798,-53.2485 741.3579,-62.0632 745.5719,-56.4737\"/>\n</g>\n<!-- 12 -->\n<g id=\"node13\" class=\"node\">\n<title>12</title>\n<path fill=\"#eda876\" stroke=\"#000000\" d=\"M879.5,-53C879.5,-53 796.5,-53 796.5,-53 790.5,-53 784.5,-47 784.5,-41 784.5,-41 784.5,-12 784.5,-12 784.5,-6 790.5,0 796.5,0 796.5,0 879.5,0 879.5,0 885.5,0 891.5,-6 891.5,-12 891.5,-12 891.5,-41 891.5,-41 891.5,-47 885.5,-53 879.5,-53\"/>\n<text text-anchor=\"start\" x=\"800\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.361</text>\n<text text-anchor=\"start\" x=\"794\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 38</text>\n<text text-anchor=\"start\" x=\"792.5\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [29, 9]</text>\n</g>\n<!-- 10&#45;&gt;12 -->\n<g id=\"edge12\" class=\"edge\">\n<title>10&#45;&gt;12</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M831.5256,-88.9777C832.3891,-80.6449 833.3171,-71.6903 834.1931,-63.2364\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"837.6787,-63.556 835.2281,-53.2485 830.7159,-62.8344 837.6787,-63.556\"/>\n</g>\n<!-- 14 -->\n<g id=\"node15\" class=\"node\">\n<title>14</title>\n<path fill=\"#f2c09c\" stroke=\"#000000\" d=\"M1030,-53C1030,-53 922,-53 922,-53 916,-53 910,-47 910,-41 910,-41 910,-12 910,-12 910,-6 916,0 922,0 922,0 1030,0 1030,0 1036,0 1042,-6 1042,-12 1042,-12 1042,-41 1042,-41 1042,-47 1036,-53 1030,-53\"/>\n<text text-anchor=\"start\" x=\"938\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.444</text>\n<text text-anchor=\"start\" x=\"928\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 809</text>\n<text text-anchor=\"start\" x=\"918\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [540, 269]</text>\n</g>\n<!-- 13&#45;&gt;14 -->\n<g id=\"edge14\" class=\"edge\">\n<title>13&#45;&gt;14</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M982.4744,-88.9777C981.6109,-80.6449 980.6829,-71.6903 979.8069,-63.2364\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"983.2841,-62.8344 978.7719,-53.2485 976.3213,-63.556 983.2841,-62.8344\"/>\n</g>\n<!-- 15 -->\n<g id=\"node16\" class=\"node\">\n<title>15</title>\n<path fill=\"#fbece2\" stroke=\"#000000\" d=\"M1180,-53C1180,-53 1072,-53 1072,-53 1066,-53 1060,-47 1060,-41 1060,-41 1060,-12 1060,-12 1060,-6 1066,0 1072,0 1072,0 1180,0 1180,0 1186,0 1192,-6 1192,-12 1192,-12 1192,-41 1192,-41 1192,-47 1186,-53 1180,-53\"/>\n<text text-anchor=\"start\" x=\"1088\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.497</text>\n<text text-anchor=\"start\" x=\"1078\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 287</text>\n<text text-anchor=\"start\" x=\"1068\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [155, 132]</text>\n</g>\n<!-- 13&#45;&gt;15 -->\n<g id=\"edge15\" class=\"edge\">\n<title>13&#45;&gt;15</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1035.3588,-88.9777C1049.4406,-79.2713 1064.7463,-68.7213 1078.702,-59.1018\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"1080.9467,-61.8055 1087.1939,-53.2485 1076.974,-56.042 1080.9467,-61.8055\"/>\n</g>\n<!-- 17 -->\n<g id=\"node18\" class=\"node\">\n<title>17</title>\n<path fill=\"#a6d3f3\" stroke=\"#000000\" d=\"M1524,-261C1524,-261 1398,-261 1398,-261 1392,-261 1386,-255 1386,-249 1386,-249 1386,-205 1386,-205 1386,-199 1392,-193 1398,-193 1398,-193 1524,-193 1524,-193 1530,-193 1536,-199 1536,-205 1536,-205 1536,-249 1536,-249 1536,-255 1530,-261 1524,-261\"/>\n<text text-anchor=\"start\" x=\"1394\" y=\"-245.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">BILL_AMT1 ≤ &#45;0.667</text>\n<text text-anchor=\"start\" x=\"1423\" y=\"-230.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.458</text>\n<text text-anchor=\"start\" x=\"1409\" y=\"-215.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 1257</text>\n<text text-anchor=\"start\" x=\"1403\" y=\"-200.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [446, 811]</text>\n</g>\n<!-- 16&#45;&gt;17 -->\n<g id=\"edge17\" class=\"edge\">\n<title>16&#45;&gt;17</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1461,-296.9465C1461,-288.776 1461,-279.9318 1461,-271.3697\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"1464.5001,-271.13 1461,-261.13 1457.5001,-271.13 1464.5001,-271.13\"/>\n</g>\n<!-- 24 -->\n<g id=\"node25\" class=\"node\">\n<title>24</title>\n<path fill=\"#73baed\" stroke=\"#000000\" d=\"M1930.5,-261C1930.5,-261 1811.5,-261 1811.5,-261 1805.5,-261 1799.5,-255 1799.5,-249 1799.5,-249 1799.5,-205 1799.5,-205 1799.5,-199 1805.5,-193 1811.5,-193 1811.5,-193 1930.5,-193 1930.5,-193 1936.5,-193 1942.5,-199 1942.5,-205 1942.5,-205 1942.5,-249 1942.5,-249 1942.5,-255 1936.5,-261 1930.5,-261\"/>\n<text text-anchor=\"start\" x=\"1807.5\" y=\"-245.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">PAY_AMT3 ≤ 0.393</text>\n<text text-anchor=\"start\" x=\"1833\" y=\"-230.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.352</text>\n<text text-anchor=\"start\" x=\"1823\" y=\"-215.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 917</text>\n<text text-anchor=\"start\" x=\"1813\" y=\"-200.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [209, 708]</text>\n</g>\n<!-- 16&#45;&gt;24 -->\n<g id=\"edge24\" class=\"edge\">\n<title>16&#45;&gt;24</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1531.0157,-313.2399C1602.5911,-295.0842 1713.687,-266.9038 1789.2506,-247.7364\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"1790.3745,-251.0623 1799.2069,-245.2109 1788.6533,-244.2772 1790.3745,-251.0623\"/>\n</g>\n<!-- 18 -->\n<g id=\"node19\" class=\"node\">\n<title>18</title>\n<path fill=\"#f5d0b6\" stroke=\"#000000\" d=\"M1437.5,-157C1437.5,-157 1318.5,-157 1318.5,-157 1312.5,-157 1306.5,-151 1306.5,-145 1306.5,-145 1306.5,-101 1306.5,-101 1306.5,-95 1312.5,-89 1318.5,-89 1318.5,-89 1437.5,-89 1437.5,-89 1443.5,-89 1449.5,-95 1449.5,-101 1449.5,-101 1449.5,-145 1449.5,-145 1449.5,-151 1443.5,-157 1437.5,-157\"/>\n<text text-anchor=\"start\" x=\"1314.5\" y=\"-141.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">PAY_AMT5 ≤ 1.338</text>\n<text text-anchor=\"start\" x=\"1340\" y=\"-126.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.474</text>\n<text text-anchor=\"start\" x=\"1330\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 106</text>\n<text text-anchor=\"start\" x=\"1328\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [65, 41]</text>\n</g>\n<!-- 17&#45;&gt;18 -->\n<g id=\"edge18\" class=\"edge\">\n<title>17&#45;&gt;18</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1433.8227,-192.9465C1426.7288,-184.0578 1418.9985,-174.3716 1411.614,-165.1188\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"1414.2118,-162.7628 1405.2384,-157.13 1408.7406,-167.1293 1414.2118,-162.7628\"/>\n</g>\n<!-- 21 -->\n<g id=\"node22\" class=\"node\">\n<title>21</title>\n<path fill=\"#9bcdf2\" stroke=\"#000000\" d=\"M1608.5,-157C1608.5,-157 1479.5,-157 1479.5,-157 1473.5,-157 1467.5,-151 1467.5,-145 1467.5,-145 1467.5,-101 1467.5,-101 1467.5,-95 1473.5,-89 1479.5,-89 1479.5,-89 1608.5,-89 1608.5,-89 1614.5,-89 1620.5,-95 1620.5,-101 1620.5,-101 1620.5,-145 1620.5,-145 1620.5,-151 1614.5,-157 1608.5,-157\"/>\n<text text-anchor=\"start\" x=\"1475.5\" y=\"-141.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">EDUCATION ≤ 2.091</text>\n<text text-anchor=\"start\" x=\"1506\" y=\"-126.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.443</text>\n<text text-anchor=\"start\" x=\"1492\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 1151</text>\n<text text-anchor=\"start\" x=\"1486\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [381, 770]</text>\n</g>\n<!-- 17&#45;&gt;21 -->\n<g id=\"edge21\" class=\"edge\">\n<title>17&#45;&gt;21</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1488.1773,-192.9465C1495.2712,-184.0578 1503.0015,-174.3716 1510.386,-165.1188\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"1513.2594,-167.1293 1516.7616,-157.13 1507.7882,-162.7628 1513.2594,-167.1293\"/>\n</g>\n<!-- 19 -->\n<g id=\"node20\" class=\"node\">\n<title>19</title>\n<path fill=\"#f4c9aa\" stroke=\"#000000\" d=\"M1314,-53C1314,-53 1222,-53 1222,-53 1216,-53 1210,-47 1210,-41 1210,-41 1210,-12 1210,-12 1210,-6 1216,0 1222,0 1222,0 1314,0 1314,0 1320,0 1326,-6 1326,-12 1326,-12 1326,-41 1326,-41 1326,-47 1320,-53 1314,-53\"/>\n<text text-anchor=\"start\" x=\"1230\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.462</text>\n<text text-anchor=\"start\" x=\"1220\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 102</text>\n<text text-anchor=\"start\" x=\"1218\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [65, 37]</text>\n</g>\n<!-- 18&#45;&gt;19 -->\n<g id=\"edge19\" class=\"edge\">\n<title>18&#45;&gt;19</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1339.2181,-88.9777C1328.467,-79.546 1316.8078,-69.3178 1306.0962,-59.9208\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"1308.316,-57.2122 1298.4905,-53.2485 1303.6996,-62.4743 1308.316,-57.2122\"/>\n</g>\n<!-- 20 -->\n<g id=\"node21\" class=\"node\">\n<title>20</title>\n<path fill=\"#399de5\" stroke=\"#000000\" d=\"M1431.5,-53C1431.5,-53 1356.5,-53 1356.5,-53 1350.5,-53 1344.5,-47 1344.5,-41 1344.5,-41 1344.5,-12 1344.5,-12 1344.5,-6 1350.5,0 1356.5,0 1356.5,0 1431.5,0 1431.5,0 1437.5,0 1443.5,-6 1443.5,-12 1443.5,-12 1443.5,-41 1443.5,-41 1443.5,-47 1437.5,-53 1431.5,-53\"/>\n<text text-anchor=\"start\" x=\"1364.5\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.0</text>\n<text text-anchor=\"start\" x=\"1354.5\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 4</text>\n<text text-anchor=\"start\" x=\"1352.5\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [0, 4]</text>\n</g>\n<!-- 18&#45;&gt;20 -->\n<g id=\"edge20\" class=\"edge\">\n<title>18&#45;&gt;20</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1383.641,-88.9777C1385.0226,-80.6449 1386.5073,-71.6903 1387.909,-63.2364\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"1391.3821,-63.6863 1389.565,-53.2485 1384.4764,-62.5413 1391.3821,-63.6863\"/>\n</g>\n<!-- 22 -->\n<g id=\"node23\" class=\"node\">\n<title>22</title>\n<path fill=\"#98ccf2\" stroke=\"#000000\" d=\"M1582,-53C1582,-53 1474,-53 1474,-53 1468,-53 1462,-47 1462,-41 1462,-41 1462,-12 1462,-12 1462,-6 1468,0 1474,0 1474,0 1582,0 1582,0 1588,0 1594,-6 1594,-12 1594,-12 1594,-41 1594,-41 1594,-47 1588,-53 1582,-53\"/>\n<text text-anchor=\"start\" x=\"1490\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.439</text>\n<text text-anchor=\"start\" x=\"1476\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 1133</text>\n<text text-anchor=\"start\" x=\"1470\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [368, 765]</text>\n</g>\n<!-- 21&#45;&gt;22 -->\n<g id=\"edge22\" class=\"edge\">\n<title>21&#45;&gt;22</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1538.359,-88.9777C1536.9774,-80.6449 1535.4927,-71.6903 1534.091,-63.2364\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"1537.5236,-62.5413 1532.435,-53.2485 1530.6179,-63.6863 1537.5236,-62.5413\"/>\n</g>\n<!-- 23 -->\n<g id=\"node24\" class=\"node\">\n<title>23</title>\n<path fill=\"#efb185\" stroke=\"#000000\" d=\"M1707.5,-53C1707.5,-53 1624.5,-53 1624.5,-53 1618.5,-53 1612.5,-47 1612.5,-41 1612.5,-41 1612.5,-12 1612.5,-12 1612.5,-6 1618.5,0 1624.5,0 1624.5,0 1707.5,0 1707.5,0 1713.5,0 1719.5,-6 1719.5,-12 1719.5,-12 1719.5,-41 1719.5,-41 1719.5,-47 1713.5,-53 1707.5,-53\"/>\n<text text-anchor=\"start\" x=\"1628\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.401</text>\n<text text-anchor=\"start\" x=\"1622\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 18</text>\n<text text-anchor=\"start\" x=\"1620.5\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [13, 5]</text>\n</g>\n<!-- 21&#45;&gt;23 -->\n<g id=\"edge23\" class=\"edge\">\n<title>21&#45;&gt;23</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1587.0126,-88.9777C1599.0524,-79.4545 1612.1188,-69.1191 1624.0935,-59.6473\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"1626.5115,-62.1973 1632.1833,-53.2485 1622.1689,-56.7072 1626.5115,-62.1973\"/>\n</g>\n<!-- 25 -->\n<g id=\"node26\" class=\"node\">\n<title>25</title>\n<path fill=\"#6fb8ec\" stroke=\"#000000\" d=\"M1925,-157C1925,-157 1817,-157 1817,-157 1811,-157 1805,-151 1805,-145 1805,-145 1805,-101 1805,-101 1805,-95 1811,-89 1817,-89 1817,-89 1925,-89 1925,-89 1931,-89 1937,-95 1937,-101 1937,-101 1937,-145 1937,-145 1937,-151 1931,-157 1925,-157\"/>\n<text text-anchor=\"start\" x=\"1822.5\" y=\"-141.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">PAY_2 ≤ 3.048</text>\n<text text-anchor=\"start\" x=\"1833\" y=\"-126.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.338</text>\n<text text-anchor=\"start\" x=\"1823\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 895</text>\n<text text-anchor=\"start\" x=\"1813\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [193, 702]</text>\n</g>\n<!-- 24&#45;&gt;25 -->\n<g id=\"edge25\" class=\"edge\">\n<title>24&#45;&gt;25</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1871,-192.9465C1871,-184.776 1871,-175.9318 1871,-167.3697\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"1874.5001,-167.13 1871,-157.13 1867.5001,-167.13 1874.5001,-167.13\"/>\n</g>\n<!-- 28 -->\n<g id=\"node29\" class=\"node\">\n<title>28</title>\n<path fill=\"#efb083\" stroke=\"#000000\" d=\"M2117.5,-157C2117.5,-157 2034.5,-157 2034.5,-157 2028.5,-157 2022.5,-151 2022.5,-145 2022.5,-145 2022.5,-101 2022.5,-101 2022.5,-95 2028.5,-89 2034.5,-89 2034.5,-89 2117.5,-89 2117.5,-89 2123.5,-89 2129.5,-95 2129.5,-101 2129.5,-101 2129.5,-145 2129.5,-145 2129.5,-151 2123.5,-157 2117.5,-157\"/>\n<text text-anchor=\"start\" x=\"2034.5\" y=\"-141.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">AGE ≤ 0.328</text>\n<text text-anchor=\"start\" x=\"2038\" y=\"-126.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.397</text>\n<text text-anchor=\"start\" x=\"2032\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 22</text>\n<text text-anchor=\"start\" x=\"2030.5\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [16, 6]</text>\n</g>\n<!-- 24&#45;&gt;28 -->\n<g id=\"edge28\" class=\"edge\">\n<title>24&#45;&gt;28</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1938.1247,-192.9465C1962.3537,-180.6547 1989.5885,-166.838 2013.4137,-154.7511\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"2015.0301,-157.8558 2022.3646,-150.2101 2011.8631,-151.6132 2015.0301,-157.8558\"/>\n</g>\n<!-- 26 -->\n<g id=\"node27\" class=\"node\">\n<title>26</title>\n<path fill=\"#6cb6ec\" stroke=\"#000000\" d=\"M1858,-53C1858,-53 1750,-53 1750,-53 1744,-53 1738,-47 1738,-41 1738,-41 1738,-12 1738,-12 1738,-6 1744,0 1750,0 1750,0 1858,0 1858,0 1864,0 1870,-6 1870,-12 1870,-12 1870,-41 1870,-41 1870,-47 1864,-53 1858,-53\"/>\n<text text-anchor=\"start\" x=\"1766\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.324</text>\n<text text-anchor=\"start\" x=\"1756\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 841</text>\n<text text-anchor=\"start\" x=\"1746\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [171, 670]</text>\n</g>\n<!-- 25&#45;&gt;26 -->\n<g id=\"edge26\" class=\"edge\">\n<title>25&#45;&gt;26</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1847.3783,-88.9777C1841.2113,-80.0954 1834.5539,-70.5067 1828.3499,-61.5711\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"1831.1497,-59.4666 1822.5715,-53.2485 1825.3997,-63.4589 1831.1497,-59.4666\"/>\n</g>\n<!-- 27 -->\n<g id=\"node28\" class=\"node\">\n<title>27</title>\n<path fill=\"#c1e0f7\" stroke=\"#000000\" d=\"M1992,-53C1992,-53 1900,-53 1900,-53 1894,-53 1888,-47 1888,-41 1888,-41 1888,-12 1888,-12 1888,-6 1894,0 1900,0 1900,0 1992,0 1992,0 1998,0 2004,-6 2004,-12 2004,-12 2004,-41 2004,-41 2004,-47 1998,-53 1992,-53\"/>\n<text text-anchor=\"start\" x=\"1908\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.483</text>\n<text text-anchor=\"start\" x=\"1902\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 54</text>\n<text text-anchor=\"start\" x=\"1896\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [22, 32]</text>\n</g>\n<!-- 25&#45;&gt;27 -->\n<g id=\"edge27\" class=\"edge\">\n<title>25&#45;&gt;27</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1897.4422,-88.9777C1904.4167,-80.0039 1911.9516,-70.3089 1918.9573,-61.295\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"1921.8379,-63.292 1925.211,-53.2485 1916.3109,-58.9964 1921.8379,-63.292\"/>\n</g>\n<!-- 29 -->\n<g id=\"node30\" class=\"node\">\n<title>29</title>\n<path fill=\"#e88e4d\" stroke=\"#000000\" d=\"M2117.5,-53C2117.5,-53 2034.5,-53 2034.5,-53 2028.5,-53 2022.5,-47 2022.5,-41 2022.5,-41 2022.5,-12 2022.5,-12 2022.5,-6 2028.5,0 2034.5,0 2034.5,0 2117.5,0 2117.5,0 2123.5,0 2129.5,-6 2129.5,-12 2129.5,-12 2129.5,-41 2129.5,-41 2129.5,-47 2123.5,-53 2117.5,-53\"/>\n<text text-anchor=\"start\" x=\"2038\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.165</text>\n<text text-anchor=\"start\" x=\"2032\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 11</text>\n<text text-anchor=\"start\" x=\"2030.5\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [10, 1]</text>\n</g>\n<!-- 28&#45;&gt;29 -->\n<g id=\"edge29\" class=\"edge\">\n<title>28&#45;&gt;29</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M2076,-88.9777C2076,-80.7364 2076,-71.887 2076,-63.5153\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"2079.5001,-63.2484 2076,-53.2485 2072.5001,-63.2485 2079.5001,-63.2484\"/>\n</g>\n<!-- 30 -->\n<g id=\"node31\" class=\"node\">\n<title>30</title>\n<path fill=\"#fbeade\" stroke=\"#000000\" d=\"M2240,-53C2240,-53 2160,-53 2160,-53 2154,-53 2148,-47 2148,-41 2148,-41 2148,-12 2148,-12 2148,-6 2154,0 2160,0 2160,0 2240,0 2240,0 2246,0 2252,-6 2252,-12 2252,-12 2252,-41 2252,-41 2252,-47 2246,-53 2240,-53\"/>\n<text text-anchor=\"start\" x=\"2162\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">gini = 0.496</text>\n<text text-anchor=\"start\" x=\"2156\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 11</text>\n<text text-anchor=\"start\" x=\"2158.5\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = [6, 5]</text>\n</g>\n<!-- 28&#45;&gt;30 -->\n<g id=\"edge30\" class=\"edge\">\n<title>28&#45;&gt;30</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M2119.7178,-88.9777C2131.9549,-79.4545 2145.2355,-69.1191 2157.4066,-59.6473\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"2159.8866,-62.1523 2165.6289,-53.2485 2155.5875,-56.628 2159.8866,-62.1523\"/>\n</g>\n</g>\n</svg>\n"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 108
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EBZJYa0fKXfl"
      },
      "source": [
        "crossvalidation=cross_val_score(model2, X_train, y_train, cv=10).mean()"
      ],
      "execution_count": 109,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_KvQ5wv5K4_9",
        "outputId": "58686e0d-84ed-4de6-c202-9f048b9539ff",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "print('Accuracy: ' , model2.score(X_test, y_test))\n",
        "print('Cross-validation accuracy:' , crossvalidation)"
      ],
      "execution_count": 110,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Accuracy:  0.8142222222222222\n",
            "Cross-validation accuracy: 0.8206666666666667\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HR9NU_fKU-Tf"
      },
      "source": [
        "A bit of improvement can be seen in accuracy and cross validation accuracy of the model."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ixMsXg52LOWA",
        "outputId": "9ada4be9-4273-49ae-82d8-93c8a609c96c",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "conMatrix1=confusion_matrix(y_test,model2.predict(X_test))\n",
        "conMatrix1"
      ],
      "execution_count": 111,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[6625,  361],\n",
              "       [1311,  703]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 111
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5Hncf-wXVmdF",
        "outputId": "117b7ff9-1fdb-4e01-bab2-1f7206399708",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "print(\"correct predictions:\",conMatrix1[0,0]+conMatrix1[1,1])\n",
        "print(\"wrong predictions:\",conMatrix1[0,1]+conMatrix1[1,0])"
      ],
      "execution_count": 112,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "correct predictions: 7328\n",
            "wrong predictions: 1672\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6x2rGphcOj24"
      },
      "source": [
        "predictions accurcy is increased with deacrease in false negatives count so it is obviously a better model compared to model 1."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xjXnvLY5w4eB"
      },
      "source": [
        "# KNN: model3\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7nc5T8uilPG9"
      },
      "source": [
        "from sklearn.svm import SVC\n",
        "from sklearn.neighbors import KNeighborsClassifier"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jlYJETyCLtUQ",
        "outputId": "08495c48-4fec-4ff2-bc3c-47d0bbc58c4a",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "knn = KNeighborsClassifier(n_neighbors = 2)\n",
        "knn.fit(X_train, y_train)\n",
        "acc = knn.score(X_test,y_test)\n",
        "print(\"The accuracy score for KNN is: \",acc)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "The accuracy score for KNN is:  0.7877777777777778\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1yObJ_jJxLss",
        "outputId": "f682469d-f610-409a-bb20-7ee6faf3ceb5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "confusion_matrix(y_test,knn.predict(X_test))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[6661,  325],\n",
              "       [1585,  429]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3TTS_woVm3jU"
      },
      "source": [
        "# SVM: Model 4"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w2p1zgzam1FZ",
        "outputId": "41f471aa-e56f-40cc-9176-651d5c6182f2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "svm = SVC()\n",
        "svm.fit(X_train, y_train)\n",
        "acc = svm.score(X_test,y_test)\n",
        "print(\"The accuracy score for SVM is:\",acc)"
      ],
      "execution_count": 113,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "The accuracy score for SVM is: 0.8183333333333334\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "t0Ki0SFqxLy0",
        "outputId": "848a9aeb-2e7d-4f1c-db09-349c54e56e5e",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "conmatrix3=confusion_matrix(y_test,svm.predict(X_test))\n",
        "conmatrix3"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[6708,  278],\n",
              "       [1350,  664]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 75
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zgvlICDl14m6",
        "outputId": "dddafa7a-22cf-4983-9edf-ece32fd26c13",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "print(\"correct predictions:\",conmatrix3[0,0]+conmatrix3[1,1])\n",
        "print(\"wrong predictions:\",conmatrix3[0,1]+conmatrix3[1,0])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "correct predictions: 7372\n",
            "wrong predictions: 1628\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ko4jWllEnlws"
      },
      "source": [
        "So, by taking accuracy and confusion matrix into consideration we can say that all above 4 models order of their performances is Decision Tree, SVM, Logistic Regression, KNN."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vBB9MbYPsWin"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}