tree_code.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Untitled2.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyOb5ECGl8FeLLGPuCndKybG",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Jean-Tshibangu-jtm/Prediction_Fraude_avec_Arbre_de_Decision/blob/master/tree_code.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "M1KZ9DPmWNyn",
        "outputId": "6e2daf62-653a-4001-a1d9-e0324a50be3b"
      },
      "source": [
        "import pandas as pd\n",
        "from sklearn.tree import DecisionTreeClassifier\n",
        "from sklearn.externals.six import StringIO \n",
        "from IPython.display import Image \n",
        "from sklearn.tree import export_graphviz\n",
        "import pydotplus\n",
        "from sklearn import tree"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/externals/six.py:31: FutureWarning: The module is deprecated in version 0.21 and will be removed in version 0.23 since we've dropped support for Python 2.7. Please rely on the official version of six (https://pypi.org/project/six/).\n",
            "  \"(https://pypi.org/project/six/).\", FutureWarning)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Kl3sFoltZjSO"
      },
      "source": [
        "from sklearn.preprocessing import LabelEncoder\n",
        "\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.tree import DecisionTreeClassifier\n",
        "from sklearn.metrics import confusion_matrix\n",
        "from sklearn.model_selection import GridSearchCV\n",
        "from sklearn.metrics import classification_report"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g46-gTuYWlal"
      },
      "source": [
        "dataset = pd.read_csv('prediction_de_fraud.csv')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y9EnyuwcWlWF",
        "outputId": "4cba30ce-8fca-4590-a03f-dc2f6738c793"
      },
      "source": [
        "dataset.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1421223, 11)"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tczRQd6lWlMH"
      },
      "source": [
        "#récupération les données predictives\n",
        "X = dataset.drop('isFraud', axis = 1).values\n",
        "target = dataset['isFraud'].values\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OmudtRVIZ4l1"
      },
      "source": [
        "from sklearn.preprocessing import LabelEncoder\n",
        "labEncr_X = LabelEncoder()\n",
        "X[:,1] = labEncr_X.fit_transform(X[:,1])\n",
        "X[:,3] = labEncr_X.fit_transform(X[:,3])\n",
        "X[:,6] = labEncr_X.fit_transform(X[:,6])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ff7CDumQZ5R9"
      },
      "source": [
        "#Initialisation du classifieur Arbre de décision\n",
        "decTree_2 = DecisionTreeClassifier(criterion = 'gini', random_state = 50,\n",
        "max_depth= 3, min_samples_leaf=0.02)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pYClx0FjZ7mL",
        "outputId": "abc3160c-6934-4e98-81ad-753a6d3e67ea"
      },
      "source": [
        "# Adapter le classificateur aux données\n",
        "decTree_2.fit(X, target)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\n",
              "                       max_depth=3, max_features=None, max_leaf_nodes=None,\n",
              "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
              "                       min_samples_leaf=0.02, min_samples_split=2,\n",
              "                       min_weight_fraction_leaf=0.0, presort='deprecated',\n",
              "                       random_state=50, splitter='best')"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5e9--mimZ7hC"
      },
      "source": [
        "X_names = dataset.drop('isFraud', axis = 1)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aNlznkMYlEvc"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YAnj3yTzZ7cI"
      },
      "source": [
        "data = tree.export_graphviz(decTree_2, out_file=None, feature_names= X_names.columns.values, proportion= True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Oa_MCZo2Z7W4"
      },
      "source": [
        "graph = pydotplus.graph_from_dot_data(data) "
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 514
        },
        "id": "YFevIEoGZ7Od",
        "outputId": "7cff7bf1-91d3-4700-fb52-afb309b661a5"
      },
      "source": [
        "Image(graph.create_png())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b0SgYUOTZ7Dl"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}