iris_flowers_classification_decision_tree__LGMVIP_intern.ipynb

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  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "rHjyhm7HvXsU"
      },
      "source": [
        "from sklearn.datasets import load_iris # import iris data set from sklearn library\n",
        "from sklearn import tree \n",
        "from sklearn.tree  import  DecisionTreeClassifier   \n",
        "from   sklearn.metrics import accuracy_score ,confusion_matrix                                                       "
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tKF8rz8Y7QPq"
      },
      "source": [
        "iris=load_iris()\n",
        "X = iris.data\n",
        "y = iris.target"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "iris.feature_names"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mlej8tvxzt6h",
        "outputId": "f132781e-484d-4966-dcbc-ddf86aefd192"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['sepal length (cm)',\n",
              " 'sepal width (cm)',\n",
              " 'petal length (cm)',\n",
              " 'petal width (cm)']"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "iris.target_names"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gppwaaSaz_WP",
        "outputId": "c3e668ac-4792-4ce4-bf4c-07edaa1a36ef"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['setosa', 'versicolor', 'virginica'], dtype='<U10')"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JsBiFGUeMioD"
      },
      "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=0.4, random_state =33)                       \n",
        " "
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 75
        },
        "id": "uv5wygPlV-Tc",
        "outputId": "0c96c6fe-667c-4494-9a4d-78c8138dea4f"
      },
      "source": [
        "DTC=DecisionTreeClassifier(max_depth=3)\n",
        "\n",
        "DTC.fit(X_train,y_train) "
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DecisionTreeClassifier(max_depth=3)"
            ],
            "text/html": [
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            ]
          },
          "metadata": {},
          "execution_count": 6
        }
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    {
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        "id": "E5ApxyhOW-D7",
        "outputId": "67bb40a2-6be8-4f6f-a3e7-8c07876b0e01"
      },
      "source": [
        "DTC.classes_"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0, 1, 2])"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4gOewVxel7V7"
      },
      "source": [
        "y_pred=DTC.predict(X_test)\n"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1xtI4s6MkrOv",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "73c57898-a0c2-460b-b8ec-801c6fd64913"
      },
      "source": [
        "accuracy = accuracy_score(y_pred, y_test)\n",
        "accuracy\n"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.9666666666666667"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
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        "id": "Le8KwqlUnp9X",
        "outputId": "4a27fb49-bf09-460c-b601-8a22002381b5"
      },
      "source": [
        "print(confusion_matrix(y_test, y_pred))"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[17  0  0]\n",
            " [ 0 19  1]\n",
            " [ 0  1 22]]\n"
          ]
        }
      ]
    }
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}