Código.ipynb

{
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  "nbformat_minor": 5,
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.7.8"
    },
    "colab": {
      "name": "Código.ipynb",
      "provenance": [],
      "include_colab_link": true
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/CabecaDeCenoura/Inteligencia-Artificial-Iris/blob/main/C%C3%B3digo.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "sNQJ7_a2jR8z"
      },
      "source": [
        "import pandas as pd\n",
        "names = ['SepalLength', 'SepalWidth',\n",
        "         'PetalLength', 'PetalWidth',\n",
        "         'Class']\n",
        "df = pd.read_csv('iris.data', names=names)"
      ],
      "id": "sNQJ7_a2jR8z",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "Jgfhfa3ojR84",
        "outputId": "7a05a6fe-3321-4275-f785-1c892568f374"
      },
      "source": [
        "print(\"Linhas: %d, Colunas: %d\" % (len(df), len(df.columns)))"
      ],
      "id": "Jgfhfa3ojR84",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Linhas: 100, Colunas: 5\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "5_2p1-MajR87",
        "outputId": "fba73595-d2d5-482d-ded5-206650d2e096"
      },
      "source": [
        "df.head()"
      ],
      "id": "5_2p1-MajR87",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   SepalLength  SepalWidth  PetalLength  PetalWidth        Class\n",
              "0          5.1         3.5          1.4         0.2  Iris-setosa\n",
              "1          4.9         3.0          1.4         0.2  Iris-setosa\n",
              "2          4.7         3.2          1.3         0.2  Iris-setosa\n",
              "3          4.6         3.1          1.5         0.2  Iris-setosa\n",
              "4          5.0         3.6          1.4         0.2  Iris-setosa"
            ],
            "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>SepalLength</th>\n",
              "      <th>SepalWidth</th>\n",
              "      <th>PetalLength</th>\n",
              "      <th>PetalWidth</th>\n",
              "      <th>Class</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>5.1</td>\n",
              "      <td>3.5</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4.9</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>4.7</td>\n",
              "      <td>3.2</td>\n",
              "      <td>1.3</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4.6</td>\n",
              "      <td>3.1</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5.0</td>\n",
              "      <td>3.6</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "EjsqZE1zjR88",
        "outputId": "f4d25f83-92f9-4e77-df9b-97c8ce85e221"
      },
      "source": [
        "df['Class'].value_counts()"
      ],
      "id": "EjsqZE1zjR88",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Iris-versicolor    50\n",
              "Iris-setosa        50\n",
              "Name: Class, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "QUcUIrYXjR89",
        "outputId": "68911b85-d938-4049-ccd2-0490f366f65c"
      },
      "source": [
        "%matplotlib inline\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "df['Class'].value_counts().plot(kind='pie')\n",
        "plt.axis('equal');"
      ],
      "id": "QUcUIrYXjR89",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "jJNX8-mzjR8-",
        "outputId": "396ad3ed-d583-4d3e-9037-88e138e9ba8a"
      },
      "source": [
        "df['SepalArea'] = df['SepalLength'] * df['SepalWidth']\n",
        "df['PetalArea'] = df['PetalLength'] * df['PetalWidth']\n",
        "\n",
        "df['SepalLengthAboveMean'] = df['SepalLength'] > df['SepalLength'].mean()\n",
        "df['SepalWidthAboveMean'] = df['SepalWidth'] > df['SepalWidth'].mean()\n",
        "\n",
        "df['PetalLengthAboveMean'] = df['PetalLength'] > df['PetalLength'].mean()\n",
        "df['PetalWidthAboveMean'] = df['PetalWidth'] > df['PetalWidth'].mean()\n",
        "\n",
        "df.head()"
      ],
      "id": "jJNX8-mzjR8-",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   SepalLength  SepalWidth  PetalLength  PetalWidth        Class  SepalArea  \\\n",
              "0          5.1         3.5          1.4         0.2  Iris-setosa      17.85   \n",
              "1          4.9         3.0          1.4         0.2  Iris-setosa      14.70   \n",
              "2          4.7         3.2          1.3         0.2  Iris-setosa      15.04   \n",
              "3          4.6         3.1          1.5         0.2  Iris-setosa      14.26   \n",
              "4          5.0         3.6          1.4         0.2  Iris-setosa      18.00   \n",
              "\n",
              "   PetalArea  SepalLengthAboveMean  SepalWidthAboveMean  PetalLengthAboveMean  \\\n",
              "0       0.28                 False                 True                 False   \n",
              "1       0.28                 False                False                 False   \n",
              "2       0.26                 False                 True                 False   \n",
              "3       0.30                 False                 True                 False   \n",
              "4       0.28                 False                 True                 False   \n",
              "\n",
              "   PetalWidthAboveMean  \n",
              "0                False  \n",
              "1                False  \n",
              "2                False  \n",
              "3                False  \n",
              "4                False  "
            ],
            "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>SepalLength</th>\n",
              "      <th>SepalWidth</th>\n",
              "      <th>PetalLength</th>\n",
              "      <th>PetalWidth</th>\n",
              "      <th>Class</th>\n",
              "      <th>SepalArea</th>\n",
              "      <th>PetalArea</th>\n",
              "      <th>SepalLengthAboveMean</th>\n",
              "      <th>SepalWidthAboveMean</th>\n",
              "      <th>PetalLengthAboveMean</th>\n",
              "      <th>PetalWidthAboveMean</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>5.1</td>\n",
              "      <td>3.5</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "      <td>17.85</td>\n",
              "      <td>0.28</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4.9</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "      <td>14.70</td>\n",
              "      <td>0.28</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>4.7</td>\n",
              "      <td>3.2</td>\n",
              "      <td>1.3</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "      <td>15.04</td>\n",
              "      <td>0.26</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4.6</td>\n",
              "      <td>3.1</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "      <td>14.26</td>\n",
              "      <td>0.30</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5.0</td>\n",
              "      <td>3.6</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "      <td>18.00</td>\n",
              "      <td>0.28</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "sX36TK1OjR8_",
        "outputId": "8ccde6b5-b083-4184-f982-9fe2f813791b"
      },
      "source": [
        "#TESTES\n",
        "features = df.columns.difference(['Class'])\n",
        "\n",
        "X = df[features].values\n",
        "y = df['Class'].values\n",
        "\n",
        "print(features)\n"
      ],
      "id": "sX36TK1OjR8_",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Index(['PetalArea', 'PetalLength', 'PetalLengthAboveMean', 'PetalWidth',\n",
            "       'PetalWidthAboveMean', 'SepalArea', 'SepalLength',\n",
            "       'SepalLengthAboveMean', 'SepalWidth', 'SepalWidthAboveMean'],\n",
            "      dtype='object')\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": true,
        "jupyter": {
          "outputs_hidden": true
        },
        "trusted": true,
        "id": "eXWhCfPCjR9A",
        "outputId": "194aaf24-54f0-4d1a-a578-ab844bb8998c"
      },
      "source": [
        "from sklearn.tree import DecisionTreeClassifier\n",
        "\n",
        "classifier_dt = DecisionTreeClassifier(random_state=1986, criterion='gini', max_depth=3)\n",
        "classifier_dt.fit(X, y)"
      ],
      "id": "eXWhCfPCjR9A",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/linear_model/least_angle.py:30: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  method='lar', copy_X=True, eps=np.finfo(np.float).eps,\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/linear_model/least_angle.py:167: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  method='lar', copy_X=True, eps=np.finfo(np.float).eps,\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/linear_model/least_angle.py:284: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  eps=np.finfo(np.float).eps, copy_Gram=True, verbose=0,\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/linear_model/least_angle.py:862: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  eps=np.finfo(np.float).eps, copy_X=True, fit_path=True,\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/linear_model/least_angle.py:1101: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  eps=np.finfo(np.float).eps, copy_X=True, fit_path=True,\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/linear_model/least_angle.py:1127: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  eps=np.finfo(np.float).eps, positive=False):\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/linear_model/least_angle.py:1362: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  max_n_alphas=1000, n_jobs=None, eps=np.finfo(np.float).eps,\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/linear_model/least_angle.py:1602: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  max_n_alphas=1000, n_jobs=None, eps=np.finfo(np.float).eps,\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/linear_model/least_angle.py:1738: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  eps=np.finfo(np.float).eps, copy_X=True, positive=False):\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/decomposition/online_lda.py:29: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  EPS = np.finfo(np.float).eps\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=3,\n",
              "                       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=False,\n",
              "                       random_state=1986, splitter='best')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "_Vso3opojR9A",
        "outputId": "72364038-10de-44e0-c828-9e0f18a19236"
      },
      "source": [
        "sample1 = [1.0, 2.0, 3.5, 1.0, 10.0, 3.5, False, False, False, False]  # Iris-setosa\n",
        "sample2 = [5.0, 3.5, 1.3, 0.2, 17.8, 0.2, False, True, False, False]   # Iris-versicolo \n",
        "\n",
        "classifier_dt.predict([sample1, sample2])  # Predizendo o tipo da flor"
      ],
      "id": "_Vso3opojR9A",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Iris-setosa', 'Iris-versicolor'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": true,
        "jupyter": {
          "outputs_hidden": true
        },
        "trusted": true,
        "id": "R2s4UXAdjR9B",
        "outputId": "56960384-0f74-43cf-f09c-7ae93923a8f8"
      },
      "source": [
        "from sklearn.model_selection import cross_val_score\n",
        "\n",
        "scores_dt = cross_val_score(classifier_dt, X, y, scoring='accuracy', cv=5)\n",
        "print(scores_dt.mean())"
      ],
      "id": "R2s4UXAdjR9B",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "1.0\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/model_selection/_split.py:670: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  test_folds = np.zeros(n_samples, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/model_selection/_split.py:442: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  fold_sizes = np.full(n_splits, n_samples // n_splits, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/model_selection/_split.py:102: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  test_mask = np.zeros(_num_samples(X), dtype=np.bool)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/model_selection/_split.py:442: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  fold_sizes = np.full(n_splits, n_samples // n_splits, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/model_selection/_split.py:102: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  test_mask = np.zeros(_num_samples(X), dtype=np.bool)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/model_selection/_split.py:102: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  test_mask = np.zeros(_num_samples(X), dtype=np.bool)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/model_selection/_split.py:102: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  test_mask = np.zeros(_num_samples(X), dtype=np.bool)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/model_selection/_split.py:102: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  test_mask = np.zeros(_num_samples(X), dtype=np.bool)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/model_selection/_split.py:102: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  test_mask = np.zeros(_num_samples(X), dtype=np.bool)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/model_selection/_split.py:102: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  test_mask = np.zeros(_num_samples(X), dtype=np.bool)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/model_selection/_split.py:102: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  test_mask = np.zeros(_num_samples(X), dtype=np.bool)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/model_selection/_split.py:102: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  test_mask = np.zeros(_num_samples(X), dtype=np.bool)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/model_selection/_split.py:102: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  test_mask = np.zeros(_num_samples(X), dtype=np.bool)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "jupyter": {
          "outputs_hidden": true
        },
        "trusted": true,
        "id": "sTv-teqSjR9C"
      },
      "source": [
        "from sklearn.ensemble import RandomForestClassifier\n",
        "\n",
        "classifier_rf = RandomForestClassifier(random_state=1986, n_estimators=50, max_depth=5, n_jobs=-1)\n",
        "classifier_rf.fit(X, y)\n",
        "\n",
        "scores_rf = cross_val_score(classifier_rf, X, y, scoring='accuracy', cv=5)\n",
        "print(scores_rf.mean())"
      ],
      "id": "sTv-teqSjR9C",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "collapsed": true,
        "jupyter": {
          "outputs_hidden": true
        },
        "trusted": true,
        "id": "h0sdLYkZjR9D",
        "outputId": "4ad0a58c-73b8-42a7-8f5c-29f27376ce24"
      },
      "source": [
        "classifier_rf.fit(X, y)\n",
        "\n",
        "features_importance = zip(classifier_rf.feature_importances_, features)\n",
        "for importance, feature in sorted(features_importance, reverse=True):\n",
        "    print(\"%s: %f%%\" % (feature, importance*100))"
      ],
      "id": "h0sdLYkZjR9D",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "PetalLengthAboveMean: 30.000000%\n",
            "PetalLength: 22.000000%\n",
            "PetalWidth: 20.424785%\n",
            "PetalArea: 18.000000%\n",
            "PetalWidthAboveMean: 8.000000%\n",
            "SepalLengthAboveMean: 1.216738%\n",
            "SepalWidth: 0.358477%\n",
            "SepalWidthAboveMean: 0.000000%\n",
            "SepalLength: 0.000000%\n",
            "SepalArea: 0.000000%\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/ensemble/forest.py:489: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_store_unique_indices = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n",
            "/srv/conda/envs/notebook/lib/python3.7/site-packages/sklearn/tree/tree.py:163: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
            "  y_encoded = np.zeros(y.shape, dtype=np.int)\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lVaPF_pbjR9E"
      },
      "source": [
        ""
      ],
      "id": "lVaPF_pbjR9E",
      "execution_count": null,
      "outputs": []
    }
  ]
}