cap5_intro_ml_classificacao.ipynb

{
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  "metadata": {
    "colab": {
      "name": "fundamentos_de_dados.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/viniciusrpb/datavis_book/blob/main/cap5_intro_ml_classificacao.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "L734mw7irzVE"
      },
      "source": [
        "Importar as bibliotecas do Pandas, Numpy, Sklearn"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ytZpjkxbfJKA"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "from sklearn import preprocessing\n",
        "from sklearn.svm import SVC\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import classification_report\n",
        "from sklearn.neural_network import MLPClassifier\n",
        "\n",
        "#from sklearn.preprocessing import MinMaxScaler"
      ],
      "execution_count": 81,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Bw3HDDi0sBB8"
      },
      "source": [
        "**Leitura do conjunto de dados**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_sPYK5cmprDt"
      },
      "source": [
        "rawData = pd.read_csv(\"sample_data/students2.csv\")"
      ],
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wqNW4kZPoslv"
      },
      "source": [
        "Atributos e seus valores no conjunto de dados:"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "w4KZ6xFZobbi"
      },
      "source": [
        "Performance {'Excellent','Vg','Good','Average'}\n",
        "Gender {'male','female'}\n",
        "Caste {'General','OBC','SC','ST'}\n",
        "coaching {'NO','WA','OA'}\n",
        "time {'ONE','TWO','THREE','FOUR','FIVE','SEVEN'}\n",
        "Class_ten_education {'SEBA','OTHERS','CBSE'}\n",
        "twelve_education {'AHSEC','CBSE','OTHERS'}\n",
        "medium' {'ENGLISH','OTHERS','ASSAMESE'}\n",
        "Class_ X_Percentage {'Excellent','Vg','Good','Average'}\n",
        "Class_XII_Percentage {'Excellent','Vg','Good','Average'}\n",
        "Father_occupation {'DOCTOR','SCHOOL_TEACHER','BUSINESS','COLLEGE_TEACHER','OTHERS','BANK_OFFICIAL','ENGINEER','CULTIVATOR'}\n",
        "Mother_occupation {'OTHERS','HOUSE_WIFE','SCHOOL_TEACHER','DOCTOR','COLLEGE_TEACHER','BANK_OFFICIAL','BUSINESS','CULTIVATOR','ENGINEER'}"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3vRTCZSfloh8",
        "outputId": "78ff92c9-d2f0-41ae-c3d1-2192c399bc8f"
      },
      "source": [
        "print(rawData.head())"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "  Performance Gender  ... Father_occupation Mother_occupation\n",
            "0   Excellent   male  ...            DOCTOR            OTHERS\n",
            "1   Excellent   male  ...    SCHOOL_TEACHER        HOUSE_WIFE\n",
            "2   Excellent   male  ...          BUSINESS        HOUSE_WIFE\n",
            "3   Excellent   male  ...    SCHOOL_TEACHER    SCHOOL_TEACHER\n",
            "4   Excellent   male  ...   COLLEGE_TEACHER        HOUSE_WIFE\n",
            "\n",
            "[5 rows x 12 columns]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6ci7XS3W4OQk"
      },
      "source": [
        "Verificar a quantidade de instâncias e atributos"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YvYR-rcWns7Q",
        "outputId": "3b137052-0d3b-422d-afb5-57a931cea1a6"
      },
      "source": [
        "print(rawData.shape)"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(666, 12)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xLhlUFBl4d_K"
      },
      "source": [
        "Remover instâncias com valores ausentes"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kTkccPWt4grw"
      },
      "source": [
        "rawData = rawData.replace('?',np.NaN)\n",
        "rawData = rawData.dropna(axis=0)"
      ],
      "execution_count": 46,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8rIl98I8vHt9"
      },
      "source": [
        "Ver os atributos do conjunto de dados"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EDXpPUTfuDbz"
      },
      "source": [
        "attributes = rawData.columns"
      ],
      "execution_count": 47,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GGtZF3EQE3ID"
      },
      "source": [
        "Ver os valores do atributo 'Performance'"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J0IjDPOsE2dy",
        "outputId": "0b58e0f2-d4cc-4c2b-846e-676da9a76472",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "print(rawData['Performance'].value_counts())"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Good         210\n",
            "Vg           198\n",
            "Average      157\n",
            "Excellent    101\n",
            "Name: Performance, dtype: int64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CjfJa_LxFWR5"
      },
      "source": [
        "Reservar o atributo de label"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "59YTncyeFR7R"
      },
      "source": [
        "label = rawData['Performance']\n",
        "\n"
      ],
      "execution_count": 49,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JRWh_cFA5j1u"
      },
      "source": [
        "Verificar os valores e suas frequências no atributo 'time'"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YO-fClc75ltu",
        "outputId": "701f7d18-3a26-4fba-ce09-87975842c47f"
      },
      "source": [
        "print(rawData['time'].value_counts())"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "TWO      368\n",
            "ONE      199\n",
            "THREE     86\n",
            "FOUR      11\n",
            "FIVE       1\n",
            "SEVEN      1\n",
            "Name: time, dtype: int64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Np_faz_Nv_1p"
      },
      "source": [
        "Converte atributos categórico ordinal para numérico (inteiro)\n",
        "\n",
        "---\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KGruMhtRwGTw"
      },
      "source": [
        "#converte atributo time de objeto para categórico\n",
        "rawData['time'] = pd.Categorical(rawData['time'])\n",
        "\n",
        "rawData['time_num'] = rawData['time'].cat.codes"
      ],
      "execution_count": 51,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BPWkvrIj64SR",
        "outputId": "645069a5-11ff-4565-d425-25d8dccfd431"
      },
      "source": [
        "print(rawData.head())\n",
        "\n",
        "rawData = rawData.drop(['time','Performance'],axis=1)"
      ],
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "  Performance Gender    Caste  ... Father_occupation Mother_occupation time_num\n",
            "0   Excellent   male  General  ...            DOCTOR            OTHERS        2\n",
            "1   Excellent   male      OBC  ...    SCHOOL_TEACHER        HOUSE_WIFE        5\n",
            "2   Excellent   male      OBC  ...          BUSINESS        HOUSE_WIFE        5\n",
            "3   Excellent   male  General  ...    SCHOOL_TEACHER    SCHOOL_TEACHER        2\n",
            "4   Excellent   male  General  ...   COLLEGE_TEACHER        HOUSE_WIFE        5\n",
            "\n",
            "[5 rows x 13 columns]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zPYyxxn67Hw5",
        "outputId": "9285aa3a-e915-4de0-f87e-2d788180043c"
      },
      "source": [
        "print(rawData.head())"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "  Gender    Caste coaching  ... Father_occupation Mother_occupation time_num\n",
            "0   male  General       NO  ...            DOCTOR            OTHERS        2\n",
            "1   male      OBC       WA  ...    SCHOOL_TEACHER        HOUSE_WIFE        5\n",
            "2   male      OBC       OA  ...          BUSINESS        HOUSE_WIFE        5\n",
            "3   male  General       WA  ...    SCHOOL_TEACHER    SCHOOL_TEACHER        2\n",
            "4   male  General       OA  ...   COLLEGE_TEACHER        HOUSE_WIFE        5\n",
            "\n",
            "[5 rows x 11 columns]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "htp8q20W7OJe"
      },
      "source": [
        "Conversão de um atributo nominal para atributo binário (dummy variables)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TfmUEY_s7TJm",
        "outputId": "72b7807c-b15a-426a-acc1-34e08cf0cc98"
      },
      "source": [
        "rawData = pd.get_dummies(rawData)\n",
        "\n",
        "print(rawData.head())"
      ],
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "   time_num  ...  Mother_occupation_SCHOOL_TEACHER\n",
            "0         2  ...                                 0\n",
            "1         5  ...                                 0\n",
            "2         5  ...                                 0\n",
            "3         2  ...                                 1\n",
            "4         5  ...                                 0\n",
            "\n",
            "[5 rows x 44 columns]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 438
        },
        "id": "wDpLXKpk7rhF",
        "outputId": "55eeb988-d6ac-477c-fa97-8fb78cf782d9"
      },
      "source": [
        "rawData"
      ],
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "execute_result",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>661</th>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</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>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>662</th>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>663</th>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>664</th>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>665</th>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>666 rows × 44 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     time_num  ...  Mother_occupation_SCHOOL_TEACHER\n",
              "0           2  ...                                 0\n",
              "1           5  ...                                 0\n",
              "2           5  ...                                 0\n",
              "3           2  ...                                 1\n",
              "4           5  ...                                 0\n",
              "..        ...  ...                               ...\n",
              "661         2  ...                                 0\n",
              "662         4  ...                                 0\n",
              "663         5  ...                                 1\n",
              "664         4  ...                                 0\n",
              "665         2  ...                                 0\n",
              "\n",
              "[666 rows x 44 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xtafje1V8TWD",
        "outputId": "36aacca7-8edd-4159-f13e-c776904dd848"
      },
      "source": [
        "X = rawData.values\n",
        "\n",
        "print(X)"
      ],
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[2 0 1 ... 0 1 0]\n",
            " [5 0 1 ... 1 0 0]\n",
            " [5 0 1 ... 1 0 0]\n",
            " ...\n",
            " [5 0 1 ... 0 0 1]\n",
            " [4 0 1 ... 1 0 0]\n",
            " [2 1 0 ... 0 1 0]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 438
        },
        "id": "z46Ed1cX9faj",
        "outputId": "cd82e4df-15f3-4cab-e2e5-56f55186d00f"
      },
      "source": [
        "attributes_dummies = rawData.columns\n",
        "\n",
        "normalize = preprocessing.MinMaxScaler()\n",
        "xscaled = normalize.fit_transform(X)\n",
        "\n",
        "dados_tratados = pd.DataFrame(xscaled,columns=attributes_dummies)\n",
        "\n",
        "dados_tratados"
      ],
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>time_num</th>\n",
              "      <th>Gender_female</th>\n",
              "      <th>Gender_male</th>\n",
              "      <th>Caste_General</th>\n",
              "      <th>Caste_OBC</th>\n",
              "      <th>Caste_SC</th>\n",
              "      <th>Caste_ST</th>\n",
              "      <th>coaching_NO</th>\n",
              "      <th>coaching_OA</th>\n",
              "      <th>coaching_WA</th>\n",
              "      <th>Class_ten_education_CBSE</th>\n",
              "      <th>Class_ten_education_OTHERS</th>\n",
              "      <th>Class_ten_education_SEBA</th>\n",
              "      <th>twelve_education_AHSEC</th>\n",
              "      <th>twelve_education_CBSE</th>\n",
              "      <th>twelve_education_OTHERS</th>\n",
              "      <th>medium_ASSAMESE</th>\n",
              "      <th>medium_ENGLISH</th>\n",
              "      <th>medium_OTHERS</th>\n",
              "      <th>Class_ X_Percentage_Average</th>\n",
              "      <th>Class_ X_Percentage_Excellent</th>\n",
              "      <th>Class_ X_Percentage_Good</th>\n",
              "      <th>Class_ X_Percentage_Vg</th>\n",
              "      <th>Class_ XII_Percentage_Average</th>\n",
              "      <th>Class_ XII_Percentage_Excellent</th>\n",
              "      <th>Class_ XII_Percentage_Good</th>\n",
              "      <th>Class_ XII_Percentage_Vg</th>\n",
              "      <th>Father_occupation_BANK_OFFICIAL</th>\n",
              "      <th>Father_occupation_BUSINESS</th>\n",
              "      <th>Father_occupation_COLLEGE_TEACHER</th>\n",
              "      <th>Father_occupation_CULTIVATOR</th>\n",
              "      <th>Father_occupation_DOCTOR</th>\n",
              "      <th>Father_occupation_ENGINEER</th>\n",
              "      <th>Father_occupation_OTHERS</th>\n",
              "      <th>Father_occupation_SCHOOL_TEACHER</th>\n",
              "      <th>Mother_occupation_BANK_OFFICIAL</th>\n",
              "      <th>Mother_occupation_BUSINESS</th>\n",
              "      <th>Mother_occupation_COLLEGE_TEACHER</th>\n",
              "      <th>Mother_occupation_CULTIVATOR</th>\n",
              "      <th>Mother_occupation_DOCTOR</th>\n",
              "      <th>Mother_occupation_ENGINEER</th>\n",
              "      <th>Mother_occupation_HOUSE_WIFE</th>\n",
              "      <th>Mother_occupation_OTHERS</th>\n",
              "      <th>Mother_occupation_SCHOOL_TEACHER</th>\n",
              "    </tr>\n",
              "  </thead>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.4</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>661</th>\n",
              "      <td>0.4</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>662</th>\n",
              "      <td>0.8</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>663</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>664</th>\n",
              "      <td>0.8</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>665</th>\n",
              "      <td>0.4</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>666 rows × 44 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     time_num  ...  Mother_occupation_SCHOOL_TEACHER\n",
              "0         0.4  ...                               0.0\n",
              "1         1.0  ...                               0.0\n",
              "2         1.0  ...                               0.0\n",
              "3         0.4  ...                               1.0\n",
              "4         1.0  ...                               0.0\n",
              "..        ...  ...                               ...\n",
              "661       0.4  ...                               0.0\n",
              "662       0.8  ...                               0.0\n",
              "663       1.0  ...                               1.0\n",
              "664       0.8  ...                               0.0\n",
              "665       0.4  ...                               0.0\n",
              "\n",
              "[666 rows x 44 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "89yZ1rfyF4ak",
        "outputId": "9f50029a-0285-47c5-f94e-03e6b424e3bb",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        ""
      ],
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "0      Excellent\n",
            "1      Excellent\n",
            "2      Excellent\n",
            "3      Excellent\n",
            "4      Excellent\n",
            "         ...    \n",
            "661      Average\n",
            "662      Average\n",
            "663      Average\n",
            "664      Average\n",
            "665      Average\n",
            "Name: Performance, Length: 666, dtype: object\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9us2e2nCGAV0"
      },
      "source": [
        "Estratégia de avaliação dos classificadores: Holdout Cross Validation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iEY_n80kF-br"
      },
      "source": [
        "X = dados_tratados.values;\n",
        "y = label.values;\n",
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=42)"
      ],
      "execution_count": 62,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "n70Z5EbWF-sr"
      },
      "source": [
        "Classificador SVM: criação do classificador e treinamento"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3cWGYHk5HMK2",
        "outputId": "e4059621-506c-4bec-c760-37acd1451ef5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "clfsvm = SVC(kernel=\"rbf\",gamma='scale',C=1)\n",
        "\n",
        "clfsvm.fit(X_train,y_train)"
      ],
      "execution_count": 78,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "SVC(C=1, break_ties=False, cache_size=200, class_weight=None, coef0=0.0,\n",
              "    decision_function_shape='ovr', degree=3, gamma='scale', kernel='rbf',\n",
              "    max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
              "    tol=0.001, verbose=False)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 78
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9DnRLzaYH7Vd"
      },
      "source": [
        "Realiza os testes"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BMHbZ7mZH77x"
      },
      "source": [
        "y_classificados = clfsvm.predict(X_test)"
      ],
      "execution_count": 79,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Xo0dXc4aILcA"
      },
      "source": [
        "Análise da performance do classificador"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GwwFA7FbILko",
        "outputId": "d28c8c02-19e7-49d3-dcea-c0788aaf6497",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "print(classification_report(y_test,y_classificados))"
      ],
      "execution_count": 80,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "     Average       0.77      0.77      0.77        61\n",
            "   Excellent       1.00      0.02      0.04        51\n",
            "        Good       0.39      0.63      0.48        75\n",
            "          Vg       0.42      0.44      0.43        80\n",
            "\n",
            "    accuracy                           0.49       267\n",
            "   macro avg       0.64      0.46      0.43       267\n",
            "weighted avg       0.60      0.49      0.45       267\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ahq-0IflJ0D7"
      },
      "source": [
        ""
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Zj6m6mzLJ0P6",
        "outputId": "c1877c11-6631-4a3a-8ebf-d6922045b98f",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "clfmlp = MLPClassifier(random_state=1, max_iter=300,hidden_layer_sizes=(10,10))\n",
        "\n",
        "clfmlp.fit(X_train,y_train)"
      ],
      "execution_count": 88,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:571: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (300) reached and the optimization hasn't converged yet.\n",
            "  % self.max_iter, ConvergenceWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "MLPClassifier(activation='relu', alpha=0.0001, batch_size='auto', beta_1=0.9,\n",
              "              beta_2=0.999, early_stopping=False, epsilon=1e-08,\n",
              "              hidden_layer_sizes=(10, 10), learning_rate='constant',\n",
              "              learning_rate_init=0.001, max_fun=15000, max_iter=300,\n",
              "              momentum=0.9, n_iter_no_change=10, nesterovs_momentum=True,\n",
              "              power_t=0.5, random_state=1, shuffle=True, solver='adam',\n",
              "              tol=0.0001, validation_fraction=0.1, verbose=False,\n",
              "              warm_start=False)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 88
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4QgTaPKuJ8Ox"
      },
      "source": [
        "y_classif_mlp = clfmlp.predict(X_test)"
      ],
      "execution_count": 89,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N3vb9uHYKEBA",
        "outputId": "d1904b06-6fc8-4a2e-d37a-e4be2f9f19b2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "print(classification_report(y_test,y_classif_mlp))"
      ],
      "execution_count": 90,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "     Average       0.78      0.82      0.80        61\n",
            "   Excellent       0.67      0.08      0.14        51\n",
            "        Good       0.39      0.56      0.46        75\n",
            "          Vg       0.44      0.49      0.46        80\n",
            "\n",
            "    accuracy                           0.51       267\n",
            "   macro avg       0.57      0.49      0.47       267\n",
            "weighted avg       0.55      0.51      0.48       267\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}