Breast_Cancer.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {
        "id": "-Um3SV3OZcHM",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "009cf39e-7e65-4616-975d-28f5cd0718ef"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
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          ]
        }
      ],
      "source": [
        "# Installing dependencies\n",
        "!pip install numpy\n",
        "!pip install pandas\n",
        "!pip install matplotlib\n",
        "!pip install seaborn\n",
        "!pip install lazypredict"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 34,
      "metadata": {
        "id": "HMPFeUUaZ2mR"
      },
      "outputs": [],
      "source": [
        "# Importa los modulos\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib .pyplot\n",
        "import seaborn as sns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 35,
      "metadata": {
        "id": "ZaIpgW9QZ2iK",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b3a911ae-7e3d-4185-b9fc-9e1bc27f4bb5"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: kaggle in /usr/local/lib/python3.9/dist-packages (1.5.13)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.9/dist-packages (from kaggle) (4.65.0)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.9/dist-packages (from kaggle) (2.27.1)\n",
            "Requirement already satisfied: certifi in /usr/local/lib/python3.9/dist-packages (from kaggle) (2022.12.7)\n",
            "Requirement already satisfied: python-dateutil in /usr/local/lib/python3.9/dist-packages (from kaggle) (2.8.2)\n",
            "Requirement already satisfied: python-slugify in /usr/local/lib/python3.9/dist-packages (from kaggle) (8.0.1)\n",
            "Requirement already satisfied: urllib3 in /usr/local/lib/python3.9/dist-packages (from kaggle) (1.26.15)\n",
            "Requirement already satisfied: six>=1.10 in /usr/local/lib/python3.9/dist-packages (from kaggle) (1.16.0)\n",
            "Requirement already satisfied: text-unidecode>=1.3 in /usr/local/lib/python3.9/dist-packages (from python-slugify->kaggle) (1.3)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.9/dist-packages (from requests->kaggle) (3.4)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.9/dist-packages (from requests->kaggle) (2.0.12)\n",
            "mkdir: cannot create directory ‘/root/.kaggle’: File exists\n",
            "cp: cannot stat 'kaggle.json': No such file or directory\n"
          ]
        }
      ],
      "source": [
        "# Installing the kaggle library\n",
        "! pip install kaggle\n",
        "#Making a directory \n",
        "! mkdir ~/.kaggle\n",
        "# copy the \"kaggle.json\" \n",
        "!cp kaggle.json ~/.kaggle/\n",
        "# allocating the required permision for this file\n",
        "! chmod 600 ~/.kaggle/kaggle.json\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 36,
      "metadata": {
        "id": "h-D1OzJebUzH",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "da588b98-6d0a-4594-d454-cddb3d7df0f8"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "breast-cancer-wisconsin-data.zip: Skipping, found more recently modified local copy (use --force to force download)\n"
          ]
        }
      ],
      "source": [
        "#download the dataset\n",
        "! kaggle datasets download uciml/breast-cancer-wisconsin-data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 37,
      "metadata": {
        "id": "cpRg77oLcXFs",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f98fb9d2-e60f-408d-e462-51e2a6fc1f9a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Archive:  /content/breast-cancer-wisconsin-data.zip\n",
            "replace data.csv? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "  inflating: data.csv                \n"
          ]
        }
      ],
      "source": [
        "!unzip /content/breast-cancer-wisconsin-data.zip"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 38,
      "metadata": {
        "id": "Uu4Vophrc5bS"
      },
      "outputs": [],
      "source": [
        "df = pd.read_csv('/content/data.csv')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 39,
      "metadata": {
        "id": "uVczVKSndFhJ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "outputId": "30cd094f-b019-447d-b3c5-668960711cc7"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         id diagnosis  radius_mean  texture_mean  perimeter_mean  area_mean  \\\n",
              "0    842302         M        17.99         10.38          122.80     1001.0   \n",
              "1    842517         M        20.57         17.77          132.90     1326.0   \n",
              "2  84300903         M        19.69         21.25          130.00     1203.0   \n",
              "3  84348301         M        11.42         20.38           77.58      386.1   \n",
              "4  84358402         M        20.29         14.34          135.10     1297.0   \n",
              "\n",
              "   smoothness_mean  compactness_mean  concavity_mean  concave points_mean  \\\n",
              "0          0.11840           0.27760          0.3001              0.14710   \n",
              "1          0.08474           0.07864          0.0869              0.07017   \n",
              "2          0.10960           0.15990          0.1974              0.12790   \n",
              "3          0.14250           0.28390          0.2414              0.10520   \n",
              "4          0.10030           0.13280          0.1980              0.10430   \n",
              "\n",
              "   ...  texture_worst  perimeter_worst  area_worst  smoothness_worst  \\\n",
              "0  ...          17.33           184.60      2019.0            0.1622   \n",
              "1  ...          23.41           158.80      1956.0            0.1238   \n",
              "2  ...          25.53           152.50      1709.0            0.1444   \n",
              "3  ...          26.50            98.87       567.7            0.2098   \n",
              "4  ...          16.67           152.20      1575.0            0.1374   \n",
              "\n",
              "   compactness_worst  concavity_worst  concave points_worst  symmetry_worst  \\\n",
              "0             0.6656           0.7119                0.2654          0.4601   \n",
              "1             0.1866           0.2416                0.1860          0.2750   \n",
              "2             0.4245           0.4504                0.2430          0.3613   \n",
              "3             0.8663           0.6869                0.2575          0.6638   \n",
              "4             0.2050           0.4000                0.1625          0.2364   \n",
              "\n",
              "   fractal_dimension_worst  Unnamed: 32  \n",
              "0                  0.11890          NaN  \n",
              "1                  0.08902          NaN  \n",
              "2                  0.08758          NaN  \n",
              "3                  0.17300          NaN  \n",
              "4                  0.07678          NaN  \n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>diagnosis</th>\n",
              "      <th>radius_mean</th>\n",
              "      <th>texture_mean</th>\n",
              "      <th>perimeter_mean</th>\n",
              "      <th>area_mean</th>\n",
              "      <th>smoothness_mean</th>\n",
              "      <th>compactness_mean</th>\n",
              "      <th>concavity_mean</th>\n",
              "      <th>concave points_mean</th>\n",
              "      <th>...</th>\n",
              "      <th>texture_worst</th>\n",
              "      <th>perimeter_worst</th>\n",
              "      <th>area_worst</th>\n",
              "      <th>smoothness_worst</th>\n",
              "      <th>compactness_worst</th>\n",
              "      <th>concavity_worst</th>\n",
              "      <th>concave points_worst</th>\n",
              "      <th>symmetry_worst</th>\n",
              "      <th>fractal_dimension_worst</th>\n",
              "      <th>Unnamed: 32</th>\n",
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              "      <th>0</th>\n",
              "      <td>842302</td>\n",
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              "      <td>17.99</td>\n",
              "      <td>10.38</td>\n",
              "      <td>122.80</td>\n",
              "      <td>1001.0</td>\n",
              "      <td>0.11840</td>\n",
              "      <td>0.27760</td>\n",
              "      <td>0.3001</td>\n",
              "      <td>0.14710</td>\n",
              "      <td>...</td>\n",
              "      <td>17.33</td>\n",
              "      <td>184.60</td>\n",
              "      <td>2019.0</td>\n",
              "      <td>0.1622</td>\n",
              "      <td>0.6656</td>\n",
              "      <td>0.7119</td>\n",
              "      <td>0.2654</td>\n",
              "      <td>0.4601</td>\n",
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              "      <td>842517</td>\n",
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              "      <td>20.57</td>\n",
              "      <td>17.77</td>\n",
              "      <td>132.90</td>\n",
              "      <td>1326.0</td>\n",
              "      <td>0.08474</td>\n",
              "      <td>0.07864</td>\n",
              "      <td>0.0869</td>\n",
              "      <td>0.07017</td>\n",
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              "      <td>23.41</td>\n",
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              "      <td>19.69</td>\n",
              "      <td>21.25</td>\n",
              "      <td>130.00</td>\n",
              "      <td>1203.0</td>\n",
              "      <td>0.10960</td>\n",
              "      <td>0.15990</td>\n",
              "      <td>0.1974</td>\n",
              "      <td>0.12790</td>\n",
              "      <td>...</td>\n",
              "      <td>25.53</td>\n",
              "      <td>152.50</td>\n",
              "      <td>1709.0</td>\n",
              "      <td>0.1444</td>\n",
              "      <td>0.4245</td>\n",
              "      <td>0.4504</td>\n",
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              "      <td>20.38</td>\n",
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              "      <td>0.4000</td>\n",
              "      <td>0.1625</td>\n",
              "      <td>0.2364</td>\n",
              "      <td>0.07678</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 33 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c855d52b-3644-48be-8856-8a22a560cf55')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-c855d52b-3644-48be-8856-8a22a560cf55 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c855d52b-3644-48be-8856-8a22a560cf55');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ],
      "source": [
        "df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 40,
      "metadata": {
        "id": "VQFIEQhydKOg",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f8ceedac-8516-4837-8285-95f0502fe5da"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(569, 33)"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ],
      "source": [
        "# Checking the total rows and columns\n",
        "df.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 41,
      "metadata": {
        "id": "c5PKfWYVeWOj",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f2b9997c-b59c-4b67-f583-dc9c21d0d789"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 569 entries, 0 to 568\n",
            "Data columns (total 33 columns):\n",
            " #   Column                   Non-Null Count  Dtype  \n",
            "---  ------                   --------------  -----  \n",
            " 0   id                       569 non-null    int64  \n",
            " 1   diagnosis                569 non-null    object \n",
            " 2   radius_mean              569 non-null    float64\n",
            " 3   texture_mean             569 non-null    float64\n",
            " 4   perimeter_mean           569 non-null    float64\n",
            " 5   area_mean                569 non-null    float64\n",
            " 6   smoothness_mean          569 non-null    float64\n",
            " 7   compactness_mean         569 non-null    float64\n",
            " 8   concavity_mean           569 non-null    float64\n",
            " 9   concave points_mean      569 non-null    float64\n",
            " 10  symmetry_mean            569 non-null    float64\n",
            " 11  fractal_dimension_mean   569 non-null    float64\n",
            " 12  radius_se                569 non-null    float64\n",
            " 13  texture_se               569 non-null    float64\n",
            " 14  perimeter_se             569 non-null    float64\n",
            " 15  area_se                  569 non-null    float64\n",
            " 16  smoothness_se            569 non-null    float64\n",
            " 17  compactness_se           569 non-null    float64\n",
            " 18  concavity_se             569 non-null    float64\n",
            " 19  concave points_se        569 non-null    float64\n",
            " 20  symmetry_se              569 non-null    float64\n",
            " 21  fractal_dimension_se     569 non-null    float64\n",
            " 22  radius_worst             569 non-null    float64\n",
            " 23  texture_worst            569 non-null    float64\n",
            " 24  perimeter_worst          569 non-null    float64\n",
            " 25  area_worst               569 non-null    float64\n",
            " 26  smoothness_worst         569 non-null    float64\n",
            " 27  compactness_worst        569 non-null    float64\n",
            " 28  concavity_worst          569 non-null    float64\n",
            " 29  concave points_worst     569 non-null    float64\n",
            " 30  symmetry_worst           569 non-null    float64\n",
            " 31  fractal_dimension_worst  569 non-null    float64\n",
            " 32  Unnamed: 32              0 non-null      float64\n",
            "dtypes: float64(31), int64(1), object(1)\n",
            "memory usage: 146.8+ KB\n"
          ]
        }
      ],
      "source": [
        "# Columns and data types\n",
        "df.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 42,
      "metadata": {
        "id": "9_IW26tde99J",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f21f8198-990d-433c-96fa-201548300254"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id                           0\n",
              "diagnosis                    0\n",
              "radius_mean                  0\n",
              "texture_mean                 0\n",
              "perimeter_mean               0\n",
              "area_mean                    0\n",
              "smoothness_mean              0\n",
              "compactness_mean             0\n",
              "concavity_mean               0\n",
              "concave points_mean          0\n",
              "symmetry_mean                0\n",
              "fractal_dimension_mean       0\n",
              "radius_se                    0\n",
              "texture_se                   0\n",
              "perimeter_se                 0\n",
              "area_se                      0\n",
              "smoothness_se                0\n",
              "compactness_se               0\n",
              "concavity_se                 0\n",
              "concave points_se            0\n",
              "symmetry_se                  0\n",
              "fractal_dimension_se         0\n",
              "radius_worst                 0\n",
              "texture_worst                0\n",
              "perimeter_worst              0\n",
              "area_worst                   0\n",
              "smoothness_worst             0\n",
              "compactness_worst            0\n",
              "concavity_worst              0\n",
              "concave points_worst         0\n",
              "symmetry_worst               0\n",
              "fractal_dimension_worst      0\n",
              "Unnamed: 32                569\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ],
      "source": [
        "#2nd way to check null values\n",
        "df.isnull().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 43,
      "metadata": {
        "id": "T5BFtdOAfnG7"
      },
      "outputs": [],
      "source": [
        "# Drop the column with all missing values\n",
        "df = df.dropna(axis=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 44,
      "metadata": {
        "id": "dUa4TObrgc3w",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9611e826-febf-40d9-bc9e-1ce1849857c2"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(569, 32)"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ],
      "source": [
        "df.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 45,
      "metadata": {
        "id": "_WUk-ScJggM8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4c26b070-52ad-4232-824a-070af1d90872"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id                           int64\n",
              "diagnosis                   object\n",
              "radius_mean                float64\n",
              "texture_mean               float64\n",
              "perimeter_mean             float64\n",
              "area_mean                  float64\n",
              "smoothness_mean            float64\n",
              "compactness_mean           float64\n",
              "concavity_mean             float64\n",
              "concave points_mean        float64\n",
              "symmetry_mean              float64\n",
              "fractal_dimension_mean     float64\n",
              "radius_se                  float64\n",
              "texture_se                 float64\n",
              "perimeter_se               float64\n",
              "area_se                    float64\n",
              "smoothness_se              float64\n",
              "compactness_se             float64\n",
              "concavity_se               float64\n",
              "concave points_se          float64\n",
              "symmetry_se                float64\n",
              "fractal_dimension_se       float64\n",
              "radius_worst               float64\n",
              "texture_worst              float64\n",
              "perimeter_worst            float64\n",
              "area_worst                 float64\n",
              "smoothness_worst           float64\n",
              "compactness_worst          float64\n",
              "concavity_worst            float64\n",
              "concave points_worst       float64\n",
              "symmetry_worst             float64\n",
              "fractal_dimension_worst    float64\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ],
      "source": [
        "df.dtypes"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 46,
      "metadata": {
        "id": "Chm1tcSGgwpA",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "86b8d612-ede0-40ea-b01b-a7d1a3b8f05b"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "B    357\n",
              "M    212\n",
              "Name: diagnosis, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ],
      "source": [
        "# Count values of the column diagnosis \n",
        "df['diagnosis'].value_counts()  "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 47,
      "metadata": {
        "id": "u4ixrYx9hv7r",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 420
        },
        "outputId": "c732b0ec-9265-4d36-d545-316dac637561"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-47-495ef002befb>:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  df['diagnosis'] = pd.Categorical(df['diagnosis'])\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='diagnosis', ylabel='count'>"
            ]
          },
          "metadata": {},
          "execution_count": 47
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "# Convert diagnosis to a categorical type\n",
        "df['diagnosis'] = pd.Categorical(df['diagnosis'])\n",
        "\n",
        "# Create a count plot of diagnosis cases\n",
        "sns.countplot(data=df, x='diagnosis')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 48,
      "metadata": {
        "id": "z7g7J3ssiuU0"
      },
      "outputs": [],
      "source": [
        "# Used for transforming values to 0 and 1 (Y values only)\n",
        "from sklearn.preprocessing import LabelEncoder\n",
        "LabelEncoder_Y = LabelEncoder()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 49,
      "metadata": {
        "id": "Vf2zj6oCjC58"
      },
      "outputs": [],
      "source": [
        "# Categorical to Numerical\n",
        "df.iloc[:,1] = LabelEncoder_Y.fit_transform(df.iloc[:,1].values)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 50,
      "metadata": {
        "id": "TAfMAISMkji_",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "178c382c-c69f-4ab8-b218-25e7259c8b4e"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0,\n",
              "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1,\n",
              "       1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1,\n",
              "       0, 0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 1, 1, 1,\n",
              "       0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0,\n",
              "       0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 1, 0, 1,\n",
              "       1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,\n",
              "       0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0,\n",
              "       0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 1,\n",
              "       1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1,\n",
              "       0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0,\n",
              "       0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
              "       1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0,\n",
              "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0,\n",
              "       0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 1,\n",
              "       1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,\n",
              "       1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1,\n",
              "       0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0,\n",
              "       0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1,\n",
              "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0,\n",
              "       0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1,\n",
              "       0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,\n",
              "       0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 1, 0, 0,\n",
              "       0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,\n",
              "       0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
              "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0])"
            ]
          },
          "metadata": {},
          "execution_count": 50
        }
      ],
      "source": [
        "# Displaying column 1 (\"diagnosis\") values (now 0 and 1)\n",
        "df.iloc[:,1].values"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 51,
      "metadata": {
        "id": "E3PFhyfGky3O",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 920
        },
        "outputId": "7c81b17d-5a69-4e11-c657-7bd7c59a46c6"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.PairGrid at 0x7f06e43ea730>"
            ]
          },
          "metadata": {},
          "execution_count": 51
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 955.5x900 with 30 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "# Creation of pairplot (correlation of several variables)\n",
        "sns.pairplot(df.iloc[:,1:7], hue='diagnosis')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Generation of a Heatmap of the correlation between several variables with the color scheme 'YlGnBu', data annotated and expression in percentage.\n",
        "sns.heatmap(df.iloc[:,1:11].corr(), cmap= 'YlGnBu', annot=True, fmt= '.0%')"
      ],
      "metadata": {
        "id": "VUNjI5k0m30k",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 385
        },
        "outputId": "019a07ac-fb49-489b-f9f9-b0763521bd3a"
      },
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 52
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Feature Scalling \n",
        "# Splitting the data Sets in dependent / independent\n",
        "# Independiente = x\n",
        "X = df.iloc[:,2:31].values\n",
        "# Dependiente = y\n",
        "Y = df.iloc[:,1].values"
      ],
      "metadata": {
        "id": "e6ER_eBBtrTg"
      },
      "execution_count": 53,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Spliting the set 80:20\n",
        "from sklearn.model_selection import train_test_split\n",
        "X_train, X_test, Y_train, Y_test = train_test_split(X,Y, test_size = 0.2, random_state = 0)"
      ],
      "metadata": {
        "id": "FPH1HT8xu9Tv"
      },
      "execution_count": 54,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(X_train.shape)\n",
        "print(Y_train.shape)\n",
        "print(X_test.shape)\n",
        "print(Y_train.shape)"
      ],
      "metadata": {
        "id": "0CopKLoATrvC",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ac9ca74c-aab8-498b-e196-39be431f6165"
      },
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(455, 29)\n",
            "(455,)\n",
            "(114, 29)\n",
            "(455,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Preprocesamiento / Standardize features by removing the mean and scaling to unit variance.\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "sc = StandardScaler()\n",
        "X_train = sc.fit_transform(X_train)\n",
        "X_test = sc.fit_transform(X_test)"
      ],
      "metadata": {
        "id": "Qgq-j5XWwYjg"
      },
      "execution_count": 56,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Evaluate more models using lazypredict\n",
        "import lazypredict\n",
        "from lazypredict.Supervised import LazyClassifier\n",
        "clf = LazyClassifier(verbose=0,ignore_warnings=True, custom_metric=None)\n",
        "LP_models,predictions = clf.fit(X_train, X_test, Y_train, Y_test)\n",
        "LP_models"
      ],
      "metadata": {
        "id": "aHQDIZZm6xVX",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 944
        },
        "outputId": "1731407d-b33a-46c8-a93d-4e780512f1f5"
      },
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 29/29 [00:08<00:00,  3.58it/s]\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                               Accuracy  Balanced Accuracy  ROC AUC  F1 Score  \\\n",
              "Model                                                                           \n",
              "SVC                                0.98               0.98     0.98      0.98   \n",
              "BaggingClassifier                  0.98               0.98     0.98      0.98   \n",
              "RandomForestClassifier             0.97               0.97     0.97      0.97   \n",
              "AdaBoostClassifier                 0.96               0.96     0.96      0.96   \n",
              "PassiveAggressiveClassifier        0.96               0.96     0.96      0.96   \n",
              "LogisticRegression                 0.96               0.96     0.96      0.96   \n",
              "KNeighborsClassifier               0.96               0.96     0.96      0.96   \n",
              "ExtraTreeClassifier                0.96               0.95     0.95      0.96   \n",
              "XGBClassifier                      0.96               0.95     0.95      0.96   \n",
              "LinearSVC                          0.96               0.95     0.95      0.96   \n",
              "ExtraTreesClassifier               0.96               0.95     0.95      0.96   \n",
              "NuSVC                              0.96               0.95     0.95      0.96   \n",
              "CalibratedClassifierCV             0.96               0.95     0.95      0.96   \n",
              "Perceptron                         0.95               0.95     0.95      0.95   \n",
              "DecisionTreeClassifier             0.95               0.95     0.95      0.95   \n",
              "QuadraticDiscriminantAnalysis      0.94               0.94     0.94      0.94   \n",
              "LGBMClassifier                     0.95               0.94     0.94      0.95   \n",
              "NearestCentroid                    0.95               0.94     0.94      0.95   \n",
              "SGDClassifier                      0.94               0.94     0.94      0.94   \n",
              "RidgeClassifier                    0.95               0.94     0.94      0.95   \n",
              "RidgeClassifierCV                  0.95               0.94     0.94      0.95   \n",
              "GaussianNB                         0.94               0.94     0.94      0.94   \n",
              "LinearDiscriminantAnalysis         0.94               0.93     0.93      0.94   \n",
              "BernoulliNB                        0.92               0.92     0.92      0.92   \n",
              "LabelSpreading                     0.90               0.89     0.89      0.90   \n",
              "LabelPropagation                   0.90               0.89     0.89      0.90   \n",
              "DummyClassifier                    0.59               0.50     0.50      0.44   \n",
              "\n",
              "                               Time Taken  \n",
              "Model                                      \n",
              "SVC                                  0.05  \n",
              "BaggingClassifier                    0.41  \n",
              "RandomForestClassifier               0.65  \n",
              "AdaBoostClassifier                   0.38  \n",
              "PassiveAggressiveClassifier          0.05  \n",
              "LogisticRegression                   0.08  \n",
              "KNeighborsClassifier                 0.02  \n",
              "ExtraTreeClassifier                  0.01  \n",
              "XGBClassifier                        5.07  \n",
              "LinearSVC                            0.08  \n",
              "ExtraTreesClassifier                 0.18  \n",
              "NuSVC                                0.05  \n",
              "CalibratedClassifierCV               0.13  \n",
              "Perceptron                           0.03  \n",
              "DecisionTreeClassifier               0.02  \n",
              "QuadraticDiscriminantAnalysis        0.04  \n",
              "LGBMClassifier                       0.19  \n",
              "NearestCentroid                      0.08  \n",
              "SGDClassifier                        0.07  \n",
              "RidgeClassifier                      0.12  \n",
              "RidgeClassifierCV                    0.04  \n",
              "GaussianNB                           0.02  \n",
              "LinearDiscriminantAnalysis           0.06  \n",
              "BernoulliNB                          0.08  \n",
              "LabelSpreading                       0.05  \n",
              "LabelPropagation                     0.09  \n",
              "DummyClassifier                      0.01  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-87441f81-9d5e-412b-818e-cd4ec4a05259\">\n",
              "    <div class=\"colab-df-container\">\n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Accuracy</th>\n",
              "      <th>Balanced Accuracy</th>\n",
              "      <th>ROC AUC</th>\n",
              "      <th>F1 Score</th>\n",
              "      <th>Time Taken</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Model</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>SVC</th>\n",
              "      <td>0.98</td>\n",
              "      <td>0.98</td>\n",
              "      <td>0.98</td>\n",
              "      <td>0.98</td>\n",
              "      <td>0.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>BaggingClassifier</th>\n",
              "      <td>0.98</td>\n",
              "      <td>0.98</td>\n",
              "      <td>0.98</td>\n",
              "      <td>0.98</td>\n",
              "      <td>0.41</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RandomForestClassifier</th>\n",
              "      <td>0.97</td>\n",
              "      <td>0.97</td>\n",
              "      <td>0.97</td>\n",
              "      <td>0.97</td>\n",
              "      <td>0.65</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AdaBoostClassifier</th>\n",
              "      <td>0.96</td>\n",
              "      <td>0.96</td>\n",
              "      <td>0.96</td>\n",
              "      <td>0.96</td>\n",
              "      <td>0.38</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PassiveAggressiveClassifier</th>\n",
              "      <td>0.96</td>\n",
              "      <td>0.96</td>\n",
              "      <td>0.96</td>\n",
              "      <td>0.96</td>\n",
              "      <td>0.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LogisticRegression</th>\n",
              "      <td>0.96</td>\n",
              "      <td>0.96</td>\n",
              "      <td>0.96</td>\n",
              "      <td>0.96</td>\n",
              "      <td>0.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>KNeighborsClassifier</th>\n",
              "      <td>0.96</td>\n",
              "      <td>0.96</td>\n",
              "      <td>0.96</td>\n",
              "      <td>0.96</td>\n",
              "      <td>0.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ExtraTreeClassifier</th>\n",
              "      <td>0.96</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.96</td>\n",
              "      <td>0.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>XGBClassifier</th>\n",
              "      <td>0.96</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.96</td>\n",
              "      <td>5.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LinearSVC</th>\n",
              "      <td>0.96</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.96</td>\n",
              "      <td>0.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ExtraTreesClassifier</th>\n",
              "      <td>0.96</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.96</td>\n",
              "      <td>0.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>NuSVC</th>\n",
              "      <td>0.96</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.96</td>\n",
              "      <td>0.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CalibratedClassifierCV</th>\n",
              "      <td>0.96</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.96</td>\n",
              "      <td>0.13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Perceptron</th>\n",
              "      <td>0.95</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DecisionTreeClassifier</th>\n",
              "      <td>0.95</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>QuadraticDiscriminantAnalysis</th>\n",
              "      <td>0.94</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LGBMClassifier</th>\n",
              "      <td>0.95</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>NearestCentroid</th>\n",
              "      <td>0.95</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SGDClassifier</th>\n",
              "      <td>0.94</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RidgeClassifier</th>\n",
              "      <td>0.95</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RidgeClassifierCV</th>\n",
              "      <td>0.95</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.95</td>\n",
              "      <td>0.04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>GaussianNB</th>\n",
              "      <td>0.94</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LinearDiscriminantAnalysis</th>\n",
              "      <td>0.94</td>\n",
              "      <td>0.93</td>\n",
              "      <td>0.93</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>BernoulliNB</th>\n",
              "      <td>0.92</td>\n",
              "      <td>0.92</td>\n",
              "      <td>0.92</td>\n",
              "      <td>0.92</td>\n",
              "      <td>0.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LabelSpreading</th>\n",
              "      <td>0.90</td>\n",
              "      <td>0.89</td>\n",
              "      <td>0.89</td>\n",
              "      <td>0.90</td>\n",
              "      <td>0.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LabelPropagation</th>\n",
              "      <td>0.90</td>\n",
              "      <td>0.89</td>\n",
              "      <td>0.89</td>\n",
              "      <td>0.90</td>\n",
              "      <td>0.09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DummyClassifier</th>\n",
              "      <td>0.59</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.44</td>\n",
              "      <td>0.01</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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          },
          "metadata": {},
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(LP_models)"
      ],
      "metadata": {
        "id": "kEfz2C2uSLru",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "118f164e-df92-45bf-c079-610bc5d433cd"
      },
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                               Accuracy  Balanced Accuracy  ROC AUC  F1 Score  \\\n",
            "Model                                                                           \n",
            "SVC                                0.98               0.98     0.98      0.98   \n",
            "BaggingClassifier                  0.98               0.98     0.98      0.98   \n",
            "RandomForestClassifier             0.97               0.97     0.97      0.97   \n",
            "AdaBoostClassifier                 0.96               0.96     0.96      0.96   \n",
            "PassiveAggressiveClassifier        0.96               0.96     0.96      0.96   \n",
            "LogisticRegression                 0.96               0.96     0.96      0.96   \n",
            "KNeighborsClassifier               0.96               0.96     0.96      0.96   \n",
            "ExtraTreeClassifier                0.96               0.95     0.95      0.96   \n",
            "XGBClassifier                      0.96               0.95     0.95      0.96   \n",
            "LinearSVC                          0.96               0.95     0.95      0.96   \n",
            "ExtraTreesClassifier               0.96               0.95     0.95      0.96   \n",
            "NuSVC                              0.96               0.95     0.95      0.96   \n",
            "CalibratedClassifierCV             0.96               0.95     0.95      0.96   \n",
            "Perceptron                         0.95               0.95     0.95      0.95   \n",
            "DecisionTreeClassifier             0.95               0.95     0.95      0.95   \n",
            "QuadraticDiscriminantAnalysis      0.94               0.94     0.94      0.94   \n",
            "LGBMClassifier                     0.95               0.94     0.94      0.95   \n",
            "NearestCentroid                    0.95               0.94     0.94      0.95   \n",
            "SGDClassifier                      0.94               0.94     0.94      0.94   \n",
            "RidgeClassifier                    0.95               0.94     0.94      0.95   \n",
            "RidgeClassifierCV                  0.95               0.94     0.94      0.95   \n",
            "GaussianNB                         0.94               0.94     0.94      0.94   \n",
            "LinearDiscriminantAnalysis         0.94               0.93     0.93      0.94   \n",
            "BernoulliNB                        0.92               0.92     0.92      0.92   \n",
            "LabelSpreading                     0.90               0.89     0.89      0.90   \n",
            "LabelPropagation                   0.90               0.89     0.89      0.90   \n",
            "DummyClassifier                    0.59               0.50     0.50      0.44   \n",
            "\n",
            "                               Time Taken  \n",
            "Model                                      \n",
            "SVC                                  0.05  \n",
            "BaggingClassifier                    0.41  \n",
            "RandomForestClassifier               0.65  \n",
            "AdaBoostClassifier                   0.38  \n",
            "PassiveAggressiveClassifier          0.05  \n",
            "LogisticRegression                   0.08  \n",
            "KNeighborsClassifier                 0.02  \n",
            "ExtraTreeClassifier                  0.01  \n",
            "XGBClassifier                        5.07  \n",
            "LinearSVC                            0.08  \n",
            "ExtraTreesClassifier                 0.18  \n",
            "NuSVC                                0.05  \n",
            "CalibratedClassifierCV               0.13  \n",
            "Perceptron                           0.03  \n",
            "DecisionTreeClassifier               0.02  \n",
            "QuadraticDiscriminantAnalysis        0.04  \n",
            "LGBMClassifier                       0.19  \n",
            "NearestCentroid                      0.08  \n",
            "SGDClassifier                        0.07  \n",
            "RidgeClassifier                      0.12  \n",
            "RidgeClassifierCV                    0.04  \n",
            "GaussianNB                           0.02  \n",
            "LinearDiscriminantAnalysis           0.06  \n",
            "BernoulliNB                          0.08  \n",
            "LabelSpreading                       0.05  \n",
            "LabelPropagation                     0.09  \n",
            "DummyClassifier                      0.01  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#For the creation of the graph to evaluate the models x = model name from models´ variable names\n",
        "# https://seaborn.pydata.org/tutorial/color_palettes.html para cambiar el color\n",
        "# https://github.com/dataprofessor/python/blob/main/lazypredict.ipynb\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "plt.figure(figsize=(10, 5))\n",
        "sns.set_theme(style='whitegrid')\n",
        "ax = sns.barplot(x=LP_models.index, y=\"Accuracy\", data=LP_models, palette='flare')\n",
        "plt.xticks(rotation=90)"
      ],
      "metadata": {
        "id": "JhL0i_yyPgYe",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "dc7e58a6-57a0-45ee-825f-a2e333f60724"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,\n",
              "        17, 18, 19, 20, 21, 22, 23, 24, 25, 26]),\n",
              " [Text(0, 0, 'SVC'),\n",
              "  Text(1, 0, 'BaggingClassifier'),\n",
              "  Text(2, 0, 'RandomForestClassifier'),\n",
              "  Text(3, 0, 'AdaBoostClassifier'),\n",
              "  Text(4, 0, 'PassiveAggressiveClassifier'),\n",
              "  Text(5, 0, 'LogisticRegression'),\n",
              "  Text(6, 0, 'KNeighborsClassifier'),\n",
              "  Text(7, 0, 'ExtraTreeClassifier'),\n",
              "  Text(8, 0, 'XGBClassifier'),\n",
              "  Text(9, 0, 'LinearSVC'),\n",
              "  Text(10, 0, 'ExtraTreesClassifier'),\n",
              "  Text(11, 0, 'NuSVC'),\n",
              "  Text(12, 0, 'CalibratedClassifierCV'),\n",
              "  Text(13, 0, 'Perceptron'),\n",
              "  Text(14, 0, 'DecisionTreeClassifier'),\n",
              "  Text(15, 0, 'QuadraticDiscriminantAnalysis'),\n",
              "  Text(16, 0, 'LGBMClassifier'),\n",
              "  Text(17, 0, 'NearestCentroid'),\n",
              "  Text(18, 0, 'SGDClassifier'),\n",
              "  Text(19, 0, 'RidgeClassifier'),\n",
              "  Text(20, 0, 'RidgeClassifierCV'),\n",
              "  Text(21, 0, 'GaussianNB'),\n",
              "  Text(22, 0, 'LinearDiscriminantAnalysis'),\n",
              "  Text(23, 0, 'BernoulliNB'),\n",
              "  Text(24, 0, 'LabelSpreading'),\n",
              "  Text(25, 0, 'LabelPropagation'),\n",
              "  Text(26, 0, 'DummyClassifier')])"
            ]
          },
          "metadata": {},
          "execution_count": 59
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ],
            "image/png": 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rgd8Bqzc2OzMzM7NJaNRlNoAnAs8GZgMbkrY3P9DAnMzMzMwmtREDNEnTgFeTgrLtgD8BpwFrAW+KiDubnqCZmZnZZLO4QwL/AI4FAnhORDwjIj4NPNT4zMzMzMwmqcUFaNcAjyNtbW4m6fGNz8jMzMxskhsxQIuIF5Iao59Lao5+h6QfAY8FpjU+OzMzM7NJaLF10CLi5oj4dESsB7wIuB14FLha0sFNT9DMzMxsshnkFCcRcSFwoaT3A68D3jra75W0PnAi6TTov4C3RsSNi/haAVcCR0fEhwaZo5mZmdlEV6lVU0T8LyJOi4iXDfBtXwWOioj1gaNIhw8WImlq/tz3q8zNzMzMbKIbk16aklYBNiWV6CB/3FTSyn2+fF9S14IbxmJuZmZmZm0z0BZnDWsCt0bEPICImCfptnz/XZ0vkrQRqd7a1sDHqvxD1113HbNmzao/Y2DOnDkL/l5izNLjTZQxJ8IcmxhzIsyxiTEnwhybGHMizLGJMSfCHJsYcyLMsYkxJ8IcmxiziTled911I35+rAK0xcpFcb8GvC0HcJXGmTlzZrE5lfolNDXeRBlzIsyxiTEnwhybGHMizLGJMSfCHJsYcyLMsYkxJ8IcmxhzIsyxiTGbmOPMmTNHDNLGZIsTuAVYI+eXdfLMVs/3d6xGKunxU0l/BfYC9pD0tTGao5mZmVkrjMkKWkTcKekqYCfglPzxyoi4q+tr/gas1Lkt6UBgOZ/iNDMzs8lmrFbQAN4F7CnpBmDPfBtJP5X0rDGch5mZmVmrjVkOWkT8kdQyqvf+ly/i6w9sek5mZmZmbTSWK2hmZmZmNgoO0MzMzMxaxgGamZmZWcs4QDMzMzNrGQdoZmZmZi3jAM3MzMysZRygmZmZmbWMAzQzMzOzlnGAZmZmZtYyDtDMzMzMWsYBmpmZmVnLOEAzMzMzaxkHaGZmZmYt4wDNzMzMrGUcoJmZmZm1jAM0MzMzs5ZxgGZmZmbWMg7QzMzMzFrGAZqZmZlZyzhAMzMzM2sZB2hmZmZmLeMAzczMzKxlHKCZmZmZtYwDNDMzM7OWcYBmZmZm1jIO0MzMzMxaxgGamZmZWcs4QDMzMzNrGQdoZmZmZi3jAM3MzMysZRygmZmZmbWMAzQzMzOzlnGAZmZmZtYyDtDMzMzMWsYBmpmZmVnLOEAzMzMzaxkHaGZmZmYt4wDNzMzMrGUcoJmZmZm1jAM0MzMzs5ZxgGZmZmbWMg7QzMzMzFrGAZqZmZlZyyw9Vv+QpPWBE4EnAv8C3hoRN/Z8zceAHYF5wMPAfhFxzljN0czMzKwNxnIF7avAURGxPnAUcGyfr/kdsFlEbAjsBpwu6TFjOEczMzOzcTcmAZqkVYBNgdPyXacBm0paufvrIuKciPhPvnkNMIW04mZmZmY2aYzVCtqawK0RMQ8gf7wt378obwX+HBF/H4P5mZmZmbXGmOWgDULSVsCngW0H/d7rrruOWbNmFZnHnDlzFvy9xJilx5soY06EOTYx5kSYYxNjToQ5NjHmRJhjE2NOhDk2MeZEmGMTY06EOTYxZhNzvO6660b8/FgFaLcAa0iaGhHzJE0FVs/3DyPpucApwGsiIgb9h2bOnFl7sh2lfglNjTdRxpwIc2xizIkwxybGnAhzbGLMiTDHJsacCHNsYsyJMMcmxpwIc2xizCbmOHPmzBGDtDHZ4oyIO4GrgJ3yXTsBV0bEXd1fJ2kz4HRg+4i4YizmZmZmZtY2Y7nF+S7gREkfB+4m5Zgh6afAxyPicuBo4DHAsZI63/eWiLh2DOdpZmZmNq7GLECLiD8Cz+5z/8u7/r7ZWM3HzMzMrK3cScDMzMysZRygmZmZmbWMAzQzMzOzlnGAZmZmZtYyDtDMzMzMWsYBmpmZmVnLOEAzMzMzaxkHaGZmZmYt4wDNzMzMrGUcoJmZmZm1jAM0MzMzs5ZxgGZmZmbWMg7QzMzMzFrGAZqZmZlZyzhAMzMzM2sZB2hmZmZmLeMAzczMzKxlHKCZmZmZtYwDNDMzM7OWcYBmZmZm1jIO0MzMzMxaxgGamZmZWcs4QDMzMzNrGQdoZmZmZi3jAM3MzMysZRygmZmZmbWMAzQzMzOzlnGAZmZmZtYyDtDMzMzMWsYBmpmZmVnLOEAzMzMzaxkHaGZmZmYt4wDNzMzMrGUcoJmZmZm1jAM0MzMzs5ZxgGZmZmbWMg7QzMzMzFrGAZqZmZlZyzhAMzMzM2sZB2hmZmZmLeMAzczMzKxlHKCZmZmZtYwDNDMzM7OWcYBmZmZm1jJLj9U/JGl94ETgicC/gLdGxI09XzMVOBx4KTAf+HxEHD9WczQzMzNrg7FcQfsqcFRErA8cBRzb52t2BtYF1gOeCxwoae0xm6GZmZlZC4zJCpqkVYBNgW3zXacBR0paOSLu6vrSHYDjIuJR4C5J3wfeCHxxFP/MVICHHnoIgHlLL1NrznPnzl3ovnnTqo/Zb7xHpz+m8niLHHPGsq0as+94yzy28niLHPMx5cecv2z1MfuO99jlKo+3qDFZroExl68+Zr/xpqxQfo5LrVD+9z11xbK/76VrjLeoMac9rvyY02uM2W+8GY8vP8dlGhjzMTXG7Dfesk8o/zh/bANjLldjzH7jLf/E5SuPN5ZjrlBjzH7jrVhgjp14hRy/9Joyf/78Wv/IaEiaBZwUERt03Xc9sEtEXNF137XAbhFxWb69D/DkiHj/4v6NOXPmvAC4oPjkzczMzJqzxaxZsy7svXPMctDGwGXAFsDtwLxxnouZmZnZSKYCq5Hil4WMVYB2C7CGpKkRMS8fBlg939/tb8D/MTTZtYCbR/MPzJo1ay6wUARqZmZm1lJ/XtQnxuSQQETcCVwF7JTv2gm4sif/DOBMYA9JS0laGXgt8J2xmKOZmZlZW4zlKc53AXtKugHYM99G0k8lPSt/zcnAX4AbgUuAT0XETWM4RzMzM7NxNyaHBMzMzMxs9NxJwMzMzKxlHKCZmZmZtYwDNDMzM7OWcYBmZmZm1jIO0MzMzMxaxgGamZmZWcs4QFuCSZoq6cfjPQ9bWP7dXLH4rzRbNEkrSFoq/32mpB0lTR/veTUpP3eOG+95mDVtiQ/QJL1A0uv63P96Sc+rOfaKdb6/z3hTJb2j1HgRMQ94YucFvITc5eHlpcZrSul55vE2LDVe/t08IGmZUmPmx8+yfe5fNrdXW+JI+pOk/SSt0eC/MT3/Hy7b7/93gHGKPoayXwGPkbQqcA7wNuBrVQebCM/v/Nwp+v/YwOvFFqXG6hpzFUnL579vKmlvSa8q/e+0VfdzsO5zsSmlY4IlqVn6ohwI7NHn/iuA44EXVxlU0hTgYuAZlWfWI/cpfQc1XmD7uAQ4S9KpwANd/9ZPqwwWEY9K+gxQ6fsXRZKAA4Cn0vW4jIjNq4xXep55vFMo+8YQwPmSvsPw383RFcf7fB7z+J77dwIE7DPogDmwuywiNq04p97xXg2sEBGn9Nz/FuCeiPjRgEO+HZgNXC/pt8A3gO9HxMMF5vo64AhSM2OAKcB8UoPjgTX0GJoSEQ9K2gk4LiIOlHRt1cFKP28kvWcx/17Vx/ovJR0JnMTw5871VQZr4HXtBEnzgG8CJ0bEbXUGk7Qn8DlgrqRPAf8PuBR4l6RnRcQnaoy9JXBFRDwgaXdgM+ALVbr45NeL1wN3R8QvJL0f2Ba4gdQZ6N6q8yT9nodV1pf0MPA7YI+IiArzXRZ4MsPfcyo9hpqICZb4FTRg+X4PtIj4K7By1UEjYj5wi6TH15hbP7+StH3B8TYGVgTeDXw4//lQzTGvklQpcBrBt4E/kIK0D3f9qaP0PP8kae2C4y0N/B54OulFcTPgWSN+x8i2IQUovb4JVFodaGCl78PAuX3u/xmw76CDRcSvI2I2sAapl+/7gdskHSZpozoTBb4IvAmYFhFTI2KpiKi7Eln6MbSMpBmkN8Hz8n3zao5Z8nnTeVy/jHQBsW3+83lguxrj7gi8Ajgd+En+Uzedo9jPHRFPBd4JPA34g6SfSHqDpKqLIu8CngJsDnwBeG5E7AhsCryx5nSPBB6UtAGwN/A34OsVxzoa2Av4gqQzgZeQfjerA8fWnOf+eX6PB55AClIPJr3mDTy2pPcC/wB+ToHHUBMxwWRYQXvCCJ+ru0R6L3ClpJ8y/Cpu4JWKLrOBvSX9F3iQfNUeEatUGSwitq4xl0WZBVwk6UaG/9x1XtyWiojP1Z7ZcKXnuTxwjaQLe8Z7U5XBIuJtFeexKFMj4tE+/86jkha6fwAlV/pmRMSdfeZ4l6TlKk8w4gHSC/U3JD2NtLLyPiqudmX/jojf1vj+foo+hkgByh2k/sUX5a3O/9WcY7HnTecxLuknwEadi2VJTwEOrzrBiHhK1e8dQdHXi4j4FemCezlSQPn/gKMlfSsiPjjgcA9FxD+Bf0r6U0Tckf+N+yXNrTK/Lo9ExHxJLwOOiYgjJFUN+rYANiC9t94GrBwRD0n6GnBNzXluHxGzum4fLmlORMyStHeF8fYGZkbEzTXn1a1oTDAZArSbJL04In7RfaekbYC6v5jf5z8l1VlBWUhedt0NWC8i9s1X76vXfON5f5HJDXexpA0jou6TuFvpeZ6S/xSRl9c/CqwTETvnwOJpEfH9ikM+RtKyEfGfnn9nOWBGjal2r/R1VG3iO9IF02MrjglA/v97G7ALcCvw3jrjAd+T9G5SELQg6On9/x1Q0cdQRHxS0uHAvTkQfwB4Q81hm3h+/1/3TkZE3JSDtMokvQh4ekQcKWkV4HERcUONIZv4uclbh18Hbiel3LwTGDRA636+9W7f122ovbSkZ5O2JjvpQFUvbObmlaQHJf0lIh6CBReJD9Wc57KS1omIv8CCIL/zmvFIhfHuKBycQeGYYDIEaPsDP5Z0PGnPHuDZpNyVWgmWEfHJmnPrN+bNklYA1o2IEqf8DgGeRFoK3xe4HziUtFRedY6/AZC0ckTcVWCOkH4nb5MUDH8zbM08I+LEumP0OIb0or1xvv134DTg+xXHOx04UdLuEXEfLEhaPZa0/VdJ4ZW+ayS9OSJO7b5T0o7AdYMOlp8rO5IuQtYGvgVsFxEDj9XHZ/PHo7ruq5yDBuUeQ5KekoOcTr7LaimNc4Fbq47d0PP7DkkfYyg/cjfSyl8lkvYlbduvRtqim05aQX1B1TGb+Llzbu1upIuG20jpBqeO+E39PVNSZ+X58V1/n0JKYanjY6TXiPMi4veS1gf+VHGsGZKenufV/XeAumkSBwC/kzQnj7kJKQdvOaq9vv1c0sGk9Jru95xKOWj5e4vGBEt8gBYRl0l6MSlB+rX57iuAbeuu1uSrtkOAtSJiS6UTWs+LiK/WGPPlpCfLPGBtSc8CPhERVYPJrUkP5CsAIuJfdfOJ8tXWGaQcxjXzHN8REXVOoO5VZ079lJ6npPVIL7BrRMRTJG0KvDoiDqw4xQ0jYldJ28GCK+06eaGfAk4Abs3bNADrAT8kXblXUnilb1/gN5JewfALpm2ArSqMdyvwa1Iuyg8josqVdF8RUTxHt+Bj6AjglaS8mV7zgXVqzLGJ5/dbSVua1+X5/TLfV9VOpN2G3wFExN9zsF5ZyZ9b6bDX20iHnr4FvKzm+826Nb53RBHxA+AHXbdvIK2mVbEsww9adP+91kpfRHw3pwZ0Ltov7UqXqJIe03n8dW/n1n3uFI0JlvgATdIWEXEB8JYGhj8OOBvonFT6I2n7onKABnySlFR7NkBEXC7pqTXG+1/OLwDScXKGrmiqOoSU9PutrjnWWhnounp9bL79YM05Qvl5HgN8hpTgDHAVcDLVg59huSM5cK4cFOTgZJccBGyc774yIqpeDXcUW+mLiBtyUPIehpLErwA+FBG3V5jbBsC/eh8vOaicG+mQQ2WSngg8J9+8OCL+XWc8Cj2GIuKV+WMTuVhNPL9vA0oefvpvRDzcs2pYd6uv5M/9WuBLpIuG2ieKG9iKQ9IbI+JMLeKkbZUc04hYu/bERh7/H5LOIccu/VI6BhiriedO0ZhgiQ/QGDru/A3ScecqbwKLskZEfFXSOwFyMmSdZGzyOHf0vPDUSQK9VtLOwJScf/ZR4IIa4wFMj4jre+ZYK79A0jqkpf+NgfmSrgR26eQbVFR6nitGxM8kHQRF8irOl7QfaSvghaS8lB+M/C2LJuk80umr70bEjYv7+gEUW+lTKqdxRkR8rNDc9qRwaZGO/POeQgqiIB1A2CUifl51TAo/hvJ21N8i4n95vpsAx0bE3TXmWOx5I+n5EXGRFlFjLCqW+yGdlnsB6bViKWA/6uf+lHy92AdYtTc4k7QtcOug22hKJyIXFYDOj4gdKsxxJmlrcLN+Y1YYr1GSXk9ahS1S9iaP+QzSLhOkLd4/1ppk4ZhgiQ/QIuKpkrYmnY78Y14i/QbwgwLbIcO+X9LjqL86db+kJ5GfIPmN+54a432QdGW4GmlL6Yek0yt1zM37/p05PoP6J8eOJdV/+2a+PTvft22NMUvPc56kaV3jrQHUCcj3J72Q30/eomNoZaWKk4F3AEdKOh34ekRcXmO8jpIrfbuRTl+dQZrf72rObRvgI33u/ybp1FidE9WfBbaMiD8A5Hyak0nH8qsq/Rg6A9hMKWH6WFIJkxOBV9cYs+TzZjZwEf1L5synet2xPUkndWcC/yFddO5ccayOkj/350g5U73uID3HB/399Cv/sCIpNWSlAccCIHLttJI5ppLuYuRA8kk1hj+YVPbmkuhzWn1Q+WLx8ww9Bj8q6SMR8a0awxaNCZb4AA2KH3fudpakY4HlJc0mLWv2q0M1iH1JS6RPkfRrUg5R5RfbiLifdDKnX7Heqj5LeiNYXdIJwEtJSbB1rBwR3f9335T0gZpjlp7n0cD3gJUkHUjKYdi/6mD56vqzDCWj1xIRJ5BWjJ8K7Ap8V9K9pGDl5EjH9KsottIXEVvn1dJdgTOUTh1+EzipYmJ2U6VFINU/+0PXmH/IwVUdRR9DwKN5q+8VwNERcbCkq2rOsdjzJiL2yB+LlvuJVGbiJXkre6lIZVbqKvl6sWq/nLOIuFYVTq92Hy5Rqnv3ftLz8DvApyvOsTPeDsDZEXGfUhHczYH9otohtX5VCLYg5cdWff3pKF325kPArPxYQkPdOOoEaEVjginz57duJbNRSmUnXk7K+XhGRNQ92r8zKYCaQso3qH2EXunk3fPymL+NiHsqjNHU1kJn/HVIOURTgHPr5jkp9aXcKSJVg85bN6fF8Lo3bZjnC0inf6cAP8r5jYOOUTz3YxH/zhTgRaSr+Q0jotLhkByU7EPX4xz4fN0V6K75zSYVHf1VRAyUnKx06neT3jyUfDE2JyLU/ztHNfYvgFNy4IukXYG3RESl7iNd49Z+DHWNdT1pi+YkYP+cN3V1RNQq0lv6eZPH3I6hzi3nVtkq1sKnV4cZdOuwz/hFfm5JsajHnqQ/RsTTKoy5FKn6wAGkgzEfj1RwvRZJ10bEM5WK9B4BHAa8LyLqtkLcEDiIVGD3gIg4q+Z4HyXtJhUpe9PveVLouVMsJpgUK2hQ9LjzMHk5tE7E3W/Me8mHBGrYlWa2FgDIuWHH1Bmjx37ABV1X/xtR4GBH6XlGxIXAhTWH2YCGcz9ykP9m0mN+DVJplUpKr/R1jTtf0uWkXLGN6f//sTiNlBbJ3gl8S1Ln8XMV9bfRSj2GOg4l5eCdl4OzdUjFMmsp/byR9GHSa9Jp+a5DJJ0YEV8acKjGTq9C0Z/7LkmbRMSV3XdK2gQY+KCJUuHYT5N+1y+LiJL1Nzt5ctsCx0fEqZIqd5vJK4SfJS0yfBr4ZoktSYaXvZlP/Ry0P0v6JENdCPYA6uQ8A2VjgiU+QFP5485I+kBEHCbpi/R5Q40KVYMlnRcRL+qzh1+1k8Cv8sfdaybad8/x5Ih4i6TL6P9z16lZ9jNJMxk6Qn1J1S250vOU9IWI+IgWkagbg1eBvz9/PD4iLhrwexcpr0htSwrKXgb8gnQq+OyocJqxqZW+PM+X5Hm+lLSttA+p3dOgOqVFbpPUKVJaorTIVOBFEfGcvBrX6VZQdbzSj6HO932N4b17b6Z6f+HGnt+ki63n5pQLlIrrXkQ66TiIztc/PSLq5r2S59LEz/1p4Ic5AOjkWW5Oqjn2zgrjnU763T4EfELDDzLU6UQB6aDFDqT0n046zfQqA0k6iqETrLMjF6otIcqXvXkX6dDBNaTf+y+o9rtpJCaASRCg0XPcWdLjJL0WuCkirq445n/zxxJ5Dx2dRM1SnQQ+RLpa/Q6pSG0Jh3aNXVykmjZ1++lB+Xl2tqBKzA3SKsyXSasBpX43ALeQrs5PAPasmNPVrfhKn9LpxV1I8/wm8N4auXHdpUXWJZ1ghAKlRSJiXr64+1qh/KbSjyEgbZeRCrWeGBH350C8ammRQ/PHJp7fUzrBGSxoUVQlefrLpJZMv6XFr2sRcY5S4/GPkbYMAeaQ6qqdU2HI0m3huu1JukA6Pm8fr8fQBf6g3k16X9yPlHTfub9Wy8Im5PebHQsN10RMMCkCtLuBP+Xg7AnA1cB9pCTd/SOi93j+aHQedddHRN1tlI7vkV54PhMRJWq2TZF0BLCGUrXkYSpG9IeQiom+PCL6nZwbWAMrh03Mc2fSG+vjIuKwxX3xKPxX0o9IhYjP6P1kjavh10f9U5HdmljpWxF4XZQ5XQosWO06IyJKBruQDhZtHxHfKTBW6cdQx06kllYfl/Rd4Kio3kWh+PO7y2WSvkmqEwWwO1DlMTBdqe/iyv1Wdiuu6jb1c/8CWDpq5vtCI11Muv0tIl7b9W/dSAraqiheW6z0e0RD+dlNxASTIkDbpGul7C3AHyLiJZKeTHrBrBKgvSh//Cj181w6lpU0C5il4e0xgErJr28iVYN+lNR0vYRVlAp3bqd0Aq13jlWSNTunpEr2IC09z5n5464MXQ3X8SrSVuSG9M+lqWpZSU+OiL8DSNqHlId2Eynpd9D2P8VX+iJi2Juq0onTV5FWtKueDJ0n6QFJy5Ta9spmA3tL+i/pOVTnoqH0YwiAnOP0dqXj/LsBZ0u6CTi0QlJ2E8/vjj1Jq0mdBum/oNrpw3eQXseXZeGV3ar5m4383JFOEn+Gmvm+3ZRK3OxMStlZ8P5ddQst+52ki4EjI1U8qCwaKKhL+feI2ZTPz24iJpgUAVr3C/YLSCtVndYgVZ/Qt0m6llQKY6EVi4o5C4eTaiw9lYUfIAMnv+YtnoMl/T16+h7W8F3SNtoMhoK+WsmakQsHdz+xldplrBMRl7Rknpcrlat4jIZ64EHFN+xI1ehPl/SPiPj1gHMZySHkFwql2n8fJq2ubEJ6fA3aRLv4Sp/Syci9I+LqfJF0OXAx6bm0QURUadkCKXn6fEnfoWuboWqeXFbyoqHoY6iPZwMvJNUE+xmpR+EOMVgB0+LPb1iwwnlo5JIbdUTExcDFSo24B81fW5RGfu7sKkmbF1zZPpOUH3Yp9QqYd1sb2AH4XD5gcxSp7M39I35XH03kWvZ7j6gjmin90kRMMCkCNCStTtrqfCHwia5PVe1J+RrSisIp9I/CBxYRxwDHSPp2RNTeF1c+jk56gVjoSHqFFTki4gDgAEnnR8SWdefYTdIFpNNZU4ArgXsk/TQiBv7/LT3PiHibUnPmX5JKtNTSWWInrXgtNF6NLZGlY6iC/KuBb0TEGfnFskq+ZRMrfat3rWjvTDp9uH1eAbqAaj31IL2W/R54etd9dU/E7hARw9ID8qrkQikDi1P6MdQ1nw+REpv/TFrp/GlEzCe92Q6Uh9fU8zuvcG5YYixJMyJiLqmO5bJ9/q2BV7uafF0jpa1cpNQbt/vCoeqBi3Uj4umL/7LRi5TIfzJwsqTnkZqHH6TU5urTMdTvcjQ6p5OL5Vr22docpurFjaQLI+IFi7tvlIrHBDA5ArSDSMfjHwIu7AQmkp4D/K3KgJHKDlwq6RWRGssWUyI4yxo7jt7AixjAchFxr6RdSKdt9yUFFZUf7IXfZP4h6dlRJmF8Ns2UQOnemnkuqedjp5zFwIM1tNLXvaL9fHI/z4i4R1LlumpRsBp6lx1ZOBjrd9+oFH4MdawNvCr6t6ip0v6nqef3LyUdSarX1h2oDHqheDHpjfABhla5OmqtdjX0c7+/8Hh/kbR8ldWtkUj6P9KpxjeTtp+PJ3XpOIehwzeLFRE/yh9L5sx1VrJ3B55IOrU8Jd+u0xt3WICfV3qfUGWgpmKCJT5Ai1Qm4AJgVYavIvyNitX1lcsPAC+WtNCR9irbKip81DsaaKbcxPJ1lxn549bAt3P+RqU37NLzVD5CTUrEXujzg+Z/NLTEDqnv6hdIdf7WJ5/EkrR8lcEaWul7SNIGwJ2kxOzuN7CqK9qd5ugfJW2N7yzpacDTIuL7FcballQGZHUNP2CzIhXbtpR+DHV93/tG+NycQcZq+PndufB8Rdd9VVI3Ns0fi5VcaPLnjojf5H9j5ah/qhpSjbvLlRqGdxdrrdNz9sekE9vHAptGxL/yp34raaAFA/U5kNatyjw7W5uSXh4R3WkHe+b3y0/0/85FzvHDpFOrK/akGyxLxfplTcQEMAkCNFjQFuSOnvtuqzFkE01mD80fix5xV9lmysWXr7v8Wqkq+tKk/JnHUb1cQOl5dl4ISx22AEDSlsAVkZqP7056PH0hb01X8R7SqtkLge0jojPfZ5NKbwxqNuVX+j4KnA88FjguciX0HBRFhfE6jgFuJxW8Bfg7qczM9yuM9RBDKzTdv/PbSSvyVRR9DC3qQq6j4hZaY8/vkheKAJJWAB7IF3IzSa/JZ0W1uluN/dySnk3ql7oUsKakZ5FKbbyj4pBBvedJPycA34s+tRIjYubCXz6ioq+RPVaUtFLksjySViJdNA3qa6T37yNJObod91V8X4SGGs9PulZPE4mk6cATcoBZdYyrSA+aJ5NWVM4l9Ymr00y5OKWaSBsBf4nUE+6JwFrRU4l7SSLpGtLP/AzSk/sU4MURsU2NMaeSihN/bbFfPE7yHJePrhZmkh5LqpVVaftP0pURsUnnY76vVtsWSTOjesmKRknaaqTPd1Zu2kLSGb0rUf3uG2C8OcCWwPKk+mLXAbdHxOy6cy1J0kWknZpvdT0ufx8RG4zvzBasOi9SlXy+Jkl6L+kCr5O283Lgc5Hyt5dIk2IFrSkq22S2M+a3SUm/D5G2ZFeS9LmofmKpeDNlSV8mVXB/kBT0bQq8M+r1IV0P+GPvSl+b5inpg8DXc67cyaTA9/0RcW7FKT6S88NeBhwTEUcotXSpLLoKrNYZp1vplb48x9WVDu/0qtpLcdiJNqVyBHW3wW7OWzadgPmXpKTpyvk/pR5DTQZgDT2/1+1zX51k9ykR8aCknUgrsQcqnaKrrKGfe3pEXN+zrV2rur6kl5BWihekBETEpyoM1VklhqGt+1qnV7WIriMdVbf68vceldOVOhcnR0ZE5d+5pDVJ+aQbMfz/snJ+dumYwAFaPQdExOlKTWa3I9U3OpLUg6wq5Rfv7UlvCB8ELmHwligdy0h6EulE3v75vkp5NF1eHBF756DvVlJ+yU9IK0BVnQFsptTH7VjSSt+JDLUeacM8Z0fEIUolLFYh1Z06PM+1iqXzFsjrGcqHrHOkv6NkgVVIj+mNcu7Y3qT/v68zFLhU0X14ZRngSaRWNlW3ws6XtB8wQ9ILSc+bSnXVunyDVNS6kyf3NlL3g+1rjFn0MaRUFuEjLPyGXed3U+x5I2kPUu2y9TW8/MCK1NuqW0bSDNIp4yPzfVVTIjqaeF2bq9QqbD6A0on6yrX6JH2eFNRvQHp8v4aU1D+wknl8XUbqp1t7uy5Sm8ZarRq7fIN0YnVj0onyd5NOQ9dRNCZwgFZP0Saz2bT8cSvSkfn/SKrTaPZQKN9MOduSlPdxq6rXlOsovtLXpdQ8O28AW5O2LH4rqc6L3MdIweh5EfH7nC9Yq0VRNptyBVahmZW+YYGYpBeR+odWtT8p8fd+0lXxD4HP1xgPYGYML2nwW0l/qDlm6cfQN0irjuuTHk+7kbb8SijxvDkXuJH0JtWdy3gf9d5oTyflFd9IKmOxKjUCnx4lX9c+S/o/WF3SCaTes7uM+B0jewVpd2FORLwzr9Ict5jvGTPRzGlqoJEVr5Ui4uuS9oqIiyVdSjol/Mka0ywaEzhAq6dYk9ku10s6m7T8v6+kx9QZLBZupvxXKjZT7nKnpGNIb6ifl7Q09Vd+mljpKz3P/0r6CKm9zhY5b67y7ztS5fwfdN2+gbSaVlfJAqvQ3ErfAhFxnlKj4arf/zDpzfCz5WbFbT1JyU8krazUUfQxRKqL9QZJr4mI0ySdRfU+ih3Fnjf5BN7NDHVSKCIiPqnUcP3efFDgfgYvxNyr+OtaRJwtKUirKVNIrfzqXIT9LyIekTRf0rQcRD65zhwlbQR8lRT4dE7TExGVf/ZFbXXW2eKk/IpXZ6v5AUlrAf8AVq4xHhSOCRyg1VOyyWzHrqQn89U5x2INUk2wSnr2xD9NWoLeD6icJ0eqlbMzqUHz3ZLWJlWxr+NQyq/0lZ7nbNJJyY9ExB1KbYoqHcuGRnLagEbarRRf6dPw4slLkXI1Ziziy0ca542RSuk08YbwT+BqpTIEkFYvLsh5aVVLG8ym4GOIody7h5R6Dd9N/TeZ4s9vpSSsA1i4RVGlgq1deZGPdudF1pkjzbyuERF/IZ0yLuF+peT+3wInSrqdoUbdVR1N+t0cQlrhey9DfXir6t7qXIa0YnxJ/reqKr3idX5+zhxNWnWeS/02TUVjAp/ibBml4+MP5kTqusfHkXRtRDwz74kfQdoTf19E1MmT6x6/blumRY07FZha9efuM17RearMCdtrImLDnI+0L+mF5vAYXuunyrjFk19LU+oX2UlIfoS0VfXxGLCJuqQDc4L4N/t8en5E7FZjjiPWV4qIOlshpR5Dp5By5GaTCo3eQzoJXaTgdannjaQrSW9+l9CVK1b1sIMaOAHdM36tn1uF61p2jfsk0u94KinP8nGk14xKRdfzmHMiYlbnvSLfd1lEjJRPNui/sRpwVERU3iGQdGlEPFupb+gOpBWvP5R4XcsraCtEy05tewWtBjVz6udXwJZKxUXPIR0ffynpBbiK4nlyKtiWqWvMYYVGSac6n0a1OlaNzFPlT9iWzkfqKLoVUHKlr2vl7JU9n6p6pdi50j8+UlHdYuoGYP2UfgxFRCef6RClJPzHkXpx1plj8ec3sFRU77PaT/G8yMI/96H5Y9G6lhHxj66bnyk0bKcg+L/zduffgZUKjQ2kfpp55b2OfitelQ9CaeEWiI9KWiMiKqcxlI4JmjjFMZm8OCLuJW1J3kpK1K37hJwSqcDoK0nHx7cj9XOrqntPvHPap26e3HL5534laXvmmaQgso5jSAckNs63/86AFaL7KD1P5fFeQTph+2TgrTXG685HOrdAPlLHShHxddKb2MWk4L5O/8fZOTjrPnlY9c32J/nPj/KfH+ePvwGqHJnfOX88ouJ8FknSKpJOkXR+vr2hpHfVHbbwY4g8t+mktIVf0s7n98Uq1I8z686L/GW+r25eZMmfu7M1+vKI+E3vn0EHU+oQgqQzJZ3R+6fiHDtOV8qvPIhUtPcWUsP0yiS9p+vP+5T6eg7S03MhEfHhiPh3RJxMek98aUTsVWPIn5Jecy7Mf64ldWm4SakVZBVFYwKvoJVR8tRP6ePj7yMdwy+ZJ1esLVOXDSNiV6UaaESquVX3AqL0PEufsJ1N2XykjtLJr8VW+mLh05uPJW3VvJdq+T7/lfQjYO1+b1RRrz3RccDZpN8RwB9JW2lfrTFm0ceQpNeTynSslu+qXMOqSxPP72cDb1NKmO9uUVS1aXgnL/KXpfIiKftzr5KDnu0kHUjPgacYvAhsk10eOs+7n+UVqmWifq/P7u3RR0gnjf9fzTE7p72fHhFHSnqSpPWjeu/L7wO/jtwOTtJrSKWDvkdKBXp2jakWiQkcoNXTxGnGosfH8wrKa7tu30hKZKyjZFumjiYKjZaeZ+kTtjcAe3Xd/jPVWwl1K7oVQPmTh+TnyrtJFw8/BWZV3Fp4FeliZkOG11YrYY2I+KqkdwJExEM1A3Io/Bgi5Rq+CbgkIurOraOJ5/dedSfVLZo5AV3y5/4uaSVqBkPtjyoXgY1mmpAvkC8OFxzgkFS11y7QTLkNSfuSdgJWIy1eTCOlc7yg4pAv7F6Bi4gfSPpkRHygxvOyaEzgAK2e4qd+YuHj4w9Q4/h4foDsxsKFLCsnT5NWOzptmR7O/0alxvNdmig0WnqepU/YNlFklK6cmZMl/Yb6ya+zKXt69a2k7evLgW1qXAETEf8mbdH8IyJ+XXWcRRi2epLfsOuWfin6GAL+HRG/rTmnXsWf31G+aXjJivodxX7uiDgAOEDS+RGxZY05DVM6xymPeRDwduAPDAWkVXvtdsZclrTK2SnpdC7w2Qorh912IpUQ+h1ARPxd6VBdVUtJel7n+SPpuQwtClS92CkaE/gUZwvlN24x/IXn/IpjfZ0UiG9NyvN6M3B+RLx3xG8c3dir9MyxzkmiaaTjya8mvQn+EPh8RNTdWik6z5IkfZe09L8TXUVGI6LOG3Zn7GFbAcCKdQKhUpRO3y0HHEgK0IaJiIFaPUl6fkRcJKlvjl2dVQBJ+5BWFV5ESsh+D2mL97CqY5Ym6aOkU32nM3zrsHYfxcLP7wVNwyOidtNwLaKiftehicra+noBQ/1llQp6v4XU2eMnEbFxjTH/BGwaEfcVmmb3+06nBufbqX+q+pKIeI4K9duVtAVwKtB5rixLen+8EnhDU6uVg/AKWg1qrpfXl4DHk5IM1yWd9tq04pCbRyqzcU1EHCTpaGquTEnahtSG6UmkK67pwL9ICeRVxptK6h6wBwULjTYwz9IFHZsoMlp8K6DwSt8KpKvzTzK05dMxHxj0uTMbuIjhVeq7x6uzTXOwpJ1JJyNfTipnUOeEdhOPoc7z5Shq9lHsmmPR5012CGnb51sAkWod1nkDLF5Rv+TPLekLEfERSWfSv8xGndxIKJv3fHvJ4CzbLCIWHAqR9FvS+1gdt0h6Aeng21Kkep6/rzpYRFyQdwM0dNeCsk6VHpulYwIHaPU00ctrP9IJlXMiYhNJ21Kv91+niOE8SctGOo1X54UW4IukVYXTSYHj7sDaVQeLVPOt5AmvjqLzpHxBxyaKjEL5rYBi7YQiYu0a8+g33h7549Ylx+0a/1uUObjRUfQxFM30Uyz9vIHyTcOLV9Sn7M/dVFJ/E3nPF0s6jVRPrnsVtvLFDTBF0mMjVSSAtDpVNz1gT+AkUm3Q/wAXMHSKu5KcV/oPUjC1as69q7NiWjQmcJmNekqXMyCPdSc5eI6InzNyA9rF+bekx5NqI52dt9XqtqvpJOVOi4j5EXE89Y/h/1LSkZI2l/SMzp+WzXOZiDiPtE1ze84zqRM835ADs1NJBTwvpUwfxf9Gan3Urc5V9roR8THgPxFxGqkMQbG8mhIkbanUlBpJu0v6qqSqjdc7Y343/346t5+o+iUNSj+GFpA0Q9LOks6rO1YDz++iTcNZuKL+l6lfUb/Yz92d1N/vT40pvpnUcWXHiLibVKalbreDzYBVSQHQh/OfuuWiTiEFfvvl3OLfkoKrSvIuy6sj4iWkFe2VImLb/F5ZdcxtJN1CKukUwE30SbsYUNGYwCto9TTRy2uu0im5GyXtSeqduVyN8V6RV6j2J0X0K1LjiZJ13vxvlfQq0hyfsOgvH5VO5fNXdN1XZcurW+l5Fi3oGMOLjF5G+t3UKjKaFd0KoLmVvpKOBDaStAEpL+cU4OukY/NVrZMPIQAQEf+StG69aZYvCippM9JqzxtJq6Yn1BmPZp7fpZuG70TahvwQQxX1axWqpYGfW4WT+vMBi0Pz2KsAq0bECXXm2G/1WfVPqH8h55u+KN/1kYio/NqW38PeAXytRH5l1sRKcdGYwAFaPU308jqAlKfzEVJS/4oM1WEaWETMyx8fBU6uObeOw/Kq3AHAaaQ51qpxEz31sQopPc/ego5TgY/XniUpH6LEOFnprYDelb57KLPSV1LxyvKkYqhTO88hpYMsA/cL7VHkMSRpJVKS+G6kHMOTSC3iXlZzftDM8/tsFWwaHs1U1C/+c5MKl+6dk/pvJV2I/oR0ATEwNdPloXv855IClTeQ8qAri4izSXUES/mVpO0jok7JoGEi4oa8RT4fOF7S5aTff1VFYwKf4ixELevlpUX0gOuI6gUiG7GI7cx7o0bbjSblN+tKBR0l3UX/380U0kmnujmCnX9nWdJW2gMlxstjbkFe6YsCJ2xLyVfrewBfAfaIVLz0mu5E5Qpjfol0RX1ovmsv4OaI2LvebBeMX+cxNJcUeH88hsoE/KXOAaUm5LywVaOnx6rSKc7bB31+LyrpvqNA8n1RGjp1+QXSgYYz1HUKscJ4V+bc5F1Itf/2JZVseWaNOa5CKv+yG/AUUgmc0+rkYiklGx5AV201qPe+k183n0jayn6Qmq+XGjoVeg5pBf6vwA9KPYdKxAReQasgv/H1+ifwz5yIP/ASrKQRV8ki4ugBhyzaAw5Aiyhl0FEzqfSnwJrAvfn2iqSE2P8BO8UATYtLz3OkXLicVDpQaQhSAn+j1FV4spOYXfP30xmj5EpfSZ3K8udFucryH81/Ojk+PwY+X2WgBh5Dh5K2CA+S9A3qFSLuzKOJ5/fB9O+88Jj8uUFXdotX0m/4da10Un+xbgdKlfN3A55PKqz7duCUiPhCjfl1fJu0cvRN6hc57ij9utlZMf0YaXdgRSoWVG4iJgAHaFU9QP8SAXWOuI90EKDKMueVwBMi4q/ddyoVzvt3v28YhZGW0WuVNKBs243S8xypQn2VPLl5jLCqMOBYC1GhwpNjtdJXQhSuLK/hpV/qFD/tKPoYilTC4aOkBOTdSCuHS0vaOiKqlmpp4vm9XvSp4RipxMExFcY7BZjR+4aX3yDn9v+WxWryda10MfOS3Q6+B5xHqpd4F4Dql+zoWCoiqvbr7Ssibs6rzp2jwH+ss4qfDzxBytusm1vaREzgAK2KaOBoe5RvjfFF0v7/X3vu34h0NTdw0+d+yaQFFWu7UXqeDeTHlV5V6PVG4KlRv7ZR4yt9pUj6IPD1SGVkTiZd8Lw/Is6tMl4ULv3SRI5lziv9MfBjSSuTmq4fLunxETFwyYmGnt+PHeFzVV5HP086cXd8z/07kd649xl0wCZf1xpI6i/Z5eEVwNuAPyj1sy1ZmPViSRtGxDWlBswHn04j5dVOIfWt3jEqdtLI/3fvYOgg0XnAcVWCviZiAnCZjUokbSDpxX3uf/FIWxmLGXN3SQs90STtIalK8PaszmpUt7zSsEWF8ZD06pz70Hv/W/KppzqWkvS8rjErt90oPU9JL5D0uj73v657zgNY5KoC6cW3rlKFJ+cBK0fEzd1/SKeSWpN/ls3OwdnWpMKiuwF1r+CLlX5p4DHU+f6nQQoEIuLLORfpzRXHauL5/T9JC60O5vuqlNnYhlRrqtcJVCxn0OTrmqQLJK2YV7quBL4u6Ys1hnw66aTgk/NjcRUqrhxGxNk5Z095bl/J435KGl6wroJnA5dJukbS7zp/ao55FLBLRCgi1iddyFZZhe0e7zXAWfnPq0m5aANrIiYAr6BVdRD9T3r8g3SF9+oKY+5Bavrc69uk49nfHHC8kZpZV13G/jD9+4L+jLRF+aOK40K6Mjxd0rC2G0q1k74y4Fil53kg/a9SryRdyS/0xFyM0qsKvS5WmcKTTa/0ldTZ5tma1I7pt0olRuooWfrlQMo+hjpOZeEuI4f2uW80mnh+fxn4oaS9yIWTgc1J23wHVxhvavRpCp9XPKv2T2zydW25fOGwC6ng8b6kivpVT13+hKGts2VIXQ9uJiX3VxIR/wIOJ62+bkq6uLmIeuVf9qrxvYsUuadr/vsFNePIrYBndB5PSjUOq5YjaiImcIBW0ar9lm4j4lpVL465dL/TXBFxf953H9QUSStFxD+778xbIVUrOs+IPoUBI+KuHEhVFmXbbpSe5/IRcVOf8f6a/z8H9T9J60TEX7rvrLGq0KuTz7hn131VcmlK5w816b+SPkLa6tpCqZbgSBcpi1V4W7LoY0ipzMYqpG2epzP0nF6RkS8ARlL8+R0R38opCt8A1sh330oqs1Gl1MRj+iVd5/lVLYHS2OsaBZP685yGPSaVeu7WKq0iaZfO7yIirgCukHRpjfGmAl+JiKrtCRfl55J2jtTdA0lvBs6pMd6/SL+fToHjacBdFcdqIiZwgFbRiiN8rkowBSPXnFm+wnjHAd+VtHvkekNKRTa/RvWedSMVbaz6ptBtC4YafK8i6XFRrcF36XmONF6/0zuLU3pVYZiCOTVNr/SVNJtUL/AjEXFHDvZrt2jS8KbzqwBNPCarPIZ2Jq1SrM7wwPteqj+GGnl+R6rIf3wnEO0kpFd0OqlzwO6dbXylXrHHUr3eVJOvayWT+hcSEefV3DKFVOi3N1j+f1Ssm5lXMx+QtExElLjg7NgV+KCkTv7hDOBfOQWoyqGl35N2G07Pt99I2pZ9DwxcOaGJmMABWkV3SdokIq7svlPSJlQ/IXmhpH0iYtiLq6S9ScvNA4mIw/IL4jVKpSogLYl/JSIOrTjHayS9OSJO7ZnjjkCt+m9auMH3dKo3+C49z5skvTgiftEz3jak7YWB9FlVmEKqKF91VaEzn6dExE2LynmIwUs5NL3SV0wOmvbquv1n0rZDZYUfk6UfQ4eRygTsV/C0XJPP7wsj4gWLu28UPkXKN7tV0o35vvWAH5K2kato7OembFJ/b7mWpUir5ZVWDpVOjT8bWEnDyzytSM3VZ9JBjvMlfYd0wjHdOXi5qG6lDy1NI6UYrJ9vX036uTdj8DSgJmICB2gVfRr4gaRPMXwF5GPAOyuOuQ/wG6XyEp3l5c1JCdlbVRkwIg5QKrnQeVJfH0PNa6vYN8/xFV1zfDYpcbfSHLuUbPBdep77k07KHd8z3tuBSknEhVcVOo4gVRnvV9LhcQxeGbzRlb6S8irKR0hNipfp3B8RdVo9lXxMFn8M5Tl9TqnExJMZXhB00GAcmn1+D1slzPmBA7dRyifsdsm7AZ1ir1dGja4ENPhzR6pQf1VnRyDf/a8aQ3Y/tx8BbiStLFWxBunx/ViGl3m6j7QiXcfSpBWqp3fdV6uERz6g1Dl9ORP4e28Kz4Djlayc0ERM4E4CVUl6Cek/v7PPPgf4bERU3hPPqypv7hrzClJF58q9xySdET3VtfvdN8B4q5KuCrvneHRE1KrfpaGqzguqbCtX4W7DPCU9kxREd4/3xX55B6MYayqpRte/8xbF+0kHRG4APhUR9444QAWSbomINSt839tJrYh684e+VnJ+dUn6LnA9Kaj6GCnReU5E7FtjzNKPyWKPoa4x3wN8gdQfdUHNu6hYDV3SaqSt4lLPmw+TfuYVSS3COpYlHeao9OaV8+42yDevi4g/Vhmna7ymXte2IeXQPon0+5kO/KvCdlxjJL0kKpajGQuSDgZOiojr8nvkb0kdPqYBO0eqTFBl3CmkMhudAzrnAsfnoLrKeMVjAq+gVZQf0EUf1BHxX0lzI+K93fd3J3FW0K8A39MqjkVE3EF6EJZWtMF36XlGxLWk3oclHE26AlxG0l9IpyJ/TLpaP5ah04MlVXrRaWilrwnrRsQbJL0mIk6TdBbp9HMdpR+TJR9DHR8CZnZWF+rKAUnJ5/fXSLlhR5ICoI77IuLuQQeTtAwpD+3FpNWjKcC6ks4FdoyIqiUnmnpdK96QO68Wi+ErxQsd5hmtiDg351r2tmWqvB2ZV3U/CqwTETsrlYN5WvQp/TQKryStjkPqnvEQ6YDM00gpB5UCNNIuwCYMVUjYlbRdPnAtPWgmJnCAVoP6t2e6F/hdRNzY53Oj0S9hs999i5vbHqSrg/U1vP7MiqT8gMokrUd6UK8REU9ROpr96og4sMawpRt8I+nLpJyVB0lv1psC76wa7OYk8UOAtSJiS6VCps+LiH6lKEayBenqf1ngNlKtsYckfQ0oVtixFElbAldExAOSdidth3wh+pxKHEedN+aHlJoV301KD6gkj3EY6U275GOy1GOo445SwVleqVikiKhSBPZe0mviK7v+nVVIAcao27d16cxhjYi4J4/3eODrpDfxyl0fGnpdK9qQW9IOwJdI6Qq3ki7Ar6ZaWZXOmCeQtjqvYHjnkTqOIXVF2Tjf/jupyOz3K4w1t2tV64WkXaWHgWvzdmdV2wGb5m3zTpmNOVQM0PIYfyRdjJwQBXogO0Cr56WkVY/z8u1tSDkMB0k6MCL6FVTsq4GEzXNJV5hHMrzmzn3UDwKOAT7DUF/Cq0gnfg6sOmC+gn2Juhp8S9oIWOj4+wBeHBF759ySW0krUz9hwGC3y3Gk7gyd388f81iDvrl2XnAeVGpw/RCkyvCSHlrM9y7Sog4HZHWe60cCG0naANib9DN/naEK3G1wQw6qTiW98d9DerEdWH4T/CZwPykB+w3Ar0q84FLuMdTx8xxYfZvhNe+q5KB9iPR/djYFTxpCKthKCtKmkBKz75H004gYtB7Y64BtO8EZQKQWSu8kvebVactV/HUNeDh/vFWp6O1fqZB712U/YBZwTqSm6dsC29cYD+B5wAY56Cllw4jYVdJ2APn1vOrJ76mSliddJG3J8FZZVUurwFAbpo7eVk1V7ERaKf5LTrs4KtwsfdzMB54ZEX8DkLQmqTrx5sAv6F/xelGKJmzmq+qbSVf/5PlNJ/XnrPviu2JE/CwfQCgRWGwGrEXqxfkvparMnyE18S2Rq7ElcFZE3Kp6vebWiIiv5jcD8qpXleKYMzRUu6r779C1bVHBSP0e65y6fCQi5kt6GXBMRBwh6Y01xisuIjqV4A+RdBnpwuZnFYfbn7SqdZVSZ4JPRESdYqXdSj2GOt6aP3b/PqoW092G9FrzZlKfxhMiovKWbo9SBVtn9EsMj1SzrM5zBwq/rmWdhtwHkFaQViSVsKjqkYi4s7NyFBE/l1S3ufktNb+/n2Fbzfl3UzVAO5Z04XAP6WDAnDzmBlSvWwaphtrZeQUR0hZn1dcMACKd4ny70oGQ3fL4NwGHRsRZg47nAK2edTrBGUBE3KJU6uAODViMMCc6/qB0wqakb5NOkTxEekFcSdLnIuJLNYadp1Q8d37+N9ZgwHZMXfPbn3TlHqSVxyNJ5RGOpP5JojuVCqq+DPh8flGr1LQ2G/Y7zU/CKldcyzK8dlX33ysHkNFAv8dsaUnPJh1s6JQIqPP/2KhILbPqeDQirspj/UpSnebWvUo9hoCyv/OI+DWpbtdjSQHfEXlF+8MF/k9LFWz97wifq3yYKiv2utYRQw25L6N+Q26AuTm5/UZJe5JW5OoW070BOE/S9xm+ClunJMb5kvYjXYC+kLTyXilXLCKOymk6azA8x+sR6nUs2IeUBvT6fPt7pJzJEp5N2o79Dynoe5ekHSJih0EGcYBWzz/yg7CTZDibFBRMpfob7eMlrRAR9ykd2d0c2L9z1VCB8pXr9sAvSflsl5DyGKo6mvRgXknSgaSr+P0rjrULqRDoHZLWJyVhbxUVG+D2eDMpZ+jEvA2yNsOXxwd1lqRjgeUlzSZtUw2ySgpARKxdYw7j4WOkq9hfRsTv8++pTlmDYiTdRf/n2hSqFa8EmN6zqjlslbPi9mFHkcdQr5zX1Z00/rcRvnxEEfGgpItJeWI7AavWnR/lCrauk3OFek2hRrujrNjrmqQR+4LG4G3XOg4AViDl2x1DWpF7d8WxOpYB/gw8s+u+ujlo+5MCoPtJp4x/mD9WEhGXkYLc7vsq51Ln9+gfRMQrqZ5e0G/cD5EWRP5MKnv005zO8jlJA79mOkCr562kHmZ759u/Ii2TTmNo62FQB0TE6ZI2JyUxHkb6RVdtqNypYrwV6cHyn5pbKkTESUqnD19FWg3atcYV9n9z/lknmTZKBGf5CfjN/ATszPuvpCKXlUTEwZJ2JtUUezlweNUDB93ylXpnReq2TtJqW3RWd7tu38DQVed4K128EhZe4aTrdtXtQ6D8Y0iLKONAhdSAHDTtSHrt+l8ed4OoVzuxo1TB1r1G+NyPq0yso/Dr2khbtwO3XVM6Ban8XCQHkLcAf6NeXbWi9cA0VELo7oj4rKQHSCWEnkBK3xm4hFBOWVhkwBgRmw86ZqRuB0+UNCUqltVYhLWBV0X/si8DrZ6BA7RaIuI2Fp2geW3FYTuJmtuSarKcmqPyqq6XdDapYOC+SnVkapG0RX7hurDuWMCKPVeby+Rcp85qRaUrzaaegJH6wNVqISTpg8ATI6Jzdf470hvrUqQk5UGbwzdK5U8eljSP1Afv8u47lQ7dVKph1fQKZ4nHUJeSZRzuIL1unQh0ukdspdyQusaqDzmH8YmkLgxHki5IBg78ImLQvryDjn8hBV7Xoly7tY5PMbRTAym4P4y0vbkvNUvzKP2SN2L4KuxJFYbqLSG0DPVLCNV5/xvJJcD3JJ3K8G4HdR7n7xvhcwPvgjlAq0mF68eQai7tQHogvzrfV6ftxq6klbir89bFGqQndB2H5KvtE0mJxH+vMdbfGH61eQtDx5yrNPjuVvQJmLf2vkH9Y/hvJp0A7rgzn8iaAfyclgVolD95WNLB9J/HY/LnapXFKK3gY2iBKFfG4RLSc+4NfT5X67mohdtmTaNC26w+K0lfYagP4uGd3MGKc+y3UnMvcDFwcAxwilfSq4EVeldHJb0FuKfCoZP1IuLsrtv/6bzPSKpcAy1///tJ23KrkbYRtwB+Qyp7NKjuEkK3AytFzRJCEfGbnvmuHGXqMW6cP3ZvEdd9nL+AlEPdiQnqpFo4QKtDzdSPeR8pv+D4SH0V16NGwc1IxW8vAJ6jVIbhkoioe1JlM6Wq6LsCl0r6PWk78bTFfGu/sUpfaXbbOH8s9QQ8mjLH8Of3nEQ7HyAi5iqdtG2b0icPS1ov+hTpjIgL8gGRtin1GOooVsYhIl5YcQ6jUaptVr+VpMNJ22d1V5LOIxUq7azSvYVUp3ANUr7XIEWGP0z/QPdnpFpggwZove/Vb+76+6At3Hq9g5TrfFFEbCdpJql7SBVzY6iE0J+jUAkhgHxQ6QzSTsOaeZX8HRHxjopDbh8RtbaH+/gGKf9uDgVK1ThAq6d4/ZiIuBh4bdftG0lFXCtRqkNzCqn20BRgQ6XOBD+vOc9rgQ8pncI8PP8bAwdoXfN8MXBZ5DZHeYVu04j4ZY05lg7+Sh3DH/YGGhEf6LpZubhqg4qePCzssSN8ruqx/iaVLuVQuozDAkptn54H3JCf73X8N+eedd9X5WK230rSUVB/JYl0OOm5nRuSfkxqK/RcUhuxQcyIiIVqOEYqB1Ll1OU0SctHxP15nD/kOa5A/cbm/8u7K0vllJDr8kpvFd0HaoYdrqFeCSFIaRYvI6cHRMTlkgbe8s55m6cDT5D0d+A1dVZee9wdEWcWGssBWk3F68eofDXrzwJbdj2hn066Yq8VoOWrrNmkK9brqX4oouOLDK+GfR/ppGnlCtmwIEBd0GutZmBa6hj+DZK2i54ebUq93FpxOrJHIycPC/mfpHUi4i/dd0pah3q135pStJRDFCzjIOlNpALE9wAfIK32/RVYT9IBEVFnRbJU26wmV5JWkrRMRHQeNzNIdSPnSxqpvEc/I61ijnRRsSjfBr4pabeIuA8WBGfHkYKNOv6TH5NXA1+QdAvVy+g0UkIomx4R1/cE+VUubr5IytX8OSlx/yBS4FfCqZLeRVrp6y5ZUqkEjAO0epqoH1O6mvW0TnCW5/aH/GSsTNIVpBeZk4DnRkSJQHVYMn9eWahVa0upUfOuDK3sHSLpxKheA67UMfyPAT+VdByp8wSkLYY96GqJ0xalTx4W9mXgh5L2Im+fkf4vDyHloLVNyRI1QNE82P1J/3ePIxXanhURf5S0Oqn+VJ0ArVQrtyZXks4ALtZQGY/tge/kFa+/DjjWNZLeHBGndt8paUegSmX5z5BOoN8qqdNGcD3S6eo63RMgXXBNJ1Uj+BzplHKlnrENH7CZm38XnYubZ1DtImxqRPww//0ESR8Y8asHcycpaD4q3+50K6j0XuYArZ4m6seU3gK5S9LsiDgBQNKu1Ku+DLBnRFxUc4xe90t6dkRcCgvyDeoe738LKYC8P495OHARFWvARaFj+Hlp/kWkwxCvzXdfSTq5W6fGVmMKnzwsJiK+pXQy+RvAk0nPv1uBz7QoiFyg1GOoI2/xzKJMHuyjXQHPzZFLBUTEbapWVLYzx6mkXYBhrdwqDtfYSlJE7C/pElKBUYADu5L5By0rsy/wG6U2c52LsGeTujVsVWFujwC7SFqX1OAb4MqIqL3iHkOtiB4E3l53vAZ9lnShsHrO/34pqY7mwPJrRmfrdUr37aqrXdlBpMfPFRFRO0/XAVoNUbB+TJfS1azfCXxL0lfzmFdR8WSbUpeEm4C71afvY9Qr4LkP8P184ADgGdSvtTWlE5wBRMT9SlW4B5bfZC6LiE2peQxf0pnAuyLiLT33b0pKLt2ozvilqYGThyVFxPGk04sr59slTngVV/Ix1OW5lMuD7Q7selcm6mzDzpP0DuBrNd/8oNmVJHJAVrutV6STtZuQ6r9tl+++AvhQRFQq/5LH/ROF0yCUyujsycKrsG8q+e/UFRFnSwrS/+cU0kVYlf+LDUmn+rvfCzq3K692ZbdFT8mfOhygVSDp+RFxkRZRLTpq1FGh8BZIRPyZdIJzuXy7TsPnI0hbcP16PtYt4HlxDvo6SboXR8TdVcfLLpP0TdLVNaS8g0pPnvwm80BPjkpVVwJXSdorIr6bA/JPkU66LbKOzjgqffKwmH7Pwe4clZrPxaIKP4Y6SubBSqmlTu/fpwBVk8Y7fiVp+4j4Tp1BFrGS9BRS8/BKq3xqoBBq/r47SOkMbfdd4A+kbe3aJw8bdgtpexwG33YGICKaPDx0nlJv1NMZnvZUafHCAVo1s0lbZf2qRdeqo1J6CwSGJ8pLqpwoH7kqfzTU8zEHZCXfUPckHRc/PN/+BfDpQQfRULHbIPWY+w7D66oNlO8TEZ+T9CNS/sNOwNNIgePGEXHPoPMbA000kS6l8xxcBtiMoQLRzyTlpLUiQCv9GOpSMg92xPZENc0G9s7J9g9SsT6UpFOAL0bE1ZL+TaqtdW8ee/+8mjqoTiHUV5Cei1/Pt99G+n1VpvKHvprw+KheqmLM5EMmp5FyGKeQiuHuGGXaApbS2XLtXn2svHjhAK2CiNgjfyxaxqGJLZAGEuU7W15/i4j/5eBvE+DYKiteks6LiBdp4Z6KtQr8QeopSKopV9cc0mnSpUknz57e9bmq+T5/JBWD3J30BvOllgZn0EAT6VI6z0FJpwF7deUwbk46idgWTTyGoGAebPQUBC2sVEuuTSPi6vz3twDX59y2J5Mq1g8coHV+bkkHA8/pHFbSUJmNOkof+mrCdZJWj9QZp82OAnbp+n1tQfr/HSglpKkV0/y9RRcvHKDVsIgtznuB6yLX8xpEQ1sgRRPlszOAzSQ9hdS+41xSccdXj/hd/XWuOIr3VJS0PGmLYZt813mkvIX7F/1dfXWSR4vkHEqaRfr/ugL4P9Lq5tlKpSwOioi2bTMUP3nYgJmd4AwgIn6nVEy5LYo+hjpKjifpOcDTug4UfYehchGfrBPARcTN9WcIDM+NewHpcdkpfFv3gNYTSAFvp6TGDCoW/e3S5tXnjscD10q6iOGrsK3KQYPhFxGRilFXGaap1lEA5IMwT2Z4Pp+3OMfBx0jbKp0WFs/Mf19D0tsjokrz3tJbIMUS5bs8Gqno5CuAoyOVYbiqykBdCbM7RMSwsgiS9qFeqYRvkOqpvT/ffhtpu2FR/VMXZYaGF1wcpsKT7/vAe2PoqPd3JP2G1ALnMmrWfiutiW33BjyoVID5FAClsiB1E9JLKvoYaigP9uMMT7R/BmkLeTlSCYbKAZqkNUnP5d5+jwNv/SiV/bibdFruE12fqlsI9XRSmY3OadA3kU6N1tHa1ecup+Y/bfdzSTtHOlGOpDcD5yzmexbSe6Ghcq2jOm2zPkt6fHafqvYW5zj4E/C+yE1Qc37BB0mrQqeRltwHVXoLpFiifJdlJD2J9IbdWUmpG/TtyMLBWL/7BjEzIrr/H38r6Q+L/OpFeyrpYES/n7HKk2/D3u3g/AKxg6Q3VphfYxo6ediEtwEnSzqe9Du5lrS13xalH0OzKZ8H+6SIuKTr9tyI+AmApPdWGK/bN0jBzsakU+TvJm3NDuog0jbhQ8CFncA2r/79rc4EI+IASZcyVGbjgM7PX0PrV5+j4Qb0dXWlv0wBPpif45BWOP/JUO/mQcct3ToKYC9Sr9gi28UO0OrZKLo61EfEFZKeGakYbKWApfQWCClR/mPUTJTvcShppe+8SDW91iFt7Q5M0rbAS0i1bbqDsRWpH/TdJmmlyH0vJT2RVCNrUNdHxCaL/7LRGSlXLwq2CSmhoW334iLV73pW3tamwjZ200o/hprIg31Mz+0Xdv19pZpjrxQRX88nly/OgdDFwCcHGSQizlTqLbwqqfJ9x99IhZ5riUJlNrrGa+3qs6QPRMRhPa+7C0REpcCnAcXTX7IiraN6/L1kLp8DtHr+I2mnyO1W8om8Tv5CpVWvHNi9g672RKTG6VUTfx8kFU0sJiK+Bnyt666/MjTfQT1E2sqdz/DCtLeTrpYH1vWC80/g6pzsC+mUViteHCeCBk8eFpefN7uRejXuK2ltYPWWnfBqhKSnsnANqyoraPMkrRqpPAQx1Bd3Nepvy3Xyrh6QtBbwDyr2nc3zu6PnvspvipK+EBEfUapPuNDrbN1crIi4kHauPncuuOoWBG9UwfzFXqVaR3X7RF7h+ynD8/kqnSZ3gFbPbsBJeQtxPmlrcldJj6X/1sNoHEw6FfnNfHtXUiHGga5m8tbU60nNW3+R98a3Jb3ZfrrKIYausXcAzo6I+yR9mpSHtx8p6X0gOR/gN5K+G0MVrevqvOBcz/DK/Mf1+drRKN01YaJo6uRhEw4BnkSa777A/aSV3sonsgpr5DGUL0Z2JT2vu3NeqrwhfA04XdLukQuA5uDveKo/dzrOl/QE0pbfHGAuUKsmWkGd4KlfSsqqdQZexInBe0mrhwdHvbqUtUTEsfnjQKuY46VkHmNWqnVUt1flP+tT//noAK2OnP+wqG2Vqk25tyMdJX8EQKkv3BwG32c/mtT3bpm8xP4Y0gvQVqSTlztWnB+k3IzTcymDlwCHkRLcn1djzJdIuiUi7pV0Minoe39EnDvoQKVfcCJiQfFYSSsCYvgLxPkl/70WaeTkYUO2Jl3YXAEQEf+SVDdpvJiex1CpFS+A1wFPifoV+omII3Ju6bUaag6+DPAVUvX+OmN3LlhPzgdiVih4QVZLRPxI0qqkHplXR8QjSl0p9iPl+n2hxvDnkS6wO1tnbwFuA9YglYio1POyJKU2RzsB6zL8MdmWLc6OUnmMHcVaR3V5HbB2RPx3sV85Cg7Qaug9QZWXSiuX2cg67SY6OsmRg9oC2ICU93AbsHJEPCTpawydOq2q01ZmW9L266mS6h5dnh0Rh0jaGliFtDp5OOkJVEl+g96Zhd8MqyaV7kAqT/J4Ui7buqQ8mFaduiyo9OnVJv0vIuZ3tiskLUX9HMbicrmFt5Mqt9e+wiblXhUr25AT5Q8ineCElDv3oKS/AWvVGVup/+zTI+JISU+StH5E3FB3znVJ2p10QXs3qXfxx0gB6TnUz3/aKiI63VG6a6s9l/b03T2LtIXdWdlsqyJ5jB1RrnVUt78w9P5YmwO0epoos3EOqSbWCfn2rsDPKowzN+cPPSjpLxHxEBSrwzM/Bys7MlT7bHrNMTtvVlsD34qI3+Y32TrOJM3rUsq88OxHakx9TkRskg84DFqyYyIpffKwSdcqldaYkvPPPko78w3fCDw1cqPvAvYGfiTp59TvJND53gdJ5V661Qp2Je1L6lSwGmm1fRppReQFdcYt5IOkXYvfS3o+8Gtgp6jZlipbqeeAzQzgCfliosgqSwFrRcQG4z2JUSiWx9ilduuoHjcCv1SZzh4O0GpqoszGPqQG551G4d9jeEL+aHWvfvSuhNTd+nkfqUL/8RFxk1I7k1/VHPO/kj5CWmrfIid91w361u0ps1HXIxFxp6SlASLi50p915ZURU8eNuyDpDy01UgB+Q9JwUvb3F4wOIOUb7caadune0WutLpj7kRajfodLCgsu0LtWZXxcET8HiBSbbk/FwrOIJVxuDinqkC6oPtOzn36a6F/o67rJK0WNZq4j5F+eYyVT72rmdZRMyjU2QMcoNVVrMyGpK0i4jcR8SgpN+GYmnNbluHbJt1/r/ViGxEXA6/tun0jqZxHHbOB9wAfiYg7cp7Ot2qO+RdJyxcsuTA3/15vlLQn6QV2uUJjWz1TcumJBaUWWhQAdLtYqS3VmRQ45UVa0V2/6invbjlJelHqvlf8N1Jx6+772nLQZHrPBeyj3bfrbOVHxP6SLmGoZMmBuZQHDF2Ej7dPApcqFRtvbSeBPnmMK5JW+P9fxSGLtI7qmWPRfF0HaPWULLPxFXIuk6SLu/MWqoiItet8/0jUQAPgnIuyV9ftP1O/zMa9wOWSzmH4C0/V5NcDgBVIq4fHkF4g3lNxrIlgIp1e/TUL5wL2u2+8bZY/dl/Q1MlBuwF4LF3lT2oYqShr3dNtt+QVi/n5hPlHSSeD26D3Ypau27W38qNwbbUGnERacb6CoVXYVouIv8GC8jp1xinROmoBSX3fD7zFOT461cu/kW/XKbPR/UBrzemzRSjWAFjN1CDqlNmI/Ke2/KaybkT8khT4Va37NmFMhNOrebt5OrBUPo3WeR6tSHrjbZUoW1gWUiuzOSUuQqJwo+cee5ICgZmk5+cFpAM8466Ji9lFlNfo/jfbUv4FUj2w9y3+y1qpzipskdZRPTbr+vsypJzqS0jbsgNzgFZDjFy9fNAyG70nN4uQtBHwVdKy7YzO/RExtcawJRsAj1SDqJIm6vpEqqj/DqrlA05oLT+9uj+pH2NvoeP7gC+Py4wWQ9J2dBWijoiqJXkA/pj/tFLPtulepPecR/OflYA7x2FaY6Fzqv0VwNOAr+fbb6PQRWNBl+TUnGvHeyL9lN56V0Oto2DhLU6lIs9HVR3PAVpN3SsLneXRiisLkvS7Pn/vjFn1iuto0tbcIaQ6L+8lFfGso1gD4E4+RjTQD079W5jcC1ycV8IG9StJ2xdMIJ4oWnt6NQfjn5R05ERYBZD0YdLJ7NPyXYdIOjEivlRlvCYuRgrrt206H1geeAJQ50Kxtbrymg4GntPJEewqs9Emm5NSQYLhq7BtWeUrvfXeVOuohUTE7ZLWr/r9DtBqKLyy8PLFf0kly0TEeZKWyqd0DsjL73VOHxZvALyILc5Oxe0T8uGJQT2JVA/u+/n2a0jlA94k6YyI+OyA480G9s7H4x8k16yLiFUqzG0iaf3p1YkQnGVvAZ7bWW2XdDgp12+gAE3SGyP1pSya81Ja77ZpTv/4IOlC8ZBxmdTYegJpq6uTmzwj39cmHxjvCYyk9NZ7NNc6qjcHbSnSlmflVWIHaPUUW1noTlYs7JH88d95u/Pv1Gx8HM00AL6DdGXTWVnYgRSgvYlUQuD9FcZcHZgVuTm5pE8B3yXVXrqUVEl6EGN25dUyrT+9KmlDUoeMklv5TZjSnQoREfdXTHSeSToJulmfz7XldOQCObh/N+mAzU9Jz8tbx3dWY+J00snd0/PtN5Gq4bdGg+89rabyraMgPR87z79HSMWIq54ydYBWU/GVBUmrkOqM9bbdqHrk+XRJTySdiLyQtKXw8RrzmwpcFhGbUrYB8EbACyNibv53vgb8AtiGdAihijU6wRlARNyT6/3cL6lK4dodImLYtqmkfUhP8iXZRDi9egzlt/KbcJlS795Ob8vdgcsHHSQiPqFUyPnMGiU6xoSkt5LyBC8HtokWdA8YK5E6M1zKUJmNAyJipC27MdPQAa2JpGjrKEmbkU5Ud4r+Xgv8MiL+XXVMB2j1NLGy8APScedfUODIc0R0thF+lov8LVOnLlhOln9Aw6tjl/AkhreseZjU2uOhisEUwPU50OtuPP8HSTOo9n+7IwsHY/3uW2JMoNOrTWzlN2FP0gXS4fn2L4BPVxkoH875DNVLdDRO0jWk18QDSQHa0t1J33VqjE0ULS6zUfyA1gRTrHWUpOeSnofHAKeS0l82A86R9LKIuLTKBB2g1dPEysKyEfHeuhNTT5/Qns/VKYwJ6RTS+ZK+Q1f9pZp5L78BfqLUKB3SFc0FShW3qwZou5HeDI/Mt39N+l3NA1422kHy1vVLSE11u4OxFWlhv8eSJtDp1U7AXWwrvwmR2ih9pOCQV0naPCJ+t/gvHRcrkFZnPsnCfYXb1i6smImwOhWpSfxUYJ2I+MR4z2cclGwdtQ+wW0R8r+u+7+Wg76N0FXYfhAO0CvKD+vXA3RFxr6RdSadJrmbhHnaDurTQkedOHbZlSJF8Z7xnktqt1AnQlibVfOtuo1Q37+W9wLsYyuE7B/hqRDwMPKfKgJFa6iyqiftdAwz1ECkQ7S3lcDsVi+lOMBPh9Oq3S27ll9ZgUv8s4CJJNzL8YqkVJ/CaqDE2QYy0OrXqWE5kJPkC7GWkLejJpmTrqA16gjMAIuIHkr5YdYIO0Ko5mpSku0xOln8M6Ym4FSlReccaY3+V9MC5hRpHnjsFMZXayuzVWWKVtDk1T+301nopIQdiR+Q/tZR+M8xJtL+R9N2IuK7n36rb0H0imE2LT6/m38EvIuJfFNrKb0BTSf1VDs9Yw/Lq1KrAdcDVEfGIpJVJB8tm066t959I+hCpkHB3kP+f8ZtS86Js66iR/q8q/z86QKtmC1Ii4LLAbcDKOVfqa8A1Ncc+hXS6sFTbjZnd+98R8TtJzxzpGxZnEYHPvcDvIvXlrDLmSqStyBflu34OfCAiBlnp6mjqzXA/SXvkbSokrU46dbpVjTEnglafXs25WKcAG+bbD5NyGFujs4VU+uJmsp7AaztJu5Mu5O8G7pL0MeAE0s5A255PndWzgxnahp7PElqjrp+o3zqqt5/rsM9VnZcDtGrm5sKDD0r6S0Q8BLUr6nf8r2rRykV4UNIuEXEKgKSdqRHRZy8lBSXn5dvbkMpWHCTpwIj4xiK/c9GOJW2b7k16kO+R7xu4oXBTb4ak3LvLlXqurkZa7Tyw8L/RRhPh9OqfJK0dEX8d74mMJNdOPDsi7stlXzYH9ouIKyqOdyHwqq5SMk8Avh8RWxabtFXxQWDTiPi9pOeT8l93amOaQERMhl2A0ap6Ad+vn2vdMR2gVTSjK1qe0RM51+2j+TNJL42In9Ucp2M34CSldhbzSbloe9cccz7wzK6rjjVJ7Sw2J51KqxKgPTUi3tB1+xOSrqozSUnLkhI014mInSU9DXhaRHy/yngR8UlJvyUVFr0b2DZSu68l3UQ4vbo8cE0OWLq3acY9GbvHARFxek412A44jLRy/LyK4y3XU0rm38qt52xcPRwRvweIiIsk/bmNwRmApJnATV07A48F1u7Mf0mjwq2joLlcSwdo1fRGy91/r5ssvwewr6T7SUmLtfJ98jH2Z+VTKrOBXUgB1Ho15rhOJzjL/8Ytkp4SEXdIemSkbxzBUpJWiYg7YUE9uLpXdseQEvk3zrf/TtqS/H6VwXIg+ingDNIW9575iHbdVdNWmmCnV0/Jf9qus/W6LXB8RJya83+qWkrSsp18oXzqeVrdSVptvVtej3bfbll5kRMZfhDr4Xxf27ZiSyndOqoxDtAqaPhkUrEnhVIB3deQVtGeQ/p9v6RqTZYu/5C0H0P1xWYDd+bTrVUD1C8BV0rqPHleTlr9qmPDiNhVqTk1EfFAzaT+i0jbUaco9SL9Emlrd5Oa82yrCXN6NRro5dqQ+Xmbc0fg1fm+yjkqpAuOn0s6Jt9+NxMjUF3S9dvy6txuW3mRqTlvE4CcT73ExgZRuHVUk5bYX8JEFRE35yeHhu6KgVelJH0F2Il0aOEEUvmK6wsEZ5B6bx7O0Fbpr0hFYKflzw0sUvuoOcDW+a7DSS9oJy/6uxZrWP00SctQYVVO0lp5xXDbiIg834eBD0iqu13cWhPp9Kqk1UiPmc7j55ekQya3j9+s+tqTVDPp+Ii4SdJ6pOdPJRFxkKTbGAr2jo2IkwrM02qYYOVFHpa0TkT8BUDSUylzQM1qmjJ/fuvatk1qkp5F6hfZ2d5cGnjDoEnEkv5Dqor8mYj4Vb7vL1Gvz9iYknRLRKxZ4/sPBu4hbeu+h5S4e01EHDDgOFdEam2FpN91lzzp/tySStKpwEKnVyOiNadXJf0COB84Pt+1G6l1WFs7H5i1gqRXklqP/YT0nvMy0vO9FS2pJjOvoLXPYaSKxOcBSNqGVBvs+QOOszrwZuCL+WTXSRT6fTdRZmMR6l497E9arbiflND+Q+DzFcbpzrfqze9pWy5WEybC6dXVIuJTXbc/k+fbCpI+EBGH9eTyLRAR+1Qc98ukvMgHSStxmwLv7JzaNluciPixpC1JeZEAB0XEn8ZzTpY4QGufx3aCM4CI+KWkQ0b6hn4i4h5SHZ6jJW1IWlFYRtL5wLci4tgacyxWZqOJEzUdeRvys/lPHfMX8fd+t5c4E+T06p8krdt5Y8nbNG1qyt1JPn5wxK8a3IsjYm9JrwBuJeW2/QTnodkA8oX1jflw1jqAA7QWcIDWPv+R9MKI+DWApK2oWbcsIq4B9pL0YVJPsLeRaoxVVbLMRvETNYvqINARg7fVWabrBFb336F+WZXWa/PpVQ31OnwMcHUuswFpxfmicZtYj84FUUQM3Ih5lLYEzoqIWyUt8RcNVo6kC4BXkl7TrgTukfTTrkr7Nk4coLXPB4DvSOokuE8H3jDC149aXlE6k+r9xjqKldlo6ETNojoIvBD4P9LK4iCaLKsyEbT59Gp3r8Nvdf391LGeyGhIOhw4MCL+nW8/EfhYROxVccg78wnOlwGfzweMJk0FeCtiuUg9pXchPYf2JfWVdoA2zhygtUxEXCZpXYaf4mxV2xqaKbNRTG8HgVwU9HOkXLRX9/2mkcdbu8zMJpaJcHp1ApXX6NiiE5wBRMS/8ip5VW8GdgZOjIi7Ja0NDJwSYZPajPxxa+DbkTriVK1naQU5QGuJPrlYj+aP60lqW2HD4mU2mpA7B3wOeCap39xpkVp02eh8n9SuJnpPr5KCgi+Pz7SGNJV836B+q1uVC8tG6lV7aNftv5LK6piN1q8lXU+KB94l6XG4zEYrOEBrj58w1Kh2LeC+fPtxwM1Aa4rrRcRtpLpqC+TVlv+RWkmNK0lPBj5JOpV0EPCmKrXkbEKcXm0q+b4pl0k6jHSqeAppG+myQQeRdHJEvEXSZfRZte4Jps1G8l5gI+AvEfFw3ibfY5znZDhAa41OLpakI4DzI+LMfHt7UgJw60jq5MftDswCHj++M1rgRlK1+yNIb4LvkLTgkxUOCUxWrT+9OgbJ96X9P1IpnStJ/4c/BvaqMM6h+WOdNlE2iUmaERFzSQdsbsj3LUs6lBbjOTdLHKC1z5YRsWfnRkR8R9JAhVWbJmkWKSh7E+nJvTvwqnGd1HBnkpbo+5XwWI3BDwlMVq0/vdrAid1GRcR9pFPUdceZkz/+RtJK+e//rDuuTSoXk+rmddq5Ten56MMm48wBWvtMkbRFRFwAIOn51G8aXoSkD5DeXB5DynPZhLTa9+3xnFcfD0fE7r135nZAldvqTEIT4fRqvxO7HW2Z4wJ5heKjpJPQO+c8yadFxPcrjLUX6cTdyvn2ncDnI+KwcjO2JVWnA0pEtOL9xRbmAK193gucJqmTU/MYUk/NNvgKqTjtO7v6trXuTRBYQ9KXI2LBSUNJq5L6M060U3/jZiKcXu09sTsBHEPaft843/47qeH59wcZJJdEeBfpcM6lpFWPzYGvSPpnRHxrpO8368gr4xvkm9d2Tmzb+HOA1jIRcYGkdRheZmPcC4JmzyB1JLhQ0g2kVbQ2Xn29HjhX0scj4lNdK2cnRsRB4zw3a4hSouFGdG2/trBx+IYRsauk7QAi4oGKjeffAewQEVd33XeOpB2BIxleE85sIZKWAU4HXkzK250CrCvpXGDHnJ9m46iNb66WAue5pDyqdRfTDmnMRMQfc9mCNUm1ll4LPEnSSZ03nDaIiP+QKmO/VtKBpJWzExycLbkkvR84i9QndOf8sS0rz92GvenlN8kqr8Or9gRnwIKuIU+qODebXDolaNaIiI0jYiPgyaTUgI+M37SswwFay0h6L/AP4Oek0hs/YXi19HEXEfMi4ocR8VpSZf5raUFNrI4c0K5OqtP2XtIW0A8lPaMtwa4V9w7SFt/fImK7/Pf7x3dKfZ2fizzPkPRCUvusH1QYZ6SfbaKUHLHx9Tpg99y3GYCIuBt4Z/6cjTNvcbbP3sDMiLh5vCcyEkkrAOtGxBXAFyV9abzn1KW7v+cDpMbunWrt80nNgG3J8r+IeFDSUpKmRMR1ktYf70n1sT9p5eJ+4AvAj4DPVxhnlRFOsK5UcW42uczod/I3Iu7KK7s2zhygtc8dEyA4ezmp2fo8YG1JzyJV6m9FqY2G+ntau/0n9wm9GviCpFtoWZkASZuR6pbNzHddC5xTsYjyL1j0CdbzKoxnk89/R/jcf8ZsFrZIDtDa5+e5bc23GaqS3rZWT58kvTmcDRARl0t66vhOySaj3P91BvAeYDppBfpzpM4bs8dvZsNJei6pTMlXSac2p5CeQ+dIellEXDrIeBPw9Kq1zzqSzuhz/xRa1LlmMnOA1j6dXpZv7LqvddtyEXFHd3V+epKfzcbI50knnY/Ptx8E3i5pd2AHYM64zWy4fYDdIuJ7Xfd9T9KlpLpor60yqKS3AD/OuUNIegLwMpfZsFHYa4TPtSrvebJygNYyE2R77n5JTyIXAs3JzveM54Rs0tqG/ifOvglcw9BJtfG2QU9wBkBE/EDSF2uM+6GIOLlrvH9L+hAus2GLEREn5hXo3SPia+M9H1uYA7SWkrQKw+s5/W0cp9Pro6TtzadI+jWwHvDqcZ2RTVZTI+LR3jsj4lFJC90/jkbK6Smd79Oq3Dtrr4iYJ+kdgAO0FnKA1jKStiFVu38SKQl/OvAvYJXxnFe3iLhU0tbA80j5Cr/tPqptNoYeI2nZXPtuAUnLkXLT2mJ6Ty/TYZ+rMe4dkl4fEWcBSHoDcGeN8Wzy+ZWk7SPiO+M9ERvOAVr7fBF4EanC86akRuRrj+eEekn6GKnw69njPReb9E4HTpS0e25EjqQVSaeMzxzXmQ3X29e0W512aR8AfpAPFgE8Arymxng2+cwG9pb0X1IO5xRgfkS0ZlFgsnKA1kIRcYOkaRExHzhe0uXAAeM9ry4rAJdI+gMp1+e7EfG/xXyPWRM+RWo5dqukG/N96wE/BA4cpzktpKm+phHxx1x8ubs13Lwm/i1bYj1rvCdg/U2ZP7+Nva4nL0mXRMRzJJ1D6qn3V+AHEdGqU5w5ufTlpGbNWwDfj4h3ju+sbLKStC6wSb55ZUT8aTzn0zRJMyJirqRl+32+d8vXzCYer6C1z2GSHk9aMTsNWJGRj0OPi3yV/iNJN5GKb+5GahFiNuZyQLZEB2U9LialQDzA8C3SKfm2DwrYqEhaEzgY2IjhB9NatSgwGTlAaxFJqwI3APdHxGWSnkc6MXkkLTo2n2stvRl4G7Ac6VCDn8xmYyQiNs0f3U/Z6voGqTD6xsDOwLuBP4/nhCzxk7slcmHNm0l9JK+U9FogSE2/25YjEMCGwPsjQhHxuYi4ZbwnZTbZSDp0NPeZjWCliPg68EhEXEw6NPDy8Z2SgVfQ2uSDwKYR8XtJzwd+DezU0qPPa0XESH3czGxsbNnnvq3GfBY2kT2UPz4gaS3gH8DK4zgfyxygtcfDEfF7gIi4SNKf2xacSXpjRJwJvK2nzRMAEXH02M/KbPKR9EbgTcDaPf0UV8SNrm0w5+e0laNJrdHmAq1675msHKC1R28hy0e7b7ekWfpMUm2pzfp8zseBzcbODaR0iM3zx477gPPGZUY2IUXEh/NfT5b0G2CFiLhuPOdkictstISkv7LoIGe+T9SYWS9JT4iIf4/3PGxik/Qi4OkRcWTus7xiRNww3vOa7LyC1hJNFbJsgqQdgLMj4j5JnyJdxe8XEVeM89TMJpv7ci/FjRleImG3cZuRTSiS9iUdCliNVDFgGulk5wvGc17mU5xWzQE5ONsc2A44ifTENrOxdSzwfOCVwI2k9AMf4LFB7ERqL/gAQET8ndQtxsaZAzSr4uH8cVvg+Ig4la6rdzMbM5tHxK7APRFxEGnVY4NxnpNNLP+NiId77nPuUws4QLMq5udtzh2BX+T7po/jfMwmq85q2TxJy0bEvYCbXNsgbpH0AtLr+lKSDgB+P96TMuegWTV7AvuQVs9ukrQe8KtxnpPZZPTv3BruZ8DZkv4J3DrOc7KJZU9SmspMUomWC0gdBWyc+RSnmdkEJWlqRMyTtBSp/drjgJMi4r7xnZlNNJKWBZaKiAfGey6WOECzgUn6MvAp4EHSytmmwDsj4pRxnZjZJCJpKvCDiHjleM/FJjZJTwWeSteuWkT8dPxmZOAcNKvmxTnXZTvSdsr6wIfGd0pmk0tEzAOemFfPzCqRdBBwCXAA8OH8x6/nLeAcNKtjS+CsiLhVkpdizcbeJcBZkk4ll0kAr37YQN4IPNXb4u3jAM2quFPSMcDLgM9LWhqYOs5zMpuMNs4f391133zAAZqN1u0OztrJAZpV8WbSKZ8TI+JuSWsDh4zvlMwmn4jYerznYBPexZJOI/VZ/l/nTq/Cjj8fEjAzm2AkvXykz/vN1UZLUr8SSfMjYpsxn4wN4wDNBiZpTeBgYCOG9/9zQ3ezMdD1proMqb3Ttfn2M4HfRcTzxmViZlaMtzitim8A3yblv+xMyn/583hOyGwy6Wxt5q2pvSLi0nx7c+AD4zk3mxgkPSUXGn9Gv89HxPVjPScbzsezrYqVIuLrwCMRcTEwGxhxy8XMGjGzE5wBRMTvSKtoZotzRP74kz5/LhqvSdkQr6BZFQ/ljw9IWgv4B7DyOM7HbLJ6UNIunSLRknYmtesxG1GnwHFEPKX3c5JuGfsZWS8HaDYQSU8A7sv9/44C5gBzSSeAzGxsvQ04WdJx+fa1wK7jOB9bMjg5vQUcoNmoSdoB+CZwP3AT8AZgFrBCRFw3nnMzm4wi4g/AsyQtn2/fP85TMrNCHKDZIPYHnhcRV0naGvhERLxwnOdkNqlJWhEQsIwkACLi/HGdlLXeog4HZI4NWsC/BBvEoxFxFUBE/EqSi9OajaO8qv0l4PGkvrjrAlcDm47nvGxC+MkIn/vfCJ+zMeIAzQYxXdLTgSn59ozu2z6WbTbm9iOlGZwTEZtI2hbYfpznZBNAv8MB1i4us2GDWJbU469zFPsxXbd/PI7zMpusHomIO8kX2xHxc1LhWjOb4LyCZqMWEWuP9xzMbJi5kqYAN0raE/grsNz4TsnMSnCAZmY2cR0ArAB8BDgGWBF4z7jOyMyKcC9OMzMzs5bxCpqZ2QQl6eB+90fEPmM9FzMry4cEzMwmrge7/swDXobbrpktEbzFaWa2hMgdBb4TEduN91zMrB6voJmZLTkeANYa70mYWX3OQTMzm6AkfZGhxtZLkYrW/mH8ZmRmpThAMzObuB5gKEB7BPgqcNb4TcfMSnGAZmY2AUnaGtgGeCYpSLsI+HFEPCxpekQ8NK4TNLNanINmZjbBSNoeOBk4jRSkvQg4GzhD0obAj8ZxemZWgFfQzMwmnv2A7SLi9133XSXpAuB3wKnjMy0zK8UraGZmE88yPcEZABFxHXAb8M6xn5KZleQAzcxs4pkuaVrvnZJmAFMiYt44zMnMCnKAZmY28fwAOEnSip07JD0OOCF/zswmOOegmZlNPB8FjgFukfSnfN+6wJn5c2Y2wbnVk5nZBCVpLVKZjSnAtRFx8zhPycwKcYBmZmZm1jLOQTMzMzNrGQdoZmZmZi3jAM3MbACS1pY0X9JiD1lJmi3pwrGYl5ktWXyK08yWaJL+CqwOrB4R/+y6/0pgY+ApEfHXcZmcmdkieAXNzCaDm4CdOjckPRNYdvymY2Y2Mq+gmdlkcDLwVuCIfHtX4CTgMwC54OsRwMuA/wDHAZ+LiEclTQW+AMwG7gO+3D1w/t5DgJcDjwLfBD7hav5mVodX0MxsMrgEWEHS03PAtSNwStfnjwBWBNYBtiIFc2/Ln9sDeCWwCfAsYPuesU8AHiEVit0EeAnw9kZ+CjObNBygmdlk0VlF2xb4A3Brvr8TsH00Iu7P+WhfBt6SP/8m4NCIuCUi/g0c1BlQ0pNIK2d7RcSDEXEn8JU8nplZZd7iNLPJ4mTgfOAppO3NjpWAaUB3Ff6bgTXy31cHbun5XMf/5e+9XVLnvqV6vt7MbGAO0MxsUoiImyXdRFrx2r3rU/8EHiYFW9fn+9ZiaIXtdmDNrq9fq+vvtwBzgZUi4pEm5m1mk5O3OM1sMtkd2CYiHuy6bx5wBvBZSctL+j/ggwzlqJ0BvF/SkyU9Hti3840RcTtwLvBlSStIWkrSUyVtNSY/jZktsRygmdmkERF/jojL+3xqT+BB4C/AhcCpwDfy544DzgGuBq4Azur53rcC00mrb3cD3wFWKz55M5tU3CzdzMzMrGW8gmZmZmbWMg7QzMzMzFrGAZqZmZlZyzhAMzMzM2sZB2hmZmZmLeMAzczMzKxlHKCZmZmZtYwDNDMzM7OWcYBmZmZm1jL/Hy7fik/KgR2IAAAAAElFTkSuQmCC\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Creation of the three types of model\n",
        "from sklearn import tree\n",
        "\n",
        "# Assumes binary yes/no classification response\n",
        "def models(X_train, Y_train):\n",
        "  from sklearn.linear_model import LogisticRegression\n",
        "  log = LogisticRegression(random_state= 0)\n",
        "  log.fit(X_train, Y_train) \n",
        "\n",
        "  from sklearn.tree import DecisionTreeClassifier\n",
        "  tree = DecisionTreeClassifier(criterion= 'entropy', random_state= 0)\n",
        "  tree.fit(X_train, Y_train)\n",
        "\n",
        "  from sklearn.ensemble import RandomForestClassifier\n",
        "  forest = RandomForestClassifier(n_estimators= 10, criterion= 'entropy', random_state= 0)\n",
        "  forest.fit(X_train, Y_train)\n",
        "\n",
        "  print('The accuracy of the Logistic Regression: ', log.score(X_train, Y_train))\n",
        "  print('The accuracy of the Decision Regression: ', tree.score(X_train, Y_train))\n",
        "  print('The accuracy of the Random Regression: ', forest.score(X_train, Y_train))\n",
        "\n",
        "  return log, tree, forest\n"
      ],
      "metadata": {
        "id": "CawRpvpmxgrr"
      },
      "execution_count": 60,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Function deployment \n",
        "model = models(X_train, Y_train)"
      ],
      "metadata": {
        "id": "UIz5JQac6NIh",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b64fd16e-ae4a-4138-8641-e232feba2593"
      },
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The accuracy of the Logistic Regression:  0.9912087912087912\n",
            "The accuracy of the Decision Regression:  1.0\n",
            "The accuracy of the Random Regression:  0.9978021978021978\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Creation of the confusion matrix, to see how accurate it is at the time of the predictions\n",
        "from sklearn.metrics import confusion_matrix\n",
        "cm = confusion_matrix(Y_test, model[0].predict(X_test))\n",
        "tp = cm[0][0]\n",
        "tn = cm[1][1]\n",
        "fp = cm[0][1]\n",
        "fn = cm[1][0]\n",
        "print(cm)\n",
        "print('Accuracy: ', (tp+tn)/(tp+tn+fp+fn))"
      ],
      "metadata": {
        "id": "VgPiayu6AW4O",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e7c83c60-4043-4e98-a9e4-a1627781cc15"
      },
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[66  1]\n",
            " [ 3 44]]\n",
            "Accuracy:  0.9649122807017544\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Another way of obtaining classification accuracy and score\n",
        "from sklearn.metrics import classification_report\n",
        "from sklearn.metrics import accuracy_score\n",
        "\n",
        "for i in range(len(model)):\n",
        "  print('Model: ',i)\n",
        "  print(classification_report(Y_test, model[i].predict(X_test)))\n",
        "  print(accuracy_score(Y_test, model[i].predict(X_test)))\n",
        "  print()"
      ],
      "metadata": {
        "id": "dkuvAEsIHOgB",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c70061fe-7f8f-44f7-be7e-0eacc48e8693"
      },
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model:  0\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.96      0.99      0.97        67\n",
            "           1       0.98      0.94      0.96        47\n",
            "\n",
            "    accuracy                           0.96       114\n",
            "   macro avg       0.97      0.96      0.96       114\n",
            "weighted avg       0.97      0.96      0.96       114\n",
            "\n",
            "0.9649122807017544\n",
            "\n",
            "Model:  1\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.94      0.96      0.95        67\n",
            "           1       0.93      0.91      0.92        47\n",
            "\n",
            "    accuracy                           0.94       114\n",
            "   macro avg       0.94      0.94      0.94       114\n",
            "weighted avg       0.94      0.94      0.94       114\n",
            "\n",
            "0.9385964912280702\n",
            "\n",
            "Model:  2\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.96      1.00      0.98        67\n",
            "           1       1.00      0.94      0.97        47\n",
            "\n",
            "    accuracy                           0.97       114\n",
            "   macro avg       0.98      0.97      0.97       114\n",
            "weighted avg       0.97      0.97      0.97       114\n",
            "\n",
            "0.9736842105263158\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Las predicciones del modelo vs las reales\n",
        "pred = model[2].predict(X_test)\n",
        "print('Our model prediction: ')\n",
        "print(pred)\n",
        "print()\n",
        "print('Actual prediction: ')\n",
        "print(Y_test)"
      ],
      "metadata": {
        "id": "WNXmUqSQJQZe",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cb54c75b-f0c5-4012-930b-adf5a13a3d56"
      },
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Our model prediction: \n",
            "[1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 1 1 1 0 0 1 0 0 1 0 1 0 1 0 1 0 1 0\n",
            " 1 0 1 0 0 0 0 0 1 0 0 0 1 1 1 1 0 0 0 0 0 0 1 1 1 0 0 1 0 1 1 1 0 0 1 0 0\n",
            " 1 0 0 0 0 0 1 1 1 0 1 0 0 0 1 1 0 1 0 1 0 0 1 0 0 0 0 0 0 0 1 0 1 0 1 1 0\n",
            " 1 1 0]\n",
            "\n",
            "Actual prediction: \n",
            "[1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 1 1 1 0 0 1 0 0 1 0 1 0 1 0 1 0 1 0\n",
            " 1 0 1 1 0 1 0 0 1 0 0 0 1 1 1 1 0 0 0 0 0 0 1 1 1 0 0 1 0 1 1 1 0 0 1 0 1\n",
            " 1 0 0 0 0 0 1 1 1 0 1 0 0 0 1 1 0 1 0 1 0 0 1 0 0 0 0 0 0 0 1 0 1 0 1 1 0\n",
            " 1 1 0]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(len(X_test)):\n",
        "  if pred[i] == Y_test[i]:\n",
        "    print(\"Correct\")\n",
        "  else:\n",
        "    print(\"False\")"
      ],
      "metadata": {
        "id": "RJKkqJqua4ZX",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ff3a1778-3028-4903-992e-726a0804609f"
      },
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Correct\n",
            "Correct\n",
            "Correct\n",
            "Correct\n",
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            "Correct\n",
            "Correct\n",
            "Correct\n",
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            "Correct\n",
            "Correct\n",
            "Correct\n",
            "Correct\n",
            "Correct\n",
            "Correct\n",
            "Correct\n",
            "Correct\n",
            "False\n",
            "Correct\n",
            "False\n",
            "Correct\n",
            "Correct\n",
            "Correct\n",
            "Correct\n",
            "Correct\n",
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            "Correct\n",
            "Correct\n",
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            "Correct\n",
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            "Correct\n",
            "Correct\n",
            "Correct\n",
            "Correct\n",
            "Correct\n",
            "Correct\n",
            "Correct\n",
            "Correct\n",
            "Correct\n",
            "False\n",
            "Correct\n",
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            "Correct\n",
            "Correct\n",
            "Correct\n",
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            "Correct\n",
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            "Correct\n",
            "Correct\n",
            "Correct\n",
            "Correct\n",
            "Correct\n",
            "Correct\n",
            "Correct\n",
            "Correct\n"
          ]
        }
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}