ScikitLearn.ipynb

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      "authorship_tag": "ABX9TyOZ2cR750kbV/fcWz8sGqlM",
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      "name": "python3",
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    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/bijouvj/ST-summer-2024/blob/main/ScikitLearn.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "6D5sHcAN-gK8"
      },
      "outputs": [],
      "source": [
        "from sklearn import datasets\n",
        "import numpy as np"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "iris = datasets.load_iris()"
      ],
      "metadata": {
        "id": "oJp2dPGY_RYS"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X = iris.data[:, [2, 3]]"
      ],
      "metadata": {
        "id": "b6K0q2LU_TGb"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y = iris.target"
      ],
      "metadata": {
        "id": "AbLlkx3c_WiT"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print('Class labels:', np.unique(y))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FWZeG4sR_Yfv",
        "outputId": "0243a7c9-efb5-4355-d59d-183140291fe4"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Class labels: [0 1 2]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lYExx34A_ajV",
        "outputId": "0c4887d4-e51f-499a-ca82-e83e78fc34d7"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(150, 2)"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# we now use a set of powerful library functions\n",
        "from sklearn.model_selection import train_test_split"
      ],
      "metadata": {
        "id": "Meh_wYxc_cqh"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(\n",
        "    X, y, test_size=0.3, random_state=1, stratify=y)"
      ],
      "metadata": {
        "id": "6kP90h_F_lRJ"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train[:10]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dSr5B6AsBL51",
        "outputId": "874215ff-4747-49d7-81f6-396d035e87ba"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[1.4, 0.2],\n",
              "       [1.7, 0.2],\n",
              "       [5.3, 2.3],\n",
              "       [5.7, 2.1],\n",
              "       [1.2, 0.2],\n",
              "       [5.6, 2.4],\n",
              "       [6.6, 2.1],\n",
              "       [1.2, 0.2],\n",
              "       [5.8, 1.6],\n",
              "       [4.6, 1.3]])"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print('Labels counts in y:', np.bincount(y))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vhKS25No_tYk",
        "outputId": "69597f71-337b-41e0-c52c-f39cda5f6d97"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Labels counts in y: [50 50 50]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print('Labels counts in y_train:', np.bincount(y_train))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IwIAvTEEAVPV",
        "outputId": "9628b48f-2c14-486e-ca04-f3d7886f9853"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Labels counts in y_train: [35 35 35]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print('Labels counts in y_test:', np.bincount(y_test))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pLz-Cg-UAYqY",
        "outputId": "49d309fd-f301-4f95-f6ac-b03047249166"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Labels counts in y_test: [15 15 15]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.preprocessing import StandardScaler"
      ],
      "metadata": {
        "id": "U5775hj-AbVQ"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sc = StandardScaler()"
      ],
      "metadata": {
        "id": "Ew42HU6HAwMQ"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sc.fit(X_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 75
        },
        "id": "1G-81hmyAyQ0",
        "outputId": "8dde740d-a589-4810-d961-780a75ad6e48"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "StandardScaler()"
            ],
            "text/html": [
              "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>StandardScaler()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">StandardScaler</label><div class=\"sk-toggleable__content\"><pre>StandardScaler()</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X_train_std = sc.transform(X_train)"
      ],
      "metadata": {
        "id": "bbnm-SPjA0SL"
      },
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# note that we are scaling X_test using scaler fit to only X_train\n",
        "X_test_std = sc.transform(X_test)"
      ],
      "metadata": {
        "id": "kTM6SRMDA2y7"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_test_std[:10]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0r1MnhP8A5t_",
        "outputId": "913edc29-214c-46c0-daf0-cc462b8d233a"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 0.89820289,  1.44587881],\n",
              "       [-1.16537974, -1.04507821],\n",
              "       [-1.33269725, -1.17618121],\n",
              "       [ 0.39625036,  0.65926081],\n",
              "       [ 0.34047786,  0.2659518 ],\n",
              "       [ 0.11738784,  0.1348488 ],\n",
              "       [ 1.12129291,  0.79036381],\n",
              "       [ 0.39625036,  0.3970548 ],\n",
              "       [ 0.84243039,  0.92146681],\n",
              "       [-1.38846976, -1.04507821]])"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sc.mean_"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NJnTCKZoBJYZ",
        "outputId": "64410b96-d869-4945-8abc-7f6d19364ac6"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([3.78952381, 1.19714286])"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sc.var_"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jw67l6r6BSQm",
        "outputId": "df6fb941-82ff-477c-f9f4-351c9bdb7248"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([3.21484263, 0.58180136])"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.linear_model import Perceptron"
      ],
      "metadata": {
        "id": "nbkB0XpfBUwG"
      },
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ppn = Perceptron(eta0=0.1, random_state=1)"
      ],
      "metadata": {
        "id": "85eINAyQB8Uz"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ppn.fit(X_train_std, y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 75
        },
        "id": "Z4g3hVHaB-WW",
        "outputId": "cc794c5d-1829-475b-e299-d4d539ba5753"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Perceptron(eta0=0.1, random_state=1)"
            ],
            "text/html": [
              "<style>#sk-container-id-2 {color: black;background-color: white;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Perceptron(eta0=0.1, random_state=1)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">Perceptron</label><div class=\"sk-toggleable__content\"><pre>Perceptron(eta0=0.1, random_state=1)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# the model is trained, so lets make predictions on test set\n",
        "y_pred = ppn.predict(X_test_std)"
      ],
      "metadata": {
        "id": "t5zaqQv4CAFF"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print('Misclassified examples: %d' % (y_test != y_pred).sum())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IPJokojZCNlX",
        "outputId": "852c8b84-3aff-4e10-b5eb-37d030491d2b"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Misclassified examples: 1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ppn.coef_"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zkPjyDPjCQYn",
        "outputId": "030d764c-ff43-4d5b-c7f2-6d2526bf7476"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[-0.10655204, -0.11836728],\n",
              "       [ 0.31790327, -0.3670884 ],\n",
              "       [ 0.36018414,  0.30003858]])"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ppn.intercept_"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DIngMeOWC2Qv",
        "outputId": "2353f4f2-a9ce-46a0-be19-3adc12d8fc54"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([-1.00000000e-01, -2.77555756e-17, -4.00000000e-01])"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.dot(X_test_std[0], ppn.coef_[0]) + ppn.intercept_[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NSdW5iz6C90Q",
        "outputId": "d9c709f1-dada-4cc8-9b94-2b564024c2f5"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "-0.36685009478552033"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.dot(X_test_std[1], ppn.coef_[1]) + ppn.intercept_[1]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pD6RQbfLDN5f",
        "outputId": "85a3852d-c64c-4ccb-9f30-ecbaf856485f"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.013158059353653745"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.dot(X_test_std[2], ppn.coef_[2]) + ppn.intercept_[2]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "raNoh8fVDSG7",
        "outputId": "60d4a3c1-d80d-4184-f1ab-e3e398aad83b"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "-1.2329161584926842"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred[0], y_test[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "q8V4EsOpDY6R",
        "outputId": "23c59b00-39fd-4e68-b3de-2e19fc1892f6"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(2, 2)"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import accuracy_score"
      ],
      "metadata": {
        "id": "pS5f_J5eCdPf"
      },
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print('Accuracy: %.3f' % accuracy_score(y_test, y_pred))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SvA24rr6Ct-T",
        "outputId": "e37fd243-e0e7-4d22-bd37-12d50781aba5"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy: 0.978\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print('Accuracy: %.3f' % ppn.score(X_test_std, y_test))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EWG16D4ECv8d",
        "outputId": "0c5791cf-22d9-4db6-9268-f6cbc53273dd"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy: 0.978\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from matplotlib.colors import ListedColormap\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "def plot_decision_regions(X, y, classifier, test_idx=None,\n",
        "                          resolution=0.02):\n",
        "\n",
        "    # setup marker generator and color map\n",
        "    markers = ('o', 's', '^', 'v', '<')\n",
        "    colors = ('red', 'blue', 'lightgreen', 'gray', 'cyan')\n",
        "    cmap = ListedColormap(colors[:len(np.unique(y))])\n",
        "\n",
        "    # plot the decision surface\n",
        "    x1_min, x1_max = X[:, 0].min() - 1, X[:, 0].max() + 1\n",
        "    x2_min, x2_max = X[:, 1].min() - 1, X[:, 1].max() + 1\n",
        "    xx1, xx2 = np.meshgrid(np.arange(x1_min, x1_max, resolution),\n",
        "                           np.arange(x2_min, x2_max, resolution))\n",
        "\n",
        "    lab = classifier.predict(np.array([xx1.ravel(), xx2.ravel()]).T)\n",
        "    lab = lab.reshape(xx1.shape)\n",
        "\n",
        "    plt.contourf(xx1, xx2, lab, alpha=0.3, cmap=cmap)\n",
        "    plt.xlim(xx1.min(), xx1.max())\n",
        "    plt.ylim(xx2.min(), xx2.max())\n",
        "\n",
        "    # plot class examples\n",
        "    for idx, cl in enumerate(np.unique(y)):\n",
        "        plt.scatter(x=X[y == cl, 0],\n",
        "                    y=X[y == cl, 1],\n",
        "                    alpha=0.8,\n",
        "                    c=colors[idx],\n",
        "                    marker=markers[idx],\n",
        "                    label=f'Class {cl}',\n",
        "                    edgecolor='black')\n",
        "\n",
        "    # highlight test examples\n",
        "    if test_idx:\n",
        "        # plot all examples\n",
        "        X_test, y_test = X[test_idx, :], y[test_idx]\n",
        "\n",
        "        plt.scatter(X_test[:, 0], X_test[:, 1],\n",
        "                    c='none', edgecolor='black', alpha=1.0,\n",
        "                    linewidth=1, marker='o',\n",
        "                    s=100, label='Test set')"
      ],
      "metadata": {
        "id": "ZFboQrBXD1V1"
      },
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_combined_std = np.vstack((X_train_std, X_test_std))\n",
        "y_combined = np.hstack((y_train, y_test))"
      ],
      "metadata": {
        "id": "-RFx8pMpEPEC"
      },
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plot_decision_regions(X=X_combined_std,\n",
        "                      y=y_combined,\n",
        "                      classifier=ppn,\n",
        "                      test_idx=range(105, 150))\n",
        "plt.xlabel('Petal length [standardized]')\n",
        "plt.ylabel('Petal width [standardized]')\n",
        "plt.legend(loc='upper left')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "EeLs4wIWEXyS",
        "outputId": "03843afd-dbe7-4666-c8d4-aaea0e60fe87"
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Logistic Regression"
      ],
      "metadata": {
        "id": "Rs2CaDv3FbLV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def sigmoid(z):\n",
        "  return 1.0 / (1.0 + np.exp(-z))"
      ],
      "metadata": {
        "id": "oGIHpnM6Ehmb"
      },
      "execution_count": 39,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "z = np.arange(-7, 7, 0.1)\n",
        "sigma_z = sigmoid(z)"
      ],
      "metadata": {
        "id": "K-jJT1zWFZU3"
      },
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(z, sigma_z)\n",
        "plt.axvline(0.0, color='k')\n",
        "plt.ylim(-0.1, 1.1)\n",
        "plt.xlabel('z')\n",
        "plt.ylabel('$\\sigma (z)$')\n",
        "# y axis ticks and gridline\n",
        "plt.yticks([0.0, 0.5, 1.0])\n",
        "ax = plt.gca()\n",
        "ax.yaxis.grid(True)\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "w1tkwOLkFll-",
        "outputId": "6c287259-83de-48fc-ad82-98c6ef9e7863"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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mRwLwPSh2AIBTevbjndp6sESx4cH605X9ZLNxHVjAl1HsAAAntfFAkV5atluS9NiP+yo+MsTkRABOh2IHADhBTa1X9/x7ozxeQ5f1T9LFfTuaHQlAE1DsAAAn+MtnWdqWV6rY8GD94bLeZscB0EQUOwBAI1sPluj5T7IkSQ9e3kftI1wmJwLQVBQ7AECDWk/dIdhar6FxvRP0w34cggX8CcUOANBgzpd7tSmnWFEhQXpkQl/OggX8DMUOACBJyimq1NOLd0iqm4g4PoqzYAF/Q7EDAEiS/vDfzap0ezQkLUZXZaSYHQfAGaDYAQC0aHOeFm/JV5Ddpkd/fK7sdg7BAv6IYgcAAa68ulZ/+O9mSdLPL+iicxIiTU4E4ExR7AAgwD2zeIdyi6uUEhuqX/5fd7PjADgLFDsACGA78ks1Z/leSdJDP+qr0GCHuYEAnBWKHQAEKMMw9OD/NsvjNTS+T4LG9Ig3OxKAs0SxA4AA9dE3efoy67BcQXbdfymXDQOsgGIHAAGossajRz7YKkm6ZVRXpcSGmZwIQEug2AFAAJq9dJdyiiqV3C5Ut43qanYcAC2EYgcAAWb/kQrNXrpLUt0VJjhhArAOih0ABJg/frhN1bVeDevSXpf0TTQ7DoAWRLEDgACydt8RfbDpoGw26feX9ZbNxhUmACuh2AFAgDAMo+GEiaszUtSrY5TJiQC0NIodAASI9zce1PrsIoUFO3T3uHPMjgOgFVDsACAAVLk9+uOH2yRJt47qqvioEJMTAWgNFDsACABzl+9VTlGlEqNCNPX8LmbHAdBKKHYAYHFHymv0widZkqRfj+/B9CaAhVHsAMDiXvg0S6XVterdMUo/GZhsdhwArYhiBwAWduBohf65Yp8k6TeX9JTdzvQmgJVR7ADAwp5ZvFM1nrrJiC/oHmd2HACtjGIHABa1Pa9U/1l/QFLdaB2TEQPWR7EDAIt6YuE2GYZ0Sd9EDUhpZ3YcAG2AYgcAFrR67xF9vLVAdpt097geZscB0EYodgBgMYZh6ImPtkuSrh6com7xESYnAtBWKHYAYDGf7yzUqr1HFBxk1x1ju5sdB0AbotgBgIUYhqGnFu+QJE3M7KyO0aEmJwLQlih2AGAhn2wr0Nf7ixTitOu20V3NjgOgjVHsAMAiDMPQ0/WjdZOGpSk+MsTkRADaGsUOACxi4eY8bc4tUXiwQ7eMYrQOCEQUOwCwAK/X0DOLd0qSbhyZrtjwYJMTATADxQ4ALOCDTQe1Pb9UkSFBunlkF7PjADAJxQ4A/JzXa+i5JXWjdTeP7KLoMKfJiQCYhWIHAH7uo8152llQpsiQIE0ekWZ2HAAmotgBgB87frRuyoh0RYcyWgcEMoodAPixRVvytS2vVBGuIN3IaB0Q8Ch2AOCnDOPb0brJw9PULowzYYFAR7EDAD+1ZGuBthwsUViwQzeNTDc7DgAfQLEDAD9kGIae+6RutO6GYWmKYd46AKLYAYBf+nxnoTYeKFao06Gbz2e0DkAdih0A+KEXP9slSbp2aGfFRbhMTgPAV1DsAMDPrM8+qhW7DyvIbmO0DkAjFDsA8DPHRusmDExWUrtQk9MA8CUUOwDwI1kFpVq0JV82m3TrKK4JC6Axih0A+JHZS3dLksb1TlC3+EiT0wDwNRQ7APATOUWVend9jiTp1lFdTU4DwBdR7ADAT7zy+W7Veg0N69JeAzvHmB0HgA+i2AGAHzhSXqM3Vu2XJN02mtE6ACdHsQMAP/D35XtV6faob3KUzu8eZ3YcAD6KYgcAPq68ulZzl++VJN02qptsNpu5gQD4LIodAPi411dlq7jSrfS4cF3cN9HsOAB8GMUOAHxYTa1Xr3y+R5J0ywVd5LAzWgfg1Ch2AODD3t2Qo7ySKsVHuvTjQclmxwHg4yh2AOCjPF5Ds5fWXT7s5vPT5QpymJwIgK+j2AGAj1q8JV+7D5UrKiRIP8tMNTsOAD9AsQMAH/XK53WXD7t+WKoiXEEmpwHgDyh2AOCD1mcf1Zp9RxXssGvSsDSz4wDwExQ7APBBr3xRdybs5QOSFB8VYnIaAP6CYgcAPmb/kQp9uOmgJOmmkekmpwHgTyh2AOBj5ny5V15DOr97nHp1jDI7DgA/QrEDAB9SUuXW/NXZkhitA9B8FDsA8CFvrMpWeY1H3eMjNOqcDmbHAeBnKHYA4CPcHq/mfrlXUt2ExDYblw8D0DwUOwDwEQs2HVRucZXiIoL1owFcPgxA81HsAMAHGIahv9VPcXL9eWkKcXL5MADNR7EDAB+was8RbTxQLFeQXded19nsOAD8FMUOAHzAsQmJr8jopPYRLpPTAPBXFDsAMNmewnJ9vDVfknTjCKY4AXDmKHYAYLK/fbFbhiFd2DNe3eIjzI4DwI9R7ADAREfLa/TvtQckSTedz2gdgLNDsQMAE81bla0qt1d9kqI0rEt7s+MA8HMUOwAwidvj1d+X75VUd/kwJiQGcLYodgBgkgWbDqqgtFodIl36Yb8ks+MAsACKHQCYZE795cOuy0xVcBC7YwBnjz0JAJhgffZRbdhfpGCHXT/LZEJiAC2DYgcAJjg2WndZ/yR1iGRCYgAtg2IHAG0sr7hKCzYdlCRNGZFmbhgAlkKxA4A29q+V+1TrNTQ0LVZ9k6PNjgPAQih2ANCGqtwezVuZLUmazGgdgBZGsQOANvTfr3N1uLxGye1CNa53gtlxAFgMxQ4A2ohhGA0nTVw/LFVBDnbBAFoWexUAaCMr9xzR1oMlCnHa9dMhKWbHAWBBFDsAaCNzvtwjSfrJoE5qFxZschoAVkSxA4A2sP9IhRZvyZckTRmeZm4YAJYVdDZvdrvdysvLU0VFhTp06KDY2NiWygUAlvLPr/bJa0jnd49T94RIs+MAsKhmj9iVlpbqxRdf1KhRoxQVFaW0tDT16tVLHTp0UGpqqqZOnarVq1e3RlYA8EsVNbV6Y1X9FCeM1gFoRc0qdk8//bTS0tI0Z84cjR07Vu+++642bNigHTt2aMWKFXrggQdUW1urcePG6eKLL9bOnTtbKzcA+I231+WopKpWae3DNKZHvNlxAFhYsw7Frl69WsuWLVOfPn1O+vrQoUN14403avbs2ZozZ44+//xzde/evUWCAoA/8noNza0/aWLS8DTZ7TaTEwGwsmYVu9dff73h8XPPPacrr7xSSUlJJ6zncrl06623nn06APBzn2cVatehckW4gnRlRiez4wCwuDM+K/bOO+/U+eefr/379zdaXlNTo7Vr1551MACwgmNTnFw1uJMiQ5wmpwFgdWc13cnYsWM1atSoRuXu6NGjGjp06FkHAwB/t+dQmT7bfkg2mzRpWJrZcQAEgDOe7sRms+nhhx9WfHy8Ro0apaVLlyolpW4mdcMwWiwgAPirf63cJ0n6vx7xSosLNzkNgEBw1hMUP/zww7ruuusajdzZbGf25eAXXnhBaWlpCgkJUWZmplatWnXKdefOnSubzdboFhISckZ/LgC0hnfX50qSpoxINzkJgEBxxiN2x4/KPfTQQ7LZbBo1apTeeOONM/q8+fPna/r06Zo9e7YyMzM1a9YsjR8/Xtu3b1d8/MmnB4iKitL27dsbnp9poQSA1lBe41HPlBiN6Nbe7CgAAsQZF7tHH31U4eHfHlp48MEHJUmXXXbZGX3e008/ralTp2rKlCmSpNmzZ+uDDz7Qq6++qnvvvfek77HZbEpMTDyjPw8A2sLk4en8pxNAmznjYjdjxowTlj344INyOp168sknm/VZx86kPf4z7Xa7xo4dqxUrVpzyfWVlZUpNTZXX69WgQYP02GOPnXKOverqalVXVzc8LykpkVR3WTS3292svABwKsfvT6JDnfph33j2MQDOSnP2IWd1rdiTuf/++3X//fc36z2FhYXyeDxKSEhotDwhIUHbtm076Xt69OihV199Vf369VNxcbGefPJJDR8+XJs3b1anTifOFTVz5syGUcXjLVq0SGFhYc3KCwCnUlVV1fB4YLtqffrxQhPTALCCioqKJq9rM5pxCmt2drY6d+7c5A/PyclRcnLyadfLzc1VcnKyli9frmHDhjUsv+eee7R06VKtXLnytJ/hdrvVq1cvXXvttXr44YdPeP1kI3YpKSkqLCxUVFRUE38iAPh+63fnKbNn3X5yy55cdUuOMzkRAH9XUlKiuLg4FRcXn7azNGvEbsiQIZowYYJuvvlmDRky5KTrFBcX680339Szzz6rn//85/rVr3512s+Ni4uTw+FQfn5+o+X5+flN/g6d0+nUwIEDlZWVddLXXS6XXC7XSd/ndDJpKICW8caanIbHnTtEsX8BcNaasx9pVrHbsmWLHn30UV100UUKCQlRRkaGkpKSFBISoqNHj2rLli3avHmzBg0apMcff1w/+MEPmvS5wcHBysjI0JIlSzRhwgRJktfr1ZIlS3T77bc36TM8Ho82bdrU5D8TAFrakfIa/e/rg2bHABDAmlXs2rdvr6efflqPPvqo/v3vf2vt2rXat2+fKisrFRcXp4kTJ2r8+PHq27dvs4NMnz5dkyZN0uDBgzV06FDNmjVL5eXlDWfJ3nDDDUpOTtbMmTMl1U2xct5556lbt24qKirSE088oX379unmm29u9p8NAC3h9VXZqq71mh0DQAA7o5MnQkNDNXnyZM2fP1+zZs1qkSDXXHONDh06pN///vfKy8vTgAED9NFHHzWcUJGdnS27/dv5lI8ePaqpU6cqLy9PMTExysjI0PLly9W7d+8WyQMAzeH2ePXPFfvMjgEgwDXr5InjHZuOpLy8XDabTYMHD9bEiRNP+d07X1NSUqLo6OgmfRERAE7n/Y25un3eesUEe7Xh4csl1U3JdPx8nwBwJprTWc7qkmLr16/XoEGDNHLkSG3evFnnn3++fv3rX5/NRwKAX5rz5V5J0jWDU8wNAiCgndU8dvPmzdNFF13U8Hzjxo360Y9+pOTkZN11111nHQ4A/MHGA0Vau++onA6brhmaohOnbweAtnHGI3axsbFKSWn8P9N+/frp+eef14svvnjWwQDAXxwbrfthvyTFR4aYGwZAQDvjYjdgwADNmTPnhOXdunVTdnb2WYUCAH9RUFKl9zfmSpKmjEgzNwyAgHfGh2IfeeQRjRkzRrm5ufrFL36hfv36qby8XI899pjS09NbMiMA+KzXVmbL7TGUkRqjfp3aqby83OxIAALYGRe78847T1999ZXuuOMOnX/++Tp2cm1ISIjeeuutFgsIAL6qutajeSvrpjhhtA6ALzirkyf69++vzz77TAUFBVq7dq28Xq8yMzMVF8e1EQFY3/tfH1RhWY0So0I0vk/TLn8IAK3prIrdMfHx8brkkkta4qMAwC8YhqE5y/dIkq4fliqn46xmjwKAFsGeCADOwJp9R/VNTolcQXb9bGhns+MAgCSKHQCckTlf1o3W/XhgsmLCg01OAwB1KHYA0Ew5RZVauDlfkjSZkyYA+BCKHQA00z9X7JPHa2h41/bqmci1pgH4DoodADRDZY1Hr6+qm4R98vA0c8MAwHdQ7ACgGd5Zn6PiSrdSYkN1Ya8Es+MAQCMUOwBoIsMwNLd+ipNJw9LksNtMTgQAjVHsAKCJvsw6rB35ZQoPdujqISlmxwGAE1DsAKCJjk1xcmVGJ0WFOE1OAwAnotgBQBPsLSzXJ9sLJEmTOGkCgI+i2AFAE8xdvleGIY3u0UFdOkSYHQcATopiBwCnUVzh1ptr9kuSbhqZbnIaADg1ih0AnMbrq7NVUeNRz8RIjewWZ3YcADglih0AfI+aWq/mfrlXUt1onc3GFCcAfBfFDgC+x4JNB5VXUqUOkS5dPiDJ7DgA8L0odgBwCoZh6K+f75YkTRqWKleQw+REAPD9KHYAcApf7T6izbklCnHaNTEz1ew4AHBaFDsAOIVX6kfrrszopJjwYJPTAMDpUewA4CR2HSrTkm0Fstmkm0Z2MTsOADQJxQ4ATuJvX9RdPmxsrwSlx4WbnAYAmoZiBwDfcaS8Rm+vPSBJupkJiQH4EYodAHzHa1/tU3WtV/06RWtoeqzZcQCgySh2AHCcKrdH/1ixVxITEgPwPxQ7ADjOfzfkqrCsRknRIfrBuR3NjgMAzUKxA4B6hmHolS/qpjiZPCJNTge7SAD+hb0WANRbtrNQO/LLFB7s0E+HdjY7DgA0G8UOAOodm5D4miGdFRXiNDkNADQfxQ4AJG06UKzPdxbKYbdpyog0s+MAwBmh2AGApNlLd0mSftQ/SSmxYSanAYAzQ7EDEPD2FJZrwTcHJUm3jOpqchoAOHMUOwAB76Wlu2QY0the8eqRGGl2HAA4YxQ7AAEtr7hKb6+ru3zYbaMZrQPg3yh2AALaq1/ukdtjaGh6rDJSuXwYAP9GsQMQsIor3PrXV/skMVoHwBoodgAC1j9W7FV5jUc9EyM1+pwOZscBgLNGsQMQkCprPJqzfK+kutE6m81mbiAAaAEUOwAB6c01+3WkvEadY8N06bkdzY4DAC2CYgcg4Lg9Xr28rO7yYT+/oIuCHOwKAVgDezMAAed/X+cqp6hScREuXZnRyew4ANBiKHYAAorXazRcPuymkekKcTpMTgQALYdiByCgLNlWoB35ZYp0BWnieZ3NjgMALYpiByBgGIahFz/LkiRdNyxVUSFOkxMBQMui2AEIGCt2Hda67CIFB9k1ZUSa2XEAoMVR7AAEjGeX7JQk/WxoZ8VHhpicBgBaHsUOQED4avdhrdxzRMEOu24Z1cXsOADQKih2AALCc/WjdVcP6aSO0aEmpwGA1kGxA2B5q/ce0fJdh+V02HTb6G5mxwGAVkOxA2B5x0brrszopOR2jNYBsC6KHQBLW7vvqD7fWaggu02/YLQOgMVR7ABY2rEzYX8yKFkpsWEmpwGA1kWxA2BZa/Ye0bIdh+Sw2zRtDKN1AKyPYgfAsp5atEOSdFVGJ6W2Dzc5DQC0PoodAEtavqtQK3bXnQl7+/8xWgcgMFDsAFiOYRh6un607qdDOqtTDN+tAxAYKHYALGfZzkKt2XdUwUF2vlsHIKBQ7ABYSt1o3XZJ0nWZqUqM5pqwAAIHxQ6ApXy8tUBfHyhWqNOh20Z3NTsOALQpih0Ay/B4DT2xcJskadLwNHWIdJmcCADaFsUOgGW8sz5HO/LLFBUSpNtGMVoHIPBQ7ABYQpXbo2cW150J+4sx3RQd5jQ5EQC0PYodAEt47at9yimqVGJUiCYPTzM7DgCYgmIHwO+VVLn1wqdZkqQ7x3ZXiNNhciIAMAfFDoDfe2XZbh2tcKtrh3BdmdHJ7DgAYBqKHQC/ll9SpVe+2CNJ+n/jeyjIwW4NQOBiDwjArz21aLsqajwa2LmdxvdJNDsOAJiKYgfAb23JLdFbaw9Iku6/tLdsNpvJiQDAXBQ7AH7JMAw9tmCrDEO6tF9HZaTGmB0JAExHsQPglz7bfkhfZBUq2GHXvRf3NDsOAPgEih0Av1Pr8erRBVslSZNHpCklNszkRADgGyh2APzO66v3K6ugTDFhTk0b083sOADgMyh2APxKUUWNnl60XZJ0x4XdFR3KpcMA4BiKHQC/8vTiHTpa4dY5CRGaeF6q2XEAwKdQ7AD4jS25JXrtq32SpD9c3kdOJiMGgEbYKwLwC4Zh6A//2yyvIV16bkcN7xpndiQA8DkUOwB+4X8bD2rVniMKcdp136W9zI4DAD6JYgfA51XU1OqxD+qmN/nF6G5KbhdqciIA8E0UOwA+b9bHO5VXUqWU2FD9/IIuZscBAJ9FsQPg07bkluhvX+yRJD14eR+FOB0mJwIA30WxA+CzvF5Dv313kzxeQ5f0TdT/9UwwOxIA+DSKHQCf9frqbK3PLlKEK0gPXNbH7DgA4PModgB80qHSav3pw22SpLvHnaPE6BCTEwGA76PYAfBJj3ywRSVVteqbHKUbhqWZHQcA/ALFDoDPWbI1X+9tyJXdJj3243PlsNvMjgQAfoFiB8CnFFe6dd87myRJN5/fRf06tTM3EAD4EYodAJ/y2AdblV9SrfS4cE2/6Byz4wCAX6HYAfAZn+88pPlr9kuS/nRFP+asA4BmotgB8All1bW69+26Q7CThqVqaHqsyYkAwP9Q7AD4hMcWbFVOUaU6xYTqnot7mh0HAPwSxQ6A6T7Zlq95K7MlSY9f0U/hriCTEwGAf6LYATDV4bJq3fPvukOwN41M1/BucSYnAgD/RbEDYBrDMHTvfzapsKxa5yRE6P+N72F2JADwaxQ7AKZ5c81+Ld6SL6fDplnXDOQsWAA4SxQ7AKbYU1iuh/63RZJ097ge6p0UZXIiAPB/FDsAba7K7dG0f61TeY1Hmemxmnp+F7MjAYAlUOwAtLmZC7Zqy8ESxYYH69mfDuRasADQQih2ANrUh5sO6u8r9kmSnrq6vxKjQ0xOBADWQbED0Gb2H6nQPW9vlCTdMqqLxvSINzkRAFgLxQ5Am6hyezRt3jqVVtVqUOd2+vU4pjYBgJZGsQPQ6gzD0O/e/UYbDxSrXZhTz107UE4Hux8AaGnsWQG0utdWZuuttQdkt0nPXztInWLCzI4EAJZEsQPQqtbuO6KH/rdZknTPxT01sjuXDAOA1kKxA9Bq8kuqdOtr6+T2GLr03I665QLmqwOA1kSxA9AqKms8mvqPNTpUWncd2Mev7CebjfnqAKA1UewAtDiv19Bd8zdo44FixYQ59dcbBivcFWR2LACwPIodgBb3+MLt+mhznoIddr18w2Cltg83OxIABASKHYAWNX91tmYv3SVJevzKfhqSFmtyIgAIHBQ7AC3m0+0F+u0730iS7riwuyYMTDY5EQAEFoodgBaxdt9R3fbaWtV6Df14YLLuHNvd7EgAEHAodgDO2o78Ut04d7Wq3F6N7tGBM2ABwCQUOwBn5cDRCt3wt1UqrnRrYOd2+svEQVwuDABMwt4XwBnLK67SxFdWKq+kSt3jIzRn8hCFBTOtCQCYhWIH4IwUlFTp2r9+pX2HK9QpJlT/uGmo2oUFmx0LAAIaxQ5AsxWU1pW6PYXlSm4XqtennqeO0aFmxwKAgEexA9Ash0qrNfGvK7XrULmSokP0+tTzlBIbZnYsAIAkvgwDoMlyiip13SsrtaewXIlRIZo39Tx1bk+pAwBfQbED0CS7D5XpuldWKre4SsntQvXazZlKi+NSYQDgSyh2AE5rS26Jbnh1pQrLatSlQ7heuylTSe34Th0A+BqKHYDvtTyrULe8tlalVbXq3TFK/7hpqOIiXGbHAgCcBMUOwCm9vfaA7v3PRrk9hoakxeiVSUMUHeo0OxYA4BQodgBOYBiGnluSpWc+3iFJurRfRz11VX+FOB0mJwMAfB+KHYBGqtwezfjPJr2zPkeSdMuoLvrN+J6y27n2KwD4OoodgAY5RZW65Z9r9E1OiRx2mx68vI+uOy/V7FgAgCai2AGQJH21+7Cm/WudDpfXKCbMqRd+NkjDu8WZHQsA0AwUOyDAeb2GXv58t55cuF21XkO9O0bppeszuJoEAPghih0QwA6XVWv6m19r6Y5DkqTL+yfpT1f0U2gwJ0kAgD+i2AEBasWuw7rjjfUqKK2WK8iuBy7ro2uHpshm4yQJAPBXFDsgwFS5PXpi4Xa9+uUeGYbUtUO4Xpg4SD0To8yOBgA4SxQ7IIB8vb9I09/coF2HyiVJPx2Sot9f1lthwewKAMAK2JsDAaCyxqNnl+zUXz/fLY/XUHykS3+6op/G9Iw3OxoAoAVR7ACL+3R7gX737jc6cLRSUt0JEg/9qI/ahQWbnAwA0NIodoBF5RZV6tEFW/XBxoOSpKToED30o74a2zvB5GQAgNZCsQMsprLGo5eW7dLspbtU5fbKbpOmjEjX9IvOUbiLX3kAsDL28oBFeLyG/vt1jp74aLtyi6skSUPSYvTAZX3UNzna5HQAgLZAsQP8nGEY+nhrgZ5cuF3b80slScntQjXjBz116bkdmZcOAAIIxQ7wU4ZhaNnOQj378Q6tyy6SJEWGBOnWUV1108h0hTi5egQABBqKHeBnvF5Di7fm64VPs7TxQLEkKcRp15QR6brlgi6c7QoAAYxiB/iJKrdH723I0d++2KMd+WWS6grdtUM767ZRXRUfFWJyQgCA2Sh2gI8rKKnSa1/t079WZutweY0kKdIVpOuHperGkemKi3CZnBAA4CsodoAP8noNfZ5VqHkr9+njrQXyeA1JdSdFTB6epquHpCg61GlySgCAr6HYAT4k+3CF/rP+gN5ed0D7j1Q2LB+cGqMpI9I1vk+Cghx2ExMCAHwZxQ4w2aHSai3akqd31+do9d6jDcsjQ4J0xaBOunZoZ/VIjDQxIQDAX1DsABPsP1KhhZvztGhzvlbvOyKj7kir7DZpRLc4/WRQsi7u01GhwUxZAgBoOood0AYMw1BWQZkWbs7TR5vz9E1OSaPX+3eK1g/O7agfDUhWYjRntwIAzgzFDmglBSVV+nJXob7YeVhfZhUqr6Sq4TW7TRqaHquL+yRqXJ9EJbULNTEpAMAqKHZACymqqNHafUf1RVahvswqbJhr7pjgILtGdG2vi/smamyvBLVnmhIAQAuj2AFnoNbj1Y78Mq3ff1Tr9hVp/f6j2n2ovNE6NpvUNylaI7rFaWS3OA1Oi+EyXwCAVkWxA06jptarXYfKtC2vRNsOlurrA0XaeKBYFTWeE9ZNax+m4fVFbliX9ooJ5/JeAIC2Q7ED6nm8hnKLKrXrUJl25Jdq68FSbT1Yol2HyuT2GCesH+EK0oCUdhrYue42ICVGsRQ5AICJKHYIKF6voYLSah04WqHdheXaU1iu3YfKtKewXHsPV6im1nvS90W6gtSrY5R6doxU745RGpQao64dIuSw29r4JwAA4NQodrAMwzBUUlmrQ2VVKiipVl5JlQ4crVTO0UodKKpQztFK5RZVqcZz8vImScEOuzq3D9M5CRHqlRilnh2j1KtjpJLbhcpmo8QBAHybTxW7F154QU888YTy8vLUv39//fnPf9bQoUNPuf5bb72l3/3ud9q7d6+6d++uP/3pT/rBD37QhonR2jxeQ6VVbh2tcKuookZHK2pUUFKtgtJqHSqtVkFp1XGPq0854nY8h92mjtEhSo8Lb3Tr2iFCSe1CGYUDAPgtnyl28+fP1/Tp0zV79mxlZmZq1qxZGj9+vLZv3674+PgT1l++fLmuvfZazZw5Uz/84Q81b948TZgwQevWrVPfvn1N+AnwXYZhqLrWq/LqWpVXe1RWXavymlqVVdXWPa6uuy+rrlVRfXErqnQ3elxc6W64KkNTRYUEKT4qRPGRLnWKCVWnmDAltwutexwbpoRIF9dbBQBYks0wmvvPZuvIzMzUkCFD9Pzzz0uSvF6vUlJS9Mtf/lL33nvvCetfc801Ki8v1/vvv9+w7LzzztOAAQM0e/bs0/55JSUlio6OVnFxsaKiolruB/FBhmHI7THk9nhV6zFU4/Gq1uuVu/bEx26PV1Vuj6rcXlXXelTt9qqq1tOwrMrtUXXtt+tU1a9TXetpVOCOFbdab8v89QoPdqhdWLDahTkVH+lSfGSIOkS6FB/lUnykSx0iQ+rvXUwpAlOVl5crIiJCklRWVqbw8HCTEwHwd83pLD4xYldTU6O1a9dqxowZDcvsdrvGjh2rFStWnPQ9K1as0PTp0xstGz9+vN59993WjNosK3cf1tIdh+QxDHm9hjxeyeP1ymPUPfZ6jYbXao977PEa8hp197XHPfZ6Vf/eb2/e457X1Bc3t8fb6HFLlauzEep0KNwVpAhX3X3d42/v24U5FRPmVLvQuvLWLixYMWFORdcvCw5ihA0AgNPxiWJXWFgoj8ejhISERssTEhK0bdu2k74nLy/vpOvn5eWddP3q6mpVV1c3PC8pqbtWp9vtltvtPpv4p7Rm72H95bNdrfLZZ8vpsMnpsMvpsCnIbj/uuV0hTrtcQXaFOB0N9yFBdrmcjm9fC3LI5Wz8WpjTofBjxS342yIXFhx0dt9bMzxyu0+cMw7wRcfvT1pz/wIgcDRnP+ITxa4tzJw5Uw8++OAJyxctWqSwsLBW+TMrim0alWiTzVZ3bVC76u9tkt1myHbcc1uj1+rW/e77bN/9jOPXsRkKskkOm+Sw192f6vmxzzpjtfW3qsaL3ZKK6m9AoKqq+vYXY+HChQoJCTExDQArqKioaPK6PlHs4uLi5HA4lJ+f32h5fn6+EhMTT/qexMTEZq0/Y8aMRoduS0pKlJKSonHjxrXad+w4PxcIPOXl315abvz48XzHDsBZO3aUsSl8otgFBwcrIyNDS5Ys0YQJEyTVnTyxZMkS3X777Sd9z7Bhw7RkyRLdeeedDcsWL16sYcOGnXR9l8sll+vEi647nU45nc6z/hkAQFKj/Qn7FwAtoTn7EZ8odpI0ffp0TZo0SYMHD9bQoUM1a9YslZeXa8qUKZKkG264QcnJyZo5c6Yk6Y477tCoUaP01FNP6dJLL9Ubb7yhNWvW6OWXXzbzxwAAADCNzxS7a665RocOHdLvf/975eXlacCAAfroo48aTpDIzs6W3f7tmZHDhw/XvHnzdP/99+u+++5T9+7d9e677zKHHQAACFg+M49dWwukeewAtB3msQPQ0prTWZgcDAAAwCIodgAAABZBsQMAALAIih0AAIBFUOwAAAAsgmIHAABgERQ7AAAAi6DYAQAAWATFDgAAwCIodgAAABZBsQMAALAIih0AAIBFUOwAAAAsgmIHAABgERQ7AAAAi6DYAQAAWATFDgAAwCIodgAAABZBsQMAALAIih0AAIBFUOwAAAAsgmIHAABgERQ7AAAAi6DYAQAAWATFDgAAwCIodgAAABZBsQMAALCIILMDmMUwDElSSUmJyUkAWEl5eXnD45KSEnk8HhPTALCCY13lWHf5PgFb7EpLSyVJKSkpJicBYFVJSUlmRwBgIaWlpYqOjv7edWxGU+qfBXm9XuXm5ioyMlI2m83sOG2mpKREKSkp2r9/v6KiosyO45PYRqfHNvp+bJ/TYxudHtvo9AJlGxmGodLSUiUlJclu//5v0QXsiJ3dblenTp3MjmGaqKgoS/8StAS20emxjb4f2+f02EanxzY6vUDYRqcbqTuGkycAAAAsgmIHAABgERS7AONyufTAAw/I5XKZHcVnsY1Oj230/dg+p8c2Oj220emxjU4UsCdPAAAAWA0jdgAAABZBsQMAALAIih0AAIBFUOwC3AcffKDMzEyFhoYqJiZGEyZMMDuST6qurtaAAQNks9m0YcMGs+P4jL179+qmm25Senq6QkND1bVrVz3wwAOqqakxO5qpXnjhBaWlpSkkJESZmZlatWqV2ZF8xsyZMzVkyBBFRkYqPj5eEyZM0Pbt282O5bP++Mc/ymaz6c477zQ7ik/JycnRddddp/bt2ys0NFTnnnuu1qxZY3Ysn0CxC2Bvv/22rr/+ek2ZMkVff/21vvzyS/3sZz8zO5ZPuueee7g81Els27ZNXq9XL730kjZv3qxnnnlGs2fP1n333Wd2NNPMnz9f06dP1wMPPKB169apf//+Gj9+vAoKCsyO5hOWLl2qadOm6auvvtLixYvldrs1bty4RtfYRZ3Vq1frpZdeUr9+/cyO4lOOHj2qESNGyOl06sMPP9SWLVv01FNPKSYmxuxovsFAQHK73UZycrLxyiuvmB3F5y1YsMDo2bOnsXnzZkOSsX79erMj+bTHH3/cSE9PNzuGaYYOHWpMmzat4bnH4zGSkpKMmTNnmpjKdxUUFBiSjKVLl5odxaeUlpYa3bt3NxYvXmyMGjXKuOOOO8yO5DN+85vfGCNHjjQ7hs9ixC5ArVu3Tjk5ObLb7Ro4cKA6duyoSy65RN98843Z0XxKfn6+pk6dqn/+858KCwszO45fKC4uVmxsrNkxTFFTU6O1a9dq7NixDcvsdrvGjh2rFStWmJjMdxUXF0tSwP6dOZVp06bp0ksvbfR3CXX++9//avDgwbrqqqsUHx+vgQMH6q9//avZsXwGxS5A7d69W5L0hz/8Qffff7/ef/99xcTEaPTo0Tpy5IjJ6XyDYRiaPHmybr31Vg0ePNjsOH4hKytLf/7zn3XLLbeYHcUUhYWF8ng8SkhIaLQ8ISFBeXl5JqXyXV6vV3feeadGjBihvn37mh3HZ7zxxhtat26dZs6caXYUn7R79269+OKL6t69uxYuXKjbbrtNv/rVr/T3v//d7Gg+gWJnMffee69sNtv33o59L0qSfvvb3+qKK65QRkaG5syZI5vNprfeesvkn6J1NXUb/fnPf1ZpaalmzJhhduQ219RtdLycnBxdfPHFuuqqqzR16lSTksOfTJs2Td98843eeOMNs6P4jP379+uOO+7Qv/71L4WEhJgdxyd5vV4NGjRIjz32mAYOHKif//znmjp1qmbPnm12NJ8QZHYAtKy7775bkydP/t51unTpooMHD0qSevfu3bDc5XKpS5cuys7Obs2IpmvqNvrkk0+0YsWKEy5VM3jwYE2cONHS/zts6jY6Jjc3V2PGjNHw4cP18ssvt3I63xUXFyeHw6H8/PxGy/Pz85WYmGhSKt90++236/3339eyZcvUqVMns+P4jLVr16qgoECDBg1qWObxeLRs2TI9//zzqq6ulsPhMDGh+Tp27Njo3y5J6tWrl95++22TEvkWip3FdOjQQR06dDjtehkZGXK5XNq+fbtGjhwpSXK73dq7d69SU1NbO6apmrqNnnvuOT3yyCMNz3NzczV+/HjNnz9fmZmZrRnRdE3dRlLdSN2YMWMaRn3t9sA9EBAcHKyMjAwtWbKkYeogr9erJUuW6Pbbbzc3nI8wDEO//OUv9c477+izzz5Tenq62ZF8yoUXXqhNmzY1WjZlyhT17NlTv/nNbwK+1EnSiBEjTpgiZ8eOHZb/t6upKHYBKioqSrfeeqseeOABpaSkKDU1VU888YQk6aqrrjI5nW/o3Llzo+cRERGSpK5duzLCUC8nJ0ejR49WamqqnnzySR06dKjhtUAdoZo+fbomTZqkwYMHa+jQoZo1a5bKy8s1ZcoUs6P5hGnTpmnevHl67733FBkZ2fDdw+joaIWGhpqcznyRkZEnfN8wPDxc7du353uI9e666y4NHz5cjz32mK6++mqtWrVKL7/8ckAfLTgexS6APfHEEwoKCtL111+vyspKZWZm6pNPPmEuIDTZ4sWLlZWVpaysrBPKrmEYJqUy1zXXXKNDhw7p97//vfLy8jRgwAB99NFHJ5xQEahefPFFSdLo0aMbLZ8zZ85pD/8DkjRkyBC98847mjFjhh566CGlp6dr1qxZmjhxotnRfILNCNS9LwAAgMUE7pdhAAAALIZiBwAAYBEUOwAAAIug2AEAAFgExQ4AAMAiKHYAAAAWQbEDAACwCIodAACARVDsAAAALIJiBwAAYBEUOwAAAIug2AFAC9i7d69sNtsJt+9e7B4AWlOQ2QEAwApSUlJ08ODBhud5eXkaO3asLrjgAhNTAQg0NsMwDLNDAICVVFVVafTo0erQoYPee+892e0cHAHQNhixA4AWduONN6q0tFSLFy+m1AFoUxQ7AGhBjzzyiBYuXKhVq1YpMjLS7DgAAgyHYgGghbz99tu69tpr9eGHH+rCCy80Ow6AAESxA4AW8M033ygzM1PTp0/XtGnTGpYHBwcrNjbWxGQAAgnFDgBawNy5czVlypQTlo8aNUqfffZZ2wcCEJAodgAAABbB6VoAAAAWQbEDAACwCIodAACARVDsAAAALIJiBwAAYBEUOwAAAIug2AEAAFgExQ4AAMAiKHYAAAAWQbEDAACwCIodAACARVDsAAAALOL/A+L706Tm0xRVAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def loss_1(z):\n",
        "  return - np.log(sigmoid(z))\n",
        "\n",
        "def loss_0(z):\n",
        "  return - np.log(1 - sigmoid(z))"
      ],
      "metadata": {
        "id": "41OMA1ydFxhW"
      },
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "z = np.arange(-10, 10, 0.1)\n",
        "sigma_z = sigmoid(z)\n",
        "c1 = [loss_1(x) for x in z]\n",
        "c0 = [loss_0(x) for x in z]"
      ],
      "metadata": {
        "id": "6tWc5SJHGc5z"
      },
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(sigma_z, c1, label='L(w, b) if y=1')\n",
        "plt.plot(sigma_z, c0, linestyle='--', label='L(w, b) if y=0')\n",
        "plt.ylim(0.0, 5.1)\n",
        "plt.xlim([0, 1])\n",
        "plt.xlabel('$\\sigma(z)$')\n",
        "plt.ylabel('L(w, b)')\n",
        "plt.legend(loc='best')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "DC-CcC3UGn6R",
        "outputId": "85901e17-2c15-4586-8468-a4d6bb6afa82"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "class LogisticRegressionGD:\n",
        "\n",
        "    \"\"\"Gradient descent-based logistic regression classifier.\n",
        "\n",
        "    Parameters\n",
        "    ------------\n",
        "\n",
        "    eta : float\n",
        "      Learning rate (between 0.0 and 1.0)\n",
        "    n_iter : int\n",
        "      Passes over the training dataset.\n",
        "    random_state : int\n",
        "      Random number generator seed for random weight\n",
        "      initialization.\n",
        "\n",
        "    Attributes\n",
        "    -----------\n",
        "\n",
        "    w_ : 1d-array\n",
        "      Weights after training.\n",
        "    b_ : Scalar\n",
        "      Bias unit after fitting.\n",
        "    losses_ : list\n",
        "      Mean squared error loss function values in each epoch.\n",
        "\n",
        "    \"\"\"\n",
        "\n",
        "    def __init__(self, eta=0.01, n_iter=50, random_state=1):\n",
        "        self.eta = eta\n",
        "        self.n_iter = n_iter\n",
        "        self.random_state = random_state\n",
        "\n",
        "    def fit(self, X, y):\n",
        "        \"\"\" Fit training data.\n",
        "\n",
        "        Parameters\n",
        "        ----------\n",
        "        X : {array-like}, shape = [n_examples, n_features]\n",
        "          Training vectors, where n_examples is the\n",
        "          number of examples and n_features is the\n",
        "          number of features.\n",
        "\n",
        "        y : array-like, shape = [n_examples]\n",
        "          Target values.\n",
        "\n",
        "        Returns\n",
        "        -------\n",
        "        self : Instance of LogisticRegressionGD\n",
        "        \"\"\"\n",
        "\n",
        "        rgen = np.random.RandomState(self.random_state)\n",
        "        self.w_ = rgen.normal(loc=0.0, scale=0.01, size=X.shape[1])\n",
        "        self.b_ = np.float_(0.)\n",
        "\n",
        "        self.losses_ = []\n",
        "\n",
        "        for i in range(self.n_iter):\n",
        "            net_input = self.net_input(X)\n",
        "            output = self.activation(net_input)\n",
        "            errors = (y - output)\n",
        "            self.w_ += self.eta * 2.0 * X.T.dot(errors) / X.shape[0]\n",
        "            self.b_ += self.eta * 2.0 * errors.mean()\n",
        "            loss = (-y.dot(np.log(output))\n",
        "                   - ((1 - y).dot(np.log(1 - output)))\n",
        "                    / X.shape[0])\n",
        "            self.losses_.append(loss)\n",
        "\n",
        "        return self\n",
        "\n",
        "    def net_input(self, X):\n",
        "        \"\"\"Calculate net input\"\"\"\n",
        "        return np.dot(X, self.w_) + self.b_\n",
        "\n",
        "    def activation(self, z):\n",
        "        \"\"\"Compute logistic sigmoid activation\"\"\"\n",
        "        return 1. / (1. + np.exp(-np.clip(z, -250, 250)))\n",
        "\n",
        "    def predict(self, X):\n",
        "        \"\"\"Return class label after unit step\"\"\"\n",
        "        return np.where(self.activation(self.net_input(X)) >= 0.5, 1, 0)"
      ],
      "metadata": {
        "id": "wIMljN3yGxk6"
      },
      "execution_count": 45,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train_01_subset = X_train_std[(y_train == 0) | (y_train == 1)]\n",
        "y_train_01_subset = y_train[(y_train == 0) | (y_train == 1)]"
      ],
      "metadata": {
        "id": "tvtgRkBRHwbJ"
      },
      "execution_count": 46,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "lrgd = LogisticRegressionGD(eta=0.3, n_iter=1000, random_state=1)"
      ],
      "metadata": {
        "id": "2ww70zPWIlNr"
      },
      "execution_count": 47,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "lrgd.fit(X_train_01_subset, y_train_01_subset)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "taT7WeJdItyF",
        "outputId": "bb4d108a-3c30-452e-a525-86c05155b35d"
      },
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<__main__.LogisticRegressionGD at 0x7c60c5983460>"
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plot_decision_regions(X=X_train_01_subset,\n",
        "                      y=y_train_01_subset,\n",
        "                      classifier=lrgd)\n",
        "plt.xlabel('Petal length [standardized]')\n",
        "plt.ylabel('Petal width [standardized]')\n",
        "plt.legend(loc='upper left')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "o8aHKfeQIyCW",
        "outputId": "7b603203-ddae-4868-a4c3-f832a96a749b"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.linear_model import LogisticRegression"
      ],
      "metadata": {
        "id": "VLNldQmiI9vk"
      },
      "execution_count": 50,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "lr = LogisticRegression(C=100.0, solver='lbfgs',\n",
        "                        multi_class='ovr')"
      ],
      "metadata": {
        "id": "lhrmyiyUJJce"
      },
      "execution_count": 51,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "lr.fit(X_train_std, y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 75
        },
        "id": "wU5qw1g9JOoa",
        "outputId": "07d3db96-aaaa-468c-e51b-db373bf7f7fd"
      },
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "LogisticRegression(C=100.0, multi_class='ovr')"
            ],
            "text/html": [
              "<style>#sk-container-id-3 {color: black;background-color: white;}#sk-container-id-3 pre{padding: 0;}#sk-container-id-3 div.sk-toggleable {background-color: white;}#sk-container-id-3 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-3 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-3 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-3 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-3 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-3 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-3 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-3 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-3 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-3 div.sk-item {position: relative;z-index: 1;}#sk-container-id-3 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-3 div.sk-item::before, #sk-container-id-3 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-3 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-3 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-3 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-3 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-3 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-3 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-3 div.sk-label-container {text-align: center;}#sk-container-id-3 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-3 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression(C=100.0, multi_class=&#x27;ovr&#x27;)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" checked><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LogisticRegression</label><div class=\"sk-toggleable__content\"><pre>LogisticRegression(C=100.0, multi_class=&#x27;ovr&#x27;)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plot_decision_regions(X_combined_std,\n",
        "                      y_combined,\n",
        "                      classifier=lr,\n",
        "                      test_idx=range(105, 150))\n",
        "plt.xlabel('Petal length [standardized]')\n",
        "plt.ylabel('Petal width [standardized]')\n",
        "plt.legend(loc='upper left')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "1D05YVXHJQpC",
        "outputId": "9897b7d0-a087-4d54-da7c-b499ac5b801f"
      },
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.tree import DecisionTreeClassifier"
      ],
      "metadata": {
        "id": "vD-dusIpJbiA"
      },
      "execution_count": 54,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "tree_model = DecisionTreeClassifier(criterion='gini',\n",
        "                                    max_depth=4,\n",
        "                                    random_state=1)"
      ],
      "metadata": {
        "id": "l96c39xOoweA"
      },
      "execution_count": 55,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "tree_model.fit(X_train, y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 75
        },
        "id": "BJTZSg49pD5p",
        "outputId": "a5f4337a-4cef-4bcf-c4d7-76b0a00a9259"
      },
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DecisionTreeClassifier(max_depth=4, random_state=1)"
            ],
            "text/html": [
              "<style>#sk-container-id-4 {color: black;background-color: white;}#sk-container-id-4 pre{padding: 0;}#sk-container-id-4 div.sk-toggleable {background-color: white;}#sk-container-id-4 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-4 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-4 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-4 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-4 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-4 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-4 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-4 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-4 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-4 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-4 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-4 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-4 div.sk-item {position: relative;z-index: 1;}#sk-container-id-4 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-4 div.sk-item::before, #sk-container-id-4 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-4 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-4 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-4 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-4 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-4 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-4 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-4 div.sk-label-container {text-align: center;}#sk-container-id-4 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-4 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-4\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeClassifier(max_depth=4, random_state=1)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" checked><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">DecisionTreeClassifier</label><div class=\"sk-toggleable__content\"><pre>DecisionTreeClassifier(max_depth=4, random_state=1)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 56
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X_combined = np.vstack((X_train, X_test))"
      ],
      "metadata": {
        "id": "KX3mN00KpF_r"
      },
      "execution_count": 57,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y_combined = np.hstack((y_train, y_test))"
      ],
      "metadata": {
        "id": "OOB6f-NZpILY"
      },
      "execution_count": 58,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plot_decision_regions(X_combined,\n",
        "                      y_combined,\n",
        "                      classifier=tree_model,\n",
        "                      test_idx=range(105, 150))\n",
        "plt.xlabel('Petal length [cm]')\n",
        "plt.ylabel('Petal width [cm]')\n",
        "plt.legend(loc='upper left')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "jRvjKrtdpKHv",
        "outputId": "1c8afde0-dae8-4b92-ed86-e6f676a8ee5c"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn import tree"
      ],
      "metadata": {
        "id": "c51FH7q7pVAC"
      },
      "execution_count": 60,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "feature_names = ['Sepal length', 'Sepal width', 'Petal length', 'Petal width']"
      ],
      "metadata": {
        "id": "L3f49l76pdf8"
      },
      "execution_count": 61,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "tree.plot_tree(tree_model, feature_names=feature_names, filled=True)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 406
        },
        "id": "eJJOIc5wpgcy",
        "outputId": "143c32b1-94ef-479f-d18f-836e9cd47b47"
      },
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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PM2bMYO3atdJyxAXKs2fA0dGxUO/Hk7UPnnz/np6eBAQEEBERIZIBQRCEciTGDGjI3bt30dHRoWfPnvz444+EhYUBkJKSgpOTE0CRG3BZ/PHHH2RnZ5Odnc3atWtp2bJlof0mJib4+fmxaNEiaVtERARqtZro6GjMzc3p378/X3zxhRTbkwp6Bor7KksiANC+fXuOHDlCTEwMarWaJUuWSLMG7t27J5VBvnv3LqdOnSpU00AQBEF4cSIZ0JDz58/TpEkTvL29ad++PQsWLADgm2++YejQofj6+pKXl/fc7Xt7exMYGEj9+vVp0aJFkfECAKtXr5aKCdWrV48pU6agVqs5fPgwPj4+eHt7M3r0aGbNmvXccTxp0KBBUllmBwcH+vfvD+R/+p83bx6tW7fG1dUVCwsLqU7Bxo0b8fDwwNvbm06dOvHdd99J1RMFQRCE8iFqE5TC67Z2/aBBgwgMDCw0HkB4utft9ysIglDeRM+AIAiCIFRyYgDhGyg4OFjTIQiCIAivEdEzIAiCIAiVnEgGNCQ0NLTY+fuvSnBwMBYWFtL0wHv37tGgQQO8vb3x8PBg+PDh0gDG56kPoFKppAGS9evX59133yU1NRWA6OhodHV1pfYCAgJKFfM777yDl5cXXl5etGvXrtDCRDKZTGrP29ub5ORkAJYuXYqrq6tGf9aCIAgVnUgGKrGgoCB27doFgJWVFUeOHCEqKorz58/z6NGjF6oPIJfL2bt3r9Seo6Mjs2fPlvY/OTXx+PHjpYp3xYoVnD17lrNnz9KpUyc+//zzQvufnN5obm4OwNChQ1m6dGmp2hcEQaisRDJQDr744gumTZsmvT5+/DiNGjUCYObMmTRs2BBPT086duxIYmJikfODg4MLjfyfPn0606dPByA7O5sxY8bg7++Pl5dXoeuUJx0dHQwMDID8lQizsrKKXYyoLAoWDFKpVGRkZLxwe2ZmZtL3aWlpL9yeIAiCkE8kA+WgX79+rFmzRnq9cuVKaQ790KFDOX36NOfOnaNly5bMnDmzTG1///331KpVi7CwMCIiIggPD2fv3r1Fjtu2bVuhbvInv0r7yTs3Nxdvb2+qVq2KiYmJNNcf/q0P0KxZM3bv3l3q+Fu3bo21tTVXr15lwoQJ0vaEhAT8/Pzw9/cv1ANRkgEDBmBnZ8fatWuLrH/g7++Pn58fc+bMKXV7giAIgphNUC7c3NyoWrUqx48fp2HDhmzevJmvv/4ayO8lmDFjBqmpqWRnZ+Pq6lqmtnfu3ElGRgbLli0D8msKXL16VaplUCAoKIigoKAXeh+6urpERUWRnZ3NkCFD2LBhA++9994L1Qc4cOAASqWSiRMnsnDhQiZMmICtrS2xsbFYWVlx584dWrduTc2aNWnatGmJ7RUkDj/99BNfffUVCxcuBPKLHTk4OJCYmEhQUBC2trb07dv3hX4egiAIlYXoGSgnAwYMYNWqVezatYuGDRtiZWVFTk4OAwYMYPny5Vy4cIG5c+eSnZ1d5FxtbW1UKpX0+slj1Go1ISEh0rPwGzduFLvcb3n0DBTQ19fn/fffZ9WqVUB+d39Bl/+T9QFKS0tLi0GDBkk3cj09PaysrABwdnama9eunDx5skwxDh06tFCPQsHKhlZWVvTp06fM7QmCIFRmIhkoJ71792bLli38/vvv0iOC7OxsVCoVtra2KJVK6dP9f9WoUYOoqCgUCgXp6ens3LlT2te5c2fmzp0rFSGKi4vj/v37RdoICgp6aq2A0ozWv3v3LmlpaQAoFAo2b96Mh4cH8Oz6AAsWLJBKHT8pMTFRGh+hVqvZsGGD1N6DBw+k95OUlMS+ffvw9PQEYPPmzYUeTxTIyMggJiZGer1+/XqpvaSkJCmBysrKYtu2bVJ7giAIQsnEY4JyYmFhQaNGjTh06BDr1q0D8ge8ffbZZ3h6emJtbU3Lli2L/cQaEBBAw4YNqVu3Lo6Ojvj4+Ej7Jk+ezOTJk6VtRkZGBAcHY2NjU67xX7t2jXHjxqFWq1GpVDRr1kwarLhx40YWLVqEjo4OarW6UH2Ay5cvF/u4ICEhgQEDBpCXl4daraZevXr8/PPPABw9epRp06ahpaWFUqlk8ODBtGnTBoAbN24UqdQIkJmZSa9evcjIyEAul+Pg4CD1XFy5coVhw4Yhl8vJy8ujS5cuDBkypFx/PoIgCG8yUZugFN7EteuDg4MJDQ194dUKW7ZsydatWzExMSmXuHr16sWsWbNwcXEpl/Ygf52E6dOnExoaWuz+N/H3KwiCUBbiMUElZWBgwF9//SUtOvS8Dh06VG6JAMCff/5ZronA0qVLGTVqFBYWFuXWpiAIwptGPCaopHr37k3v3r01HcZLN3ToUIYOHarpMARBECo00TMgCIIgCJWc6Bkog8uXL2s6BOElEL9XQRAqO5EMlIKVlRWGhob069dP06EIL4mhoaG09oEgCEJlI2YTlFJMTEyxdQU0YeHChSxbtow5c+bQokULTYdTJocOHWL8+PEMHTqUkSNHajociZWVFU5OTpoOQxAEQSNEz0ApOTk5VYibxerVq1m2bBnff/89n376qabDKTNfX18UCgWTJ0+mRYsW9OnTR9MhCYIgVHqiZ+A1cuLECVq0aMF7773H8uXLX9uqfWq1mkGDBrFu3TpCQ0Np3LixpkMSBEGo1EQy8Jq4c+cO/v7+1KpViwMHDqCnp6fpkF5ITk4OrVq14saNG4SFhVWIXhdBEITKSiQDr4G0tDSaNm1Keno6p06domrVqpoOqVw8fPgQf39/TE1NOXr0aLkuXiQIgiCUnlhnoIJTKpX06dOH6Ohotm/f/sYkAgBVq1Zl+/bt3L59m759+6JUKjUdkiAIQqUkkoEKbtKkSezatYt169ZJlQLfJB4eHvzxxx/s3Lmz2OqHgiAIwssnkoEKrGD64I8//kiHDh00Hc5L07FjR3744Qdmz57N8uXLNR2OIAhCpSPGDFRQf/31F61bt2bIkCEsWrTotZ05UFpqtZoRI0awfPly9u/fT/PmzTUdkiAIQqUhkoEK6MaNGzRq1Ahvb2/27NmDjo6OpkN6JfLy8mjfvj1nz57l1KlT1KxZU9MhCYIgVAoiGahgkpOTadKkCUqlkpMnT1a60ruPHz+mcePGaGtrc+LECXJycti1axeDBg3SdGiCIAhvLDFmoAJRKBT07t2bhIQEduzYUekSAQALCwt27NjBvXv36NWrFydPnmTw4MHExMRoOjRBEIQ3lkgGKpBPPvmEQ4cOsWHDBmrVqqXpcDSmVq1abNiwgYMHD7J9+3YAjhw5ouGoBEEQ3lwiGaggfvnlF3755RcWLFhAy5YtNR2ORq1atYrff/+dTz75hKVLl1KtWjWRDAiCILxEolBRBbB//37Gjh3L2LFjGT58uKbD0ThnZ2ciIiK4cuUKVatWJSEhgT179mg6LEEQhDeWGECoYVeuXKFx48YEBASwfft2tLS0NB1ShaBSqdi/fz8//fSTlAikpKRgamqq4cgEQRDePCIZ0ICvvvqK1q1bU7t2bRo1aoSenh4nTpwQN7qniIiIYMWKFcydOxe5XDzZEgRBKG8iGXjF0tPTMTc3Z/78+axbt46LFy8SFhZG9erVNR2aIAiCUEmJMQOv2IkTJ1AqlRw8eJATJ05w8OBBkQgIgiAIGiWSgVfsyJEjGBkZsXHjRoYMGcLHH3+Mv78/ixcv1nRohcTExJCYmKjpMIRXxMrKCicnJ02HIQiChojHBK+Yp6cn58+fx8DAgKysLDp16sTXX3+Nj4+PpkOTxMTEUKdOHTIzMzUdivCKGBoacvnyZZEQCEIlJXoGXrFLly6hra3N0KFDGTNmDG5ubpoOqYjExEQyMzNZtWoVderU0XQ4wkt2+fJl+vXrR2JiokgGBKGSEsnAK3bw4EHq1auHlZWVpkMpUZ06dfD19dV0GIIgCMJLJpKBV0yU5hUEQRAqmpeSDIjBZxXTiw4SW7NmDbNmzQIgOzubzp07M2fOnPIKTxIdHU1gYCDR0dFF9gUGBjJ9+nQCAwPL/bqhoaHSNQpeT58+XdquKR9++CFLly7lacN7GjRogEKhACA1NZWkpCSSkpIAkMlkeHl5SceGhoZibm7+0mMWBOH1Uu7JQExMDHXca5OZlV3eTQsvyNBAn8tXrj5XQhAfH8+ECROIiIjA2toapVLJxYsXX0KUmvPfZKA8PHr0CEtLy+c+/8CBA+Tl5T3zmPDwcOn7KVOm8Pjx40L7o6Kinvv6giBUDuWeDCQmJpKZlc38Hq64WRmUd/PCc7qemMWYjTeee5BYQkICenp6mJmZAaClpYWnp6e0f/PmzcycOZPc3Fysra1ZtmwZ9vb2TJ8+nRs3bhATE0NCQgLNmjVj0aJF6OrqEhISwoIFC8jLy8PExITly5dTs2bNUscUGxvL6NGjiY+PR6FQMG3aNLp160Z0dDTNmzenR48eHDx4EJlMxoYNG3B1dSU3N5fhw4dz4sQJbG1tsbe3x9XVlV69eknTO7ds2cLYsWOpXr06OTk5DBw4kDNnzmBubs6WLVtKHO9x//59Vq9eTUhICJ07d+bbb78t888bICMjgylTprBr1y5WrFhR4vFqtZpVq1bxxx9/PNf1BEGovF7amAE3KwPq2xm/rOaFV8zLy4s6derg5OREYGAggYGBDBgwACMjI65fv878+fMJDQ1FX1+ftWvX8tlnn7F27VoAjh49SkREBObm5nTv3p0lS5YwevRoOnXqxIABAwDYsGEDkyZNYv369aWOafDgwcyZMwdvb2+SkpJo0KCB9Kk+JiaGoKAgfvzxR2bMmMGsWbNYsmQJixcvJj09nUuXLpGSkoKvry+urq7UrVuXESNGADB9+nQgv6cgKiqK5cuX4+7uzvDhw1myZAmff/55kViysrLYsmULISEhxMbG8t5777F161ZcXFyA/J6Vjh07Fvs+PvjgAz7++OMi2ydPnszYsWNL3bNQ8PNv0qRJoe3+/v4olUref/99Pvvss1K1JQhC5SIGEAqlIpfL2bFjB2fPniU0NJQVK1awaNEiwsPD2bdvH5cuXaJx48YAKJXKQnUWunXrhoWFBZB/A1+xYgWjR4/m6tWrTJkyhYcPH6JSqVCpVKWOJz09nSNHjjBo0CBpW15eHjdv3sTKyopq1apJiYG/vz8HDx4E4PDhwwwePBi5XE6VKlV45513nnkdLy8v3N3dpXZOnDhR7HE2NjY4OzuzZMkS6efwJDs7uzJ11x87doybN2/y888/l/qckJAQKbkqEBsbi4ODA4mJiQQFBWFra0vfvn1L3aYgCJWDSAaEMvHy8sLLy4uRI0dibW3NhQsXUKvV9OzZkwULFpSprb59+xIcHEzz5s05f/48Xbp0KfW5arUaXV1dIiMjkclkhfZFR0ejr68vvdbS0pIG2JVVadvZtGkTK1asoF+/fnTu3Jn+/fvj5+cn7S9rz8CRI0eIjIyUehYAXFxcOHnyJDY2NkXayMzMZPPmzZw7d67QdgcHByB/8GifPn04efKkSAYEQSjijSwBdz81l/6rLpd43L4rj5l9KKZcrpmRo2ToH1dpOi+Slr9EcTom9anHzj4UQ9N5ETSdF8GKsPvlcv2XLS4ujlOnTkmvr169Sm5uLvb29rRp04atW7dKo//z8vIK3ZS2bt1KUlISKpWKFStW0LJlSyC/JHHB+IUlS5aUKR4TExP8/PxYtGiRtC0iIuKpI+4LBAYGsnr1atRqNcnJyWzdulXaZ2pqSmrq039vz9KqVStCQkI4e/Ysvr6+TJw4EQ8PD9atWwf82zNQ3FdxjwgmTZpEfHw80dHR0s81Ojq62EQA8sds+Pn5FRoPkpSURHZ2/kDerKwstm3bVmichyAIQoE3MhmwMdVlZb+SV85r627B+Jbls+LaomPx2JvpcWysD/O6ufLJ5huoVEVvTMdup/DXjRQOf+TNrmGe/Ho8nujHFX/mhUKhYOrUqdSuXRtvb28GDBhASEgI1apVo3bt2ixcuJCePXvi6emJt7c3R48elc4NCAiga9eu1KlThypVqjBs2DAAZs+eTYsWLWjQoMFzjbhfvXo1+/fvx9PTk3r16jFlypQSk4ERI0agp6eHu7s7Xbt2xdfXVxoU+c4773Do0CF8fHxYvnx5meMBMDIyYsCAARw4cIA9e/ZQrVq152rnWeLj4/H29i60rbhHBFeuXKFhw4Z4eXnh5+eHj48PQ4YMKfd4BEF4/ZV7bYKIiAj8/PzYM7z+Sx9AuPVCIrMPxWKsq0ULN3M2nUvk1DhfYpOy6Rl8Sfq+x/KLdKxrydFbKchksKRXLapbGrAu8gEnolP5qZvrC8cSuCCKpb1r41o1fwZF59/O83UHF3wcTAodN3nHLepUM2RAw/xPeN/tv4O5gTajmtm/cAzPcj4+nfa/nufMmTMlripY8DsszbElKRiMV/BfTVOr1WRmZmJkZERaWhpvvfUWCxcuJCAgQNOhaUx5/r4FQXg9vbZjBh6m5zJ9dzQ7h9XHzkyPabtvP/XYuJRc2tauwvT2Lsz/O45Fx+KZFfTsKWz9V13mflpuke11qhnyc/ei9QTiU3KwN9eVXtub6RGfmst/yw/Fp+TSpnYV6bWdmR43HmY9Mxah/CgUCgIDA8nLyyM7O5uBAwdW6kRAEAQBXuNkIOJuOn6OJtiZ6QHQ28eavVeSij22qrEOAdXzu4K9HYw5ejulxPZL85hBKFlF6REooKOjw+nTpzUdhiAIQoXy2iYDZaGn/e/QCC0ZKIt5lv9fZe0ZsDPTIy45V3pMEJeSg52pbjHH6XI3OUd6HZ+Sg51Z0eMEQRAE4VV5bQcQ+tgbcyY2jXup+TfW9VEPy7X9lf3qsH+kV5Gv4hIBgE51LVgZngDkP59/nJGHVzFjJjrVteTPyIfkKlSkZCnYfvERHes+/3K1wrOn7T1p27ZtTJs2rVyumZ6eTvfu3XFzc8PDw4Njx44Ve1xwcDAWFhZ4e3vj7e1d7MwBQRAETXttewasTXSZ1s6Zd4MvYaSrRYCLKSZ6WhqLZ2RTez7edJ2m8yLR1ZIxt5srcnn+/PfPtt6kbe0qtHW3oFkNM5rVMCNwQRQAw5vY4WKh/4yWhZLY2dmxa9euEo8LCgoiKCioXK45e/ZsnJ2d2bRpExEREfTq1Ytr164hlxfNr4OCgggODi6X6wqCILwMr20yANCmtgXdPKsCMDc0Fl+H/E/ijlX0OTXOt8j3AAHVzaTxA719rOntY10usRjrafH7++7F7pvTtfBgxUmtnZjUunymNFYm69at4//+7/8wMTGhQ4cOrFq1SpqHX1Dl8Fl1CYKDgwkNDS2XG/P69evZtGkTAL6+vlhZWREeHo6/v/8Lty0IgvCqvbaPCQAWH4unzaKzBC6IIioug/EtHTUdkvCSJCQk8Mknn3Do0CHOnDlDenr6U48tqEtw9uxZevfuLZVdfpaOHTtKXflPfv137n6B2NhYnJ2dpddOTk7ExsYWe+zu3bvx8vKiTZs2hRZuEgRBqChe656Bz1o68plIACqFkydP0qRJE2l53cGDB7Nly5Zij31aXYJnKc1jhufRpUsX3nvvPfT19Tl06BDdunXj6tWrmJiYlHyyIAjCK/JaJwOCUJznqUvQsWNH4uPji2z39PQkJCSkyHZHR0fu3LkjFTGKiYnB0bFoYvrkyootW7bEzs6Oa9euFapbIAiCoGkiGQB6Lr/I/wIdpLEEr4pKpabrsgtkK1SoVGpqWhnwQ9eamOhrE5uUzVvzo3D7Z6qigY6cbUPrv9L4KpJGjRoxYsQI4uLisLe3Z8WKFeXafll7Bnr27Mmvv/7K3LlziYiI4OHDhzRo0KDIcfHx8djZ2QFw/vx5YmJiqFGjRrnELAiCUF5EMqBBcrmMNf3rYKKf/2uYvieaRcfimdAqf3BhNRNd9o/00mSIFYaNjQ0//PADLVq0wNjYmBYtWkg1BTRh/Pjx9O/fHzc3N3R1dQkODpZmEgwdOlSaubBgwQK2bt2KtrY2urq6hISEUKVKlRJaFwRBeLUqVDKQlatk9Mbr3EnKQa1W09KtClPaOvPXjWRmH44lV6FCWy5jRucaeNnnzxyw/+IEk1o5sePSI7LzVCzo4cqSE/c4fy8DBzM9lr1fGz1tOZ9svoG+tpwL9zNIylTQua4Fk9s4F4khLiWHqTtvk5CWi0KlZlygAx3qWPIwPZdRG66TnKVAoVTTv0E1Pmhs+8LvuSARUKnUZOYqMdJ9rcd0vlRdunShT58+AHz11Vc0atQIyC/tW1DZ78nvIb9KYWhoKACDBg1i0KBB5RKLiYnJU8csLF26VPr+u+++47vvviuXawqCILwsFSoZOHwjGUsjHZb9M0UvOSv/Wa+XvTHbhnggl8s4G5fO5B232DX831Ksdma67B3hyeJj8by/8jLbhnpQw9KAPiGX2HXpkTT98MK9DDYMrgdAj+UX2H81qVCdAID/bbnJ/7V1xsPWiOQsBR1/PUcTFzM2nUvk7RrmjHnbvlBsT7qfmkv/1cWXTn7Px5ohT0keeq+4xMX7GbhbG/JFOxdpe2J6Lu0Xn0NLDoP8bXnXu2ppfoxvrDlz5rB161Zyc3OpWbNmoZuuIAiC8PwqVDJQ18aIb/fH8PXeaAKqmxHoag7kFyUas/EOcSk5aMll3EwsXNinc738QVr1bI2obqFPDcv85+z1bY24k/Tv0r/v1LdCXyf/k3e3+lU5djulUDKQkaMk7E4q47bckLblqdTceZyNr4Mxn269SVaekmY1zIodX2Bj+nzd+usG1kWpUvPt/jusOH2fUc3ssTbR5fT//LAw0uFucg69V1zCxUKPhk6mZW7/TfHll1/y5ZdfajoMQRCEN06FSgZcLPTZPbw+f99MYcPZhyw7eY81A+oyecdtevlUpZe3Nek5Smp/F1bovILaA1qywnUI5HJZqeoQFFADOloy9o3wRCaTFdm/+QMPDt9IZsGROLacTyxS+fB5ewYAtOQyenlbM2rDNUY1s0dPWy69FwdzPdq5V+FMbHqlTgYEQRCEl6NCJQPxKTlUMdCmcz1LGjia0PKXKADScpTY/1OdcNU/6/8/j60XEunXoBoAWy4kMvZth0L7jfW08LQzZsXpBAb52wD5dQY8bI24m5yDjakuPb2q4lxFnyk7bxVpv6w9A48z8gCwMNJBrVaz89IjalsbApCYnoe5gTbaWjKSsxT8fTOFae2KjnEQyi4wMJDp06dLaxG8Kg8ePKBt27bS68TERKpWrUpkZCQAmzdvZtKkSSiVSlq2bMmiRYvQ0tLcEtuCIFQeFSoZuPIgk+/2xyCTgVoN33SqDsCElo6M33oTE31tOr9AUZ96Nkb0DL4oDSD873gBgPk9XJm68zarwhNQqtTYm+kR0ted49Gp/Ho8Hi25DLlMxtS2L35jfpiRx9hNN1Co1KjVampZG/J1h/z3HBaTypzDschlMlRqNb28rXm7pvkLX1PQHGtra6KioqTXffv2xdMzf+xLamoqY8aM4fjx4zg6OtKjRw9CQkIYPHiwhqIVBKEyqVDJQEu3KrR0K3qDblWrCq1q/bu9YBAfQNyXTaTvn6w7ADCxVeH1/30cjPm+S9E53gWDCgFsTfWkAYxPKs86BgVqWxuyZ4Rnsfs61rV846sZZmZm0rdvX27duoVKpaJjx47MnDmTffv2MW3aNHJyctDW1mbRokXSHH6ZTMZ3333H+vXrycrKYvXq1cydO5czZ87g7OzMli1b0NPTY9CgQRgYGBAZGcmjR4/o2bMnM2bMKBJDbGwso0ePJj4+HoVCwbRp0+jWrRsJCQm8//77PH78mLy8PEaMGMGYMWPK7b2npaWxbds2aankPXv20KxZM5yc8v+fHTZsGD///LNIBgRBeCUqVDIgVC579uzB2tqazZs3A5CUlARAw4YNOX78OHK5nPDwcEaOHMnp06el8xwdHYmIiGDOnDm0bduWEydO4ObmRrt27di4caM0/TAiIoK//voLgLfffpsdO3bQuXPnQjEMHjyYOXPm4O3tTVJSEg0aNCAwMJDVq1fTpk0bJk+eXCi2Jz2rdPIHH3zwzHLFGzZsoEmTJtjb5ye2Zal1IAiCUN4qTTLwUzdXTYcg/IeXlxcTJ05k/PjxtGjRgnbt2gFw//59+vXrx507d9DW1ubKlSuFznv33XcB8PHxwc3NDTc3NyC/euCtW/+O5ejTp4+0NHHfvn05dOhQoWQgPT2dI0eOFFp7IC8vj5s3b9KoUSOGDBlCZmYmrVq1KnZ8gZ2dXaFu/7IICQlh6NChz3WuIAhCeas0yYBQ8dSsWZPw8HD2799PSEgI8+bNY+/evYwaNYpBgwYxcOBA0tLSMDUtPINCTy9/MKmWlpb0fcHr0tQhKKBWq9HV1SUyMrLY2SNHjhxhz549zJgxg7Vr1/Lrr78W2v+8PQMxMTFERkbSrVs3aZujo2Oh3o+n1ToQBEF4GSpsMnD8dgo/ht4t9Dz/VVoX+YCv9kbj62DCyn51SEjLZdCaKyhUapQqNQ0cTfi2U3V0tOQcv53CwDVXcLHI/xTqYqHPb71rl3iN6w8zGbvpBqk5SmxNdVnQw41qJrolnrci7D5LTsSjVkM3TyvGt8x/zrzmTAK/HI3D1lRPYz+3srh79y4WFhb07NmTgIAA6tXLjzklJUV6dv7fG3BZ/PHHHwwfPhyAtWvXMnXq1EL7TUxM8PPzY9GiRYwaNQrIf7Tg4+PDnTt3sLe3p3///tSsWZOPPvqoSPvP2zOwcuVKevTogaGhobStffv2jBs3TkoClixZQs+ePcvctiAIwvOosMlARdCmtoX0eMHCUJtNH9TDQEcLtVrNsD+vsSHqIe/75U9V9LIzLvMNeNL2W4xt7kA7dwuWnrjHd/tjmNf92Y8zoh9n8+vxeHYP98RAR0733y8SUD2FptXN6ONXDRcLfX4Mvft8b/gVO3/+PJMmTUImk6FSqViwYAEA33zzDUOHDsXMzEx6JPA8vL29CQwMlAYQ/ne8AMDq1asZPXo0ixcvRqlU4uTkxM6dOzl8+DA//PAD2trayOVyaaBfeVi5cmWRJMfU1JR58+bRunVrlEolLVq0YMCAAeV2TUEQhGd5JcnAnEOxqFFLn2BPx6Tx5Z5odgyrzy9H4th56RG5SjW2prrM6+aKhZFOofPXRT7gRHSqdGP+4XD+wKpPWziSnafim313iIxLI0ehpp17Fek65UlHS47OP1O+85RqsvNUxXYtl9bD9FxuP86mnbsFAO/7WjP7hzMlnrfr0iM617PEzCD/V9fLpyo7Lj6i6SuuuFgeOnToQIcOHYps79ixY6Hu94JBfJDftV/gyboDkJ9EPKlRo0YsWrSoSPtPnmNvby8NYHzS4MGDX9pI/v+OgSjQs2dP0RsgCIJGvJJkoLuXFf1XXZZu0hvPPqSHlxUA7/tZ89Fb+SOqFx+L55ejcfzfE+vzl+SXo3HUsNTnm07VUarUDFpzhdAbydJSxgX2XXnM7MPFj87+rlMNGjqZlHitXIWKTr+dJzYphxZu5vT0+rdWwMX7GbRddBZDXS0+ftu+2CmST7qXmoud6b/Pu430tNDTlvE4Mw8LQ52nnhefkiuVNQawN9Pj4LXkEmMXBEEQhKd5JclADUsDLAx1OB2Thre9EXuuPGZCy/yV+sJj01hwJI70HCU5CpX03L20Dl5LIjNPxdrIBwBk5iq5mZhVJBlo625B238+hT8vXW05+0d6kZ2n4rOtN9l56RFd61tR39aIsHG+mOhrc+l+Bv1WXWbLEA+cqpTtvQjlJzg4WNMhCIIgvDZe2ZiBnl5V2XTuIY8z8/CyM8bCSIcchYpPNt1g24f1cbUyYN/Vxyw5fq9okPL8VfgK5ChU0rr9amBeN1eppPHTlEfPQAF9HTld61uxMvw+XetbSWWIIb/Ykp+jCefvZTwzGbA11SU+9d8iShk5SnIU6mf2CkB+hca4lH/Pi0vJwc6s5EGHgiAIgvA08pIPKR9BHpbsvfKYPyIeSI8IchQqVGqoZqyDUqXmj4gHxZ7rVEWfS/czUSjVZOQoOXjt3wVgWteqwm8n7qFQ5icL91JzeJCWW6SNtu4W7B/pVexXaRKB+JQc0nOUACiUavZcfoT7P3UEEtJypWfZ8Sk5RN5Np3bV/H3LT91jxv47RdqraqyLi4U+e688BmBtxAPauf/7aKFX8EUi76YVOa9DHQt2XHxESpaCXIWKPyMf0uk1XakwNDT0ldcHeFJwcDAWFhaFxiccPXoUDw8P3Nzc6N69O+np6SW2s3z5cjw9PfH29sbb25sNGzZI+wYNGoSTk5O0LyQkpMT29uzZg5eXF97e3tSvX59ffvlF2jd9+nRsbGyk9r7//ntpX4MGDTA2Ni40JkIQBKE0XlnPQBVDHXzsjTl2O5VF79YCwFRfm+EBdrRedA4rI22aVjcj4m7Rf3wbOpngZWdE4C9R2JnqUs/WSNo3+i17ZhyIod3iswAY6Grx0zuuWJf+g36p3HqUzfQ90QCo1GoaOpkyrnl+oaNdlx4RcjoBbS0ZajVMau2E6z/P9a8/zHpqD8GMzjX4ZPMNvtp7R5paCKBSqbmUkIntE2MKClS3NODDJrZ0+PUcAEEeVjSr8foNHqwogoKCpEcKKpWKQYMG8eeff+Lr68u4ceOYPXt2iWWTe/TowaBBg5DJZNy/f5+6devSqVMnDAzy/x/46quvCi1sVJJmzZoRERGBlpYW6enpeHh40K5dO1xd8wfQjhgxgunTpxc5Lzw8XKPJlSAIr69XOrWwuDX/xwU6MC7Qocj2/9YZ+OGd4qfc6WnLmd7epdxifJpmNcw4MKr4ioSDG9kyuFHx5YmvJ2bxeZviixrVtjZk9/CitQkuP8ikvbsFNqbFd/8/63qa8sUXX6BWq/nqq68AOH78OOPGjePUqVPMnDmTDRs2kJOTg4ODAyEhIVhZWRU6Pzg4mNDQUOnGXHCzmz59OtnZ2YwfP55Tp06Rk5ND165dpeuUp/DwcKysrPD19QVg+PDhdO/evcRk4MlFkQp6ElQq1XPHYWz87yOvrKwsFArFC81cEQRBKMkre0zwutHXkXMyOpX+qy6/UDvrB9XDWK9sZWjr2Rgxp2vNMl9rzZkEPt95G3ODV798RL9+/VizZo30euXKlfTv3x+AoUOHcvr0ac6dO0fLli2ZOXNmmdr+/vvvqVWrFmFhYURERBAeHs7evXuLHLdt2zap+/y/X8ePHy/xOi9SH2DDhg3UrVsXLy8vlixZgpHRv71X3377LfXr16dfv37Ex8eXqr3jx49Tv359nJycGD9+PDVr/vv/w++//46npyddu3bl6tWrpWpPEAThWcSiQ0/R1cOKrh5WJR9YgfTxq0affxZBetXc3NyoWrUqx48fp2HDhmzevJmvv/4ayL+xzZgxg9TUVLKzs6Xu7tLauXMnGRkZLFu2DMj/9H316lWplkGBoKAggoKCyucNlVHBGgHXrl2jT58+tGjRAktLS7777jtsbW1Rq9XMnDmTgQMHsn///hLbCwgI4Pz589y7d48ePXrQvn17ateuzYgRI5g6dSra2tqsXr2aLl26cO3atVfwDgVBeJOJngGh3AwYMIBVq1axa9cuGjZsiJWVFTk5OQwYMIDly5dz4cIF5s6dS3Z2dpFztbW1C3WtP3mMWq0mJCSEqKgooqKiuHHjRrHr/r9oz4CjoyN37vw72PN56gPUqlULFxcXDh8+DOQvWSyTyZDL5YwZM4aTJ0+WqT1bW1sCAgLYvn07ADY2Nmhr5+fwffv25fHjxzx69KhMbQqCIPzXS+sZuJ6Y9bKaFp7Dq/h99O7dm6+//pq4uDjpEUF2djYqlQpbW1uUSqX06f6/atSoQVRUFAqFguzsbHbu3EmPHj0A6Ny5M3PnzmXFihVoa2sTFxeHlpYWNjY2hdp40Z6BBg0a8PDhQyIiIvD19eXXX38ttCKgu7s7Bw8elMoOF7hy5Qru7vnjYeLi4jh16pQ0piE+Ph47OzsA1q1bh6fnv2NEWrVqxYwZM/D39y/U3rVr16hZsyZaWlokJyezf/9+6dHKk+0dOHAAfX19LCxebP0MQRCEck8GrKysMDTQZ8zGG+XdtPCCDA30iwzcK08WFhY0atSIQ4cOsW7dOgDMzMz47LPP8PT0xNrampYtWxb76TggIICGDRtSt25dHB0d8fHxkfZNnjyZyZMnS9uMjIwIDg4ukgy8KLlczvLly+nfvz+5ubl4eHhIUwEfPnzIo0ePir3x/vbbb+zevRtdXV3kcjkzZ86kbt26QH5vSUJCAjKZDFtb20IzF86ePYuDQ9HBs9u3b2fZsmXo6OigVqsZPHgw7du3B2DSpElERkYil8sxMTFh8+bNYnChIAgvTKZ+crH3chITE0NiYmJ5Nyu8ICsrK6ka4LNERETg5+fHmTNnpJH1b6L/zmB4lq1bt3L+/PkilQ+f19mzZ5k/fz5Lly4tl/YKBAYGMn369DJNMawsv29BEJ7upTwmcHJyKtVNRxA0ycDAgL/++ouOHTuya9euZx7btWtXunbtWm7X9vLyKvdEoEGDBjx48ABdXbEipSAIZSNmEwiVVu/evendu7emwyg34eHhmg5BEITXlJhNIAiCIAiVnOgZEJ7q8uUXW3BJeD2I37MgCCIZEIqwsrLC0NCQfv36aToU4RUxNDR8qTNNBEGo2F7KbALh9VcRZ4R8//33bNq0iQULFhSZm1/RhYWF8dFHH9GzZ08mTpyo6XCKKO1ME0EQ3kyiZ0AoVkWbEfLLL7+wfv16Fi9ezPDhwzUdTpn5+voik8kYMWIEzZs3Z9SoUZoOSRAEQSJ6BoQKb9++fXTs2JHRo0fz008/aTqcF/LJJ5+wYMECdu/eTZs2bTQdjiAIAiCSAaGCu3z5Mo0bN6Zp06Zs374dLa2yVYCsaBQKBV26dOHEiROcPHlSWsZYEARBk0QyIFRYiYmJNGrUCAMDA44fP46pqammQyoXKSkpBAQEkJOTw6lTp7C0tNR0SIIgVHJinQGhQsrNzaVHjx6kpqayffv2NyYRgPx6DTt27CAlJYUePXqQm5ur6ZAEQajkRDIgVDhqtZqRI0dy8uRJNm/eTPXq1TUdUrmrXr06mzdv5vjx44waNQrRQScIgiaJZECocH744Qd+//13fvvtN5o1a6bpcF6aZs2a8dtvv7Fs2TLmzp2r6XAEQajExNRCoULZvn07EyZMYNKkSQwYMEDT4bx0AwcO5PLly3z22WfUqlWLzp07azokQRAqITGAUKgwzp07R9OmTWndujUbN25ELq8cHVcqlYoePXpw4MABjh07hqenp6ZDEgShkhHJgFAhJCQk4O/vj4WFBUeOHMHY2FjTIb1S6enpvPXWWzx+/JiwsDAUCgVr167l008/RSaTaTo8QRDecJXjo5dQoWVnZ/POO++Qm5vL9u3bK10iAGBsbMy2bdvIzc2lW7dunDlzhvHjx3Pr1i1NhyYIQiUgkgFBo9RqNUOGDCEqKoqtW7fi4OCg6ZA0xtHRka1btxIZGcnKlSuRyWQcOXJE02EJglAJiGRA0Khvv/2WNWvWEBwc/NoVHypvixcvZurUqYwaNYoNGzZgbW0tkgFBEF4JkQwIGrN+/Xr+7//+j+nTp9O7d29Nh6NxjRo1Iisrix9//BEzMzMSEhLYvXu3psMSBKESEAMIBY0IDw/n7bffpmvXrqxZs0YMknvCmTNn+Pnnn1m1ahUqlYqkpCTMzc01HZYgCG8wkQwIr8zYsWPp0qULderUwd/fHwcHB0JDQzEwMNB0aBXSnTt3WL9+vZhRIAjCSyeSAeGVSE5OxsLCgoULF/Lbb7/x4MEDwsLCsLW11XRogiAIlZ5YgVB4JY4fP45arWbz5s1cvXqVv//+GxsbG02HJQiCICCSAeEVOXLkCEZGRuzbt4/+/fvzzjvv0Lx5c1auXKnp0IoVExNDYmKipsMQXhIrKyucnJw0HYYgVBjiMYHwStSuXZtr166ho6ODTCajT58+fP7557i5uWk6tCJiYmJwd69DVlampkMRXhIDA0OuXLksEgJB+IfoGRBeiVu3bmFgYMCkSZMYMWIE1tbWmg7pqRITE8nKymSA/y/YmNbSdDhCObufeo2QsI9ITEwUyYAg/EMkA8IrcenSJZycnNDT09N0KKVmY1oLxyqiaJAgCG8+kQwIr0RFfBwgCIIg5BPJQDkSg84qpvIcLBYes5EDV34BIE+Vg4dtG7p5TS+Xtp/0KCOGn0O782Wn8Oc6//t9LZnU9tAz283MTeFU9B+0qDVc2v/FzgZ8HLgJS6NX331+Nm4Xuy7O5n7qVd5v8CONXd4r9rjdl37g7N2d0ut7qVcY0mQZnvYdWBn2MdcfHMVQ1xyAFrVG0Mil16sIXxBeayIZKCcxMTHUruNOdmaWpkMR/kPf0ICrl6+8cEKQknWfree+ZkLr/ZjoV0WlVnIv5Uo5RVm+iksE/isrL4XQ678VSgZeVEbOY4z0LJ7r3GombgxqtIj9Vxc887gOdT+lQ91PAXiQdos5B9tTx6aFtL+jx4SnJhKCIBRPJAPlJDExkezMLFzn98DAzUrT4Qj/yLqeyI0xG8tlsFhq9kO05bro65gCIJdpYW9eT9p/Nm4XB67MR6HKw0TPij4N52JuYMuui7N5mH6bpMw40rIfUsPKn95+s9CW63Iq+k/+vrEMlVqBnrYxfRvOo6qxy1NjiE+5zNrw//Fpq92kZj9gyvb6jHxrLXVtWvJnxGScLbxp5NKbMeurMf/dBADOxG5h54WZ6GkbUsempdTWhsgppGTd5/t9LbE0cuLDpsEAnIpex6X7B0nPeUQP76+pb9f+mT8XpSqPC/f2E3ZnPfHJF/miY9hz/XxtTPMfJcnKUDIl7M6f+DoGoaOl/1zXFAQhn0gGypmBmxXG9e00HYbwEtib16OaqRtf7PTFtWoAbtZN8Xd+Fz1tIx6k3eKv60v5OHAzOlr6hMdsYvPZ6Qxu/CsAtxLDmNBmPwY6Ziw9Pphjt1bS3HUIHratpW7syLvb2Xb+G4Y0WfrUGGxN3XmcGUeOIoNrD47ibOHDtQdHqWvTkusPj9HGfXSh41OzH7AxcgqftdqDhZEj6yMnS/t6+nzLz6Hdi+lFkPFZqz3cfnSalWEfPzUZuPM4klPRf3Lp/gFcqwbwds3BuFk3k/avCR9HzOOzRc4z0rNgTPMNz/xZl4Zareb0nQ0MbLSo0PZ9l3/i0NVF2JvX4x3PaZgZiMWtBKEkIhkQhFKSy+SMaLaau8kXufHwGGHR6zh6M5jxrfdxJSGU+6nX+OFgRwBUaiX6OibSuZ72HTDSrQJAY5f3OHXnT5q7DiEh7SY7TgwhPecRarUaFapnxiCTyahp1YgbD09y/cEx2tf9lL2XfiQ1+wFKVS5VDO0LHR/96AzVLRtiYeQIQJPq/bgQv/+Z1/B17AqAs4UvjzLuFHvMhsgpnLi9miDP/+Mdr2noahWtL9GnwdxnXudF3Ug8gZZchxpWDaVtQfU/x1S/GmrUHLgyn5VhYxjdfP1LjUMQ3gQiGRCEMnIwr4eDeT2a1RzE59vqcS/lCmrUeDt0oZfvjDK1teLUSPr5/4xb1QDiUy7x69EBJZ7jWjWA6w+PcedxJL18v2fvpR85F7cH16oBz/uWCtHRyp/+KZdpoVIriz2mZe2RGOlZcPRGMFfuh9LQuSf17doV6q5/2T0DYdF/4u/8bqFtBb0AMmQ0dxvKvivzXvg6glAZiGTgDZJ7P5Wb47dRZ2W/Zx73eN8V0s/G4zS+5TOPKw1lRg43xm4m83ICMj1taszsgmnD4p/Nx8w+ROKW8wDYDWuCzUD/F77+q5ScdY/kzHhcLP0AeJB2A4UqDzMDG9yrNefAlQW0qj0SSyMnlKo87qdek8YUnI/fQ4e6n6KvY8qpO39S65/u9Oy8NOnT/LFbpVuauZZ1UxYeeZ9qJq5oyXWoWbUJ+67MI6j+lCLHulj68ceZ8TzOvIuFoQOnotdK+/R1TMhRZKBWq8tcFdHC0EEayHcrMYywO3+y9dzX1LJuSt+G+Tfgl9kzkKvM4mzcLia1OVhoe0rWfSkhiIjdgp1Z3ZcWgyC8SUQy8AbRtTEtMREAsGjrjkVb93K5ZvyiY+jZm1F76Xukn4/n2oj1+BwZg0xeeBBYyrHbpPx1A+/DH6HKyuNch18xb+6KvsvzjTzXBJVKwY4L35OUGYeOlj4ymYz+/vMx1bfGVN+aXr7fs+zEUJSqXFRqFW/VHCwlA9UtG7Lk2EBpAGHTGv0BeMdrGvNDe2CkZ4GHbZtSxWFjWgulKhc366YAuFVtysGrv+BWtWmRY031renh8w0L/noXPW1D6tq0kvYZ6VbBw64t3+1rjrVxDWkAYVnVsPKnhpU/ecocLsTvfa42AC7eO8AfZz4jMzeZC/F72Xnheya0OYCJnhVrwsdR366dNH7hXNxuHMzrSY8/CoSEjSYt+yEymQxT/Wr0a/jzc8cjCJWJqE1QTiIiIvDz86P+nuEvfQBh4tYLxM4+hJaxLuYt3EjcdA7fU+PIjk3iUs9g6fuLPZZj2bEuKUdvgUxGrSW9MKhuyYN1kaSeiMb1p24vHEtU4AJqL+2NgWtVAM53/g2Xrztg4uNQ6Lhbk3dgWKcaNgPyn+/e+W4/2uYG2I9qVqTN8pR+Pp7z7X/lzJkz+Pr6luqcgt/lhNb7y2UFwl0XZwPQsd74F25LeHGxSeeYdaBNmf6fEIQ3negZeM3kPkwnevpu6u8chp6dGben7X76sXEpVGlbG5fp7Ymb/zfxi45Rc1bQM9u/3H8VuffTimw3rFMNt5+7F9meE5+Crr259FrP3ozc+FTw+U8s8SlUaVP73+PszMi68fCZsQiCIAivhkgGXjPpEXcx8XNEz84MAOvePiTtLX7hG52qxpgFVAfA2NuBlKO3S2y/NI8ZhLIRPQKCIFR0Ihl4g8n1nvj1aslQK589bQ3K3jOgZ2dGblyy9JggJy4FXTvTIsfp2pmRczdZep0Tn4LuPwmNIAiCoFkiGXjNGPvYc2vSdnLupaJna8rD9VHl2n5ZewYsOtUlYWU4Ll92IP18PHmPMzD2KjpmwrJTXWK+P4D1ez6osvJ4tP0iddeWPI2uskvJus+a8P8x8q01zzzufPweYh6fpZPHxBe+Zo4ig5Cw0dxLuYy2XJf3/OZQw6rozI9jt0L46/oyZDIZWjIdgjyn4l6tOQBHbgYTev03HqbdZEzzjdJgR4Djt1bx142lKFUKHMw96NNwbrHrFAiC8OqIZOA1o2ttgvO0dlx6NxgtI11MA1zQMtFcWWD7kU25/vEmIpvOQ6arhevcbtJMgpufbaVK29pYtHXHrFkNzJrVICowf915u+FNXquZBJpiZmBTYiIAUN+ufYnLBpfWgau/YGHowIcBy4lNOsfvJz7k/zqcQC4rPEPE2sSVT1psw1DXjPiUS/wc2oPvgi4gl2lR3bIBta3fZu2ZTwudcy/1KvuuzGNC6wMY6prxZ8QkDl9bTLs648oldkEQno9IBl5DFm1qU7Vb/ij32LmhGPvmj9zXd6yC76lxRb4HMAuoLo0fsO7tg3Xv/4zwe05axnq4//5+sftqzula6LXTpNY4TWpdLtd90xTUD9DXNqaubUtO39nIl53CC1UZfJQRw7zQbnjbd+LqgyPIkDEkYBlVjatzMvoPrj84Tn//F59KFxW7nSEBvwPgWMUTYz0LYpKicLEoPPLe7YlFjmxN66BU5ZGdl4ahrjkO5h7Ftn0/5SpOVbwx1M1/RFTHJpDt578TyYAgaJhIBl5D8YuP8XjvVdR5SvSdq1DjPzdd4fWSmv2ATVH/x2et9lLF0I6NUVOfemxS5l3q27Wju/dX7Ls8jwNXFvB+gx+e2f6iI31IybpfZLudeV0G+BetEJiUFYeF0b9TQ6sYOpCcGQ8WT5+GFx6zERtTN6l08NPYmddl09lpJGfdw1Tfmsi7O0jKjHvmOYIgvHwiGXgNOX7WEsfPXnz1QKFiiH50BhfLBlQxzB9r0cjlfc7F7Sn2WBO9qtLzd2cLH64+OFJi+6V5zPAioh9HsP3CDEa//WeJx1YzcSWo/lSWHBuIlkybWtbNkMvEP0OCoGnir1AQXiNPrv3/rNoBTyprz0AVA3seZ9yVSgonZd7F3LD4hbTupVxh+YlhfNDkN6xNapbqPTR07klD554ARMZuo5qpa6nOEwTh5RHJQCV2sedyHP4XKI0leFXUKhUXui5Dla1ArVJhUNOKmj90Rdsk/0b3aPdlYr7bj1qlxqxpdWrM6IxMq/Q17l83LpZ+rIuYQHLWPcwNbAmLXleu7Ze1Z8DboTPHboXQw/trYpPOkZ7zCKcq3kWOe5geza/H+tO34U9FxhM8S2r2A0z1rcnKS+XA1V9oVXtUmeITBKH8iWRAeOVkcjl11vSXbv7R0/cQv+gYThNaoUjLJnrqLjy2DUHXzoxrH67j4Yaz5TbgsSIy1bemm9d0fg7tjp62EW7WTQuVP37VWtX+iJCwj/hqd2O05Lr0bfizNJPgyRoB285/Q2ZuCpuipknnDgn4narGLhy9GcLeyz+SnvOI3098iL6OCV90PAVAyKmPSMlOQKHMoWnNAVLJZEEQNEckAxWAMiuX66M3knMnCbVaTZWWbjhPaUvyXzeInX0YVa4CmbacGjM6Y+yVX+HuhP0XOE1qxaMdl1Bl5+G6oAf3lpwg4/w99BzMqL3sfeR62tz4ZDNyfW0yLtxHkZSJRee6OE8uWhAnJy6F21N3kpuQhlqhwmFcIJYd6pD7MJ3rozagSM5CrVBSrX8DbD9o/MLvuSARUKtUKDNzkRvpApB8+AYm/k7o/bPEsXVfP+7/fuqNTgYAPGzb0cCpBwC7L/0gfdK2NHLiy07hRb4HcLNuyth/xg80dnmPxi7vlUss+jrGDGu6oth9T1YiHNJk6VPbaFZzAM1qFr+OxOjm618sQEEQyp1IBiqA5MM30LE0wn1Z/hQ9RXIWAMZe9nhsG4JMLif9bBy3Ju/Ac9dw6TxdOzM8944gfvExLr+/Eo9tQzGoYcmlPiE82nVJmn6YceEe9TYMBuBCj+Uk7b9aqE4AwM3/bcH5/9pi5GGLIjmLcx1/xayJC4mbzmH+dg3sx7xdKLYn5d5P5XL/1cW+N+v3fLAdUnzycKn3CjIu3sfQ3RqXL9rltxWfgp7DvysT6tmbkROfUvIP8TV38NpCzsftQanKw8rYmfcb/KjpkARBqEREMlABGNW1Iebb/UR/vRezgOqYB+YPqMp9mM6dMRvJiUtBpiUn62ZiofMsO+eXxzWqZ4t+dQsMaljmv65vS86dJOk4q3fqI9fXAaBqt/qkHLtdKBlQZuSQGnaHG+O2SNvUeSqy7zzG2NeBm59uRZmVl79wUDHjC3RtTPHaP7LM77vuuoGolSrufLuf+ytOv/QKhhVZp3oT6FRvgqbDEAShkhLJQAWg72JB/d3DSfn7Jg83nOXespPUXTOA25N3ULWXD9a9vFGm5xBW+7tC50m1B7RkheoQyOTyUtUhkKhBpqOF574RyGSyIrs9Nn9A8uEbxC04QuKW80UqHz5vzwCATEuOdS9vro3agP2oZujamZF+Nl7anxOXIhVlEgRBEF4OkQxUADnxKWhXMcCycz1MGjgS1fIXAJRpOejZ598IE1aFP6uJZ0rceoFq/Rrkf7/lAg5j3y60X8tYD2NPOxJWnMZmUP4a9Onn4zHysCXnbjK6NqZU7emFvnMVbk3ZWaT9svYM5D3OAEDHwgi1Ws2jnZcwrG0NgHkLV6K/3ENOXDK6dmY8WH0Gy051n+t9C4XNC+1Gx7qfFaoT8KqtCf8fJ26vZv67CdK2s3G72HbuG1RqJbWsm9HbbxZymZbGYhSEykgkAxVA5pUHxHy3H2QyUKup/k0nABwntOTm+K1om+hj2fn5b4hG9Wy42DNYGkD43/ECAK7ze3B76k4SVoWjVqrQszfDPaQvqcejif/1ODItOTK5DOepbZ87jgJ5DzO4MXYTaoUKtVqNYS1rqn/dAcgfWFj9yw5c6h2CWqXCLKA6VXt6vfA1Bc27kvAXSpWi0LasvDQ2RH7OuJY7qGJgz9ITHxAW/SeNqxe/xLUgCC+HSAYqgCot3ajS0q3o9la1qNKqlvS6YBAfQJO4L6Xvn6w7AOA0sVWhdox9HKjxfZci7RcMKgTQszWVBjA+qTzrGBQwrG2N554RT91v2bmeNB7iTZSryGTFqVEkZtxBrVZRz7Y1XT3/j8v3Q9l1cSYKVS5ymTa9fWfiZOENwJj11eji8TmRd7eTp8xmYKOFHL72K7FJ56hi5MCHAcHoaOmxMuxjdLX0uZt8nozcJLwdOhNUv+jyxkmZcayPnExKVgIqtYL2dT/Fy74jqdkPCD45gszcZJRqBc1qDKC529AXfs85igx2XJjByGZrCLvz7zoKl+8fooaVPxaG+csfN63Rn7+uLxXJgCC8YiIZEIRX7NL9w5joW/Fh02AAMnOTAXC28GZcy53IZXJiHkexLmIi41vvlc6rYmjPxDYHOHh1Ib/83Zv/tdyJtUkNfvm7N2fjdkhTE2OTzzE2cAsAPx3uygXLfXjYFe7RWXV6LN28puNg7kFmbjKzD7TFrWoA4TGbcK/WnLZ1xhaK7UkpWfdZdKRPse+tcfX3CXT7sMj27ee/JdDtQ4z0CleqTMqMx8LQsdB7FLUKBOHVE8nAG871p26aDkH4D3vzemw7/zVbzn6Jm3VT6ti0APJX5ltx6iOSMmORy7RJSLtR6Dxvh/zeHQdzD6oaV8fapAYAjlXqk5h+RzqugVN3adnihs49uPbgaKFkIEeRwa3EU6wK+1japlQpSEyPxsXCl9Xh48hVZlHb+q1ixxeYGdgwqe2hUr/fW4lhPEy/Q0+f70o+WBAEjRDJgCC8YlWNXRjfeh9XEv4i7M6fhF7/jY/eXsefERNp5PIejVx6k52Xzvgthdf619HSA/JrEmj/833B69LUKCigVqvRkuswsc3BYmePfNJiK5fvH2bflZ85E7uZ9/zmFNpf1p6BG4knuZt8ni92NpC2fbGzAZ+22kUVQztikiKl7UmZcVQxtC/1exEEoXyIZKCCSTl+m7s/hhZ6nv8qPVgXSfRXezHxdaDOyn4ApIbd4dakHahzFBjWqYbrvG5oGemV2M69307kD4oEHMa+LY0DUGbkcGPsZjIvJyDT06bGzC6YNnQqMbanxZFx4R43xm0h89L9QmMpKqqkzHiMdM3xcehCDcuGfLs3fyxIVl6adCM8divkuds/E7OFpjUG/PP9ZtrVGVdov76OMY5VvDhyM5i3XfP/P4tNOoeDeX0eZ8ZibmCLv/O7WBm5sD5yUpH2y9oz0Nb9Y9q6/9sLMWZ9NWklxTo2LdkUNY3HmXepYmDPsVsr8XboXOb3LAjCixHJgFCERZva0uMFtUrFjXFbqLX4XYzr2xH9xW7iFx0rsYSyRcc6VO3ljUwmI/dBGlEtfsG8VS20DHSIX3QMPXszai99j/Tz8VwbsR6fI2OQyZ9ejOhZcRh52OK1fyQn7L8o15/DyxKfcplt579Bhgw1Kt79p/u8s8ck1ob/D30dU3wcig74LC0Hcw9+Du0mDSD873gBgIGNFrI+YjLHbq1ApVZRxdCeEc1Wc/3BMQ5dW4Rcpo1MJqer57RirlB+DHRM6OHzDQv+ehe1WombdVP8nXu91GsKglCUSAZeotg5h1CrwWl8/o0z7XQM0V/uof6OYcT9coRHOy+hzlWia2uK67xu6FgYFTr/wbpIUk9ESzfm2B8OA+D4aQtU2Xnc+WYfaZFxqHMUVGnnLl2nPKWfjUeniiHG9fNL2Fbr34CrQ9eVmAwU1B4AUGbk5n+jVgPwaMclai/tDYBxfTt0qhiSfjYeEx+Hco+jIqpn24p6tq2K2d6aeratpdcFg/iAQvPyn6xJANDZY3KhdpwtfentN6tI+2MDN0vfmxvYSgMYn9S4+vsvfST/k+8FwMehywslP4IgvDiRDLxEVt29uNx/lXSTfrjxLFY98ufMW7/vh/1HbwEQv/gYcb8cxeX/2pW67bhfjqJfw5Lq33RCrVRxZdAakkNvSEsZF3i87wqxsw8X20aN7zphUkL3fG58aqFaAbplqBXwaMdFYuccJuduMq4/dUPLML8YUU58Crr/FCKC/PoDufGp8IwZjC8ShyAIgvBsIhl4iQxqWKJjYUja6RiMvO15vOcKXhP+6SUIjyVuwRGU6TmochTou1iU0FphSQevocrM48Ha/MFXysxcsm4mFkkGLNq6Y9HWvXzeUBkVrBeQdTOR66M3YhpQHR0LQ43EUln09/9Z0yEIgvAaEsnAS1a1pxcPN50j73Emxl526FgYocpRcOOTTdTf9iEGrlY83neVe0uOFzlXpi1HrVJLr1U5in9rEKjBdV43qaTx07xoz4CunSk5d//9BJ77HLUCDGpaoedgTurx21h2roeenRm5cckYuFYF8usP6NqZvvQ4BEEQhOKJZOAlswzy4O68heTeT5UeEahyFKBSo1PNGLVSxYM/Ioo9V9+pCpmX7qNWKFHlKEg6eA3LjvnLEldpXYt7v53A9aduyLS1yLmXikxLhq61SaE2XrRnwNjLjrzHGaSfj8e4vh0JK8OxeKJWQOTb86m7biB6toVv5lk3Hv57s7+XSnrkXRzH58+nt+hUl4SV4bh82YH08/HkPc7A2Ct/LMCdGfvRtTHFdnCjMsXxurr+4Bi7Ls0p9Dz/VToZ/Qebo77AxdKPkW+tAeBm4inWnRmPQpWLrVkdBvgvQE/bqFTtFMyGcK3auMR1BVKyEvj1WH9UKgUqtYIaVv686zMDLbkO1x8cY/HRflQ1zl9Zs6pxdYYELAPgjzPjORe3m2Y1B9Kx3vgX/REIgoBIBl46nSqGGPvYk3rsNrUWvQuAtqk+dsMDONd6EdpWRpg1rU56xN0i55o0dMLIy46owF/QtTPFqJ6ttM9+9FvEzDjA2XaLAdAy0MX1p3fgP8nAi5LJ5bj++A43Pt6EOleJgbs1bvO6A5D3KANFUiba5gZFzktYfYbkwzeQ6Wghk8twmtIGw1r5xYjsRzbl+sebiGw6D5muFq5zu0kzCTIvJUiDBEsbh/BiPOzaSY8XVGoVq8I+5oMmv+FYxZONUf/Hgau/lKq88pPtlIaxngWftNiKrpYBarWa308MJezOnzSp3hcAJwvvYpOk9/xmY6pvXerrCIJQMpEMvALFrfnvMC4Qh3GBRbb/t86A6w/vFNumXE8bl+ntyyfAEpg2dsH78Ogi29PCY7Ed0hgtA50i+1y+aA9PmemnZayH++9FfyZqtRpFchYWHeuUKY6KYufFWaBW08ljIgC3Ek+z6ez/8VmrPey/Mp+ouztQqHIwN7Cjv/98jPUsC51/MvoPrj84Lt1Qd12cDUDHeuPJU2az5dyXRD+KQKHKxdOuvXSd8hSTFIWxngWOVTwBaFpjAMuOf1CqZKCstOQ6aJH//45SnUeuMhsougiSIAgvn0gGhELk+jqknozmcv9V0qJDT2PRzh2LduU3OFEmk1F/e9F17UtSsOiQTlXjcovleTR06smiI+9LN+nTd9bT0Dm/Nyigel/auI8B4ODVhRy4soB3vEq/LsL+K/OxNq7Juz4zUKmV/Hq0P5fvH5aWMi5wPn4POy8UnVYI0Mt3JjWsGj7zOsmZ8VQx/HeKp4WhPUlZpasVcPn+QWbsa4GJnhWdPSbhYulX4jkKVS5zDrTnUUYMdW1bFlpjIC75AjP3t0JXy5C2dT4pdjqmIAjlQyQDQiFWXT2w6uqh6TDKpGDRIU2zNqmBsZ4ltxJP42zhzdm4Xf/2Ejw6zf4rP5Odl0aeMkd6Fl5aF+8dIFeRyYnb+c/1cxQZJKTdKJIM1LdrT327V9NjVOi6tm3xc3wHHS19rj44wm/HB/N/7Y+jr/PsBE1brsuktofIU2azJnwcUXe34+fUDYcqnnzZKQIDHRPiki+y8Mj7jGu5HSsj51f0jgShchHJgCCUI3+XXpyO2UB6TiLOFt4Y61mSp8xhZdgYPm21i2omrpyP38uha4uLnKsl00aNSnqdp8yWCg6pUdPff75U0vhpXrRnwNzQjqTMf8evPM6Mo4pBybUCnqxGWNv6LcwMbHiQfhOnKl4lngugo6WPn2M3jt5agZ9TNwx0/h37Ym9ejxqWDbmbdF4kA4LwkohkoJxlXU/UdAjCE17178PXsSt7Lv1IStY96RGBQpWDWq3CVL8aKrVS+nT/X5ZGzsQlX0CpUqBQ5XDx3gFpnX4P2zYcvv4r/RrOR0uuTXLWPeQyrSID6V60Z8CpijfpOY+ITTqHYxVPjt0KKVQr4Os9TRnTfAPmBraFzkvJuo+ZgQ0A8SmXSMq8K924t53/BjMDW5q7Dil0TlJmPAY6pujrGKNUKTgbtwtbU/d/2kvAVN8amUxGUmY80Y8j6ORRtE6CIAjlQyQD5cTKygp9QwNujNmo6VCE/9A3NMDKyuqVXMtItwouFr5ce3CUwY2XAGCgY0qr2qP4fl8LjPUsqWXdjOjHRaeT1rBqiFMVb77d+xZVDO1wqFJf2tfG/WO2n/+Wmfvzn5vraRvSt+HP5T6qXi6T07fhPELCRqNU5WJr6k5//wUApOUkkpmThKGueZHz/rqxjPPxe/MrKsp16e+/QDouLvkyjsX0EDxIv8mmqGmAGrVaRQ2rRnSo+ykAUXE7OHpzxT+9JWq61P8cG1O3cn2vgiD8S6ZWq9UlHyaURkxMDImJomegorGyssLJqeSqiAUiIiLw8/NjQuv90qj6N9V/ZzA8y7m43cSnXKZ93f+Vun21Ws2PhzoxruUO5LKnF6IqqydnWpRVbNI5Zh1ow5kzZ/D19S23mAThdSZ6BsqRk5NTmW46gqBpOlr63Hh4nEVH+kiLDj2Np30HPO07lKl9mUzGp612vUiIRfxxZjxXE/6mWc2B5dquIFRmIhkQhErMz/Ed/Bzf0XQYZfKe32xNhyAIb5zy67cTBEEQBOG1JHoGBOEp7qde03QIwksgfq+CUJRIBgThP6ysrDAwMCQk7CNNhyK8JAYGhq9shokgvA7EbAJBKEZpZ4bExsbyww8/cOTIERo1asT48eOpXr1sqwsKz+f27dvMmjWLsLAw3nrrLT799FMcHR1LdW5ZZ5gIwptOJAOC8BwyMzP5/vvvmTVrFtWqVWPu3Ll069YNmUwU2nmV1Go1mzZtYty4cTx48IAJEyYwadIkDA0NNR2aILxWRDIgCGWgVqvZsmUL48aN4969e4wfP57PP/9c3Hw0LCMjgxkzZjB79mxsbW356aef6Nq1q0jOBKGUxGwCQSila9eu0b59e7p37069evW4ePEi33zzjUgEKgAjIyO++eYbLly4QN26denWrRsdOnTg2jUxWFAQSkMkA4JQgoyMDCZPnoyHhwfXr19n27Zt7NixA1dXV02HJvyHm5sbO3fuZOvWrVy9ehUPDw8mT55MRkaGpkMThApNPCYQhKdQq9WsX7+eTz/9lMTERCZNmsSECRMwMDDQdGhCKWRlZTFz5ky+//57qlatyo8//kjPnj3FowNBKIboGRCEYly6dInWrVvTu3dv/Pz8uHTpEl988YVIBF4jBgYGTJ8+nUuXLuHr60uvXr1o06YNly9f1nRoglDhiGRAEJ6QmprKZ599hpeXFzExMezatYstW7aI6YKvsRo1arB161Z27tzJnTt38PT0ZPz48aSlpWk6NEGoMMRjAkEg/5HAmjVrGD9+PMnJyUydOpVPP/0UPT09TYcmlKPs7Gx++OEHvv32W8zNzZkzZw7vv/++eHQgVHqiZ0Co9M6dO0fz5s3p168fTZs25cqVK3z++eciEXgD6evrM2XKFK5cuUJAQAB9+/YlMDCQ8+fPazo0QdAokQwIlVZycjJjx47F19eXBw8esG/fPtavXy9WpqsEnJyc2LBhA/v27SMhIQEfHx/Gjh1LcnKypkMTBI0QjwmESkelUhESEsLEiRPJyMjgiy++YOzYsejq6mo6NEEDcnNz+emnn/jqq68wMjJi1qxZ9O/fH7lcfFYSKg/xf7vwRlMoFLRp04bff/8dgIiICJo1a8bgwYNp1aoVV69eZfz48SIRqMR0dXWZMGECV69epWXLlgwaNIi33nqLyMhIAJYtW0bbtm1RKBQajlQQXh6RDAhvtJ9++olDhw7h5OTEqFGjaNCgAampqRw+fJg1a9Zgb2+v6RCFCsLe3p61a9dy6NAhkpOTadCgAR999BFOTk4cOHCAefPmaTpEQXhpxGMC4Y118+ZN6tevT9OmTYmMjCQvL48vv/ySjz76CB0dHU2HJ1RgeXl5LFiwgC+++AI9PT28vb05duwYFy5coEaNGpoOTxDKnUgGhDeSWq2mUaNGREZGolAo6NChA3379uXtt98udZlboXKLjY3l77//ZvXq1ezevRttbW18fX05efKkmIoovHFEMiC8kRYvXszIkSOLbB86dCi//fabBiISXjdDhw5l2bJlRbYvWrSIESNGaCAiQXh5RDIgvJHu37/PrFmz8Pf3p2rVqlhaWmJpaYmtrS3a2tqaDk94DSgUCu7du8ejR4949OgRDx8+JCwsjIkTJ1KtWjVNhycI5UokAyWIiYkhMTFR02EIr4iVlZVYZ6ASEX/flYv4+3468RHpGWJiYqhTpw6ZmZmaDkV4RQwNDbl8+bL4B6MSiImJwb12HbKyxd93ZWGgb8iVq+LvuzgiGXiGxMREMjMzWbVqFXXq1NF0OMJLdvnyZfr160diYqL4x6ISSExMJCs7k3fdF1DV0FXT4Qgv2cPMG6y/Mlr8fT+FSAZKoU6dOvj6+mo6DEEQXoKqhq7Ym3hqOgxB0Cix6JAgCIIgVHIiGRAEQRCESk4kA89hzZo1eHt74+3tjbu7O5999tlLuU50dDQuLi7F7gsMDCQ0NPSlXDc0NLRQ26GhoQQGBr6Ua5XFhx9++MzFXrZt24aPjw/16tWjQ4cOhUaJy2Qy6Xfm7e0tqtMJT3U2YRPzw1szP7w1c8PeYvfNL1/KdZKyY5l90r/YfUujenAr+fhLue6t5OOF2r6VfJylUT1eyrXKYvPVz5jyl91T999NjWJRRCfmh7fm5/BWXE7cK+2b8ped9DubH96aLEXKqwj5jSLGDJRRfHw8EyZMICIiAmtra5RKJRcvXtR0WOWqIBEozwTg0aNHWFpaPvf5Bw4cIC8v76n7Hz9+zLBhwzh16hTOzs7Mnj2byZMnF1pgKCoq6rmvL1QOqTn32XPrWz7y24uxrhUqtZIHGVc1HVa5uv1PIlDDPKDc2szMe4yhjsVzn38j6W+U6mcXgtp58/9o6fw/alu2IiHjCkvP9mSKVTtp/5gGB577+oJIBsosISEBPT09zMzMANDS0sLT89/BR5s3b2bmzJnk5uZibW3NsmXLsLe3Z/r06dy4cYOYmBgSEhJo1qwZixYtQldXl5CQEBYsWEBeXh4mJiYsX76cmjVrljqm2NhYRo8eTXx8PAqFgmnTptGtWzeio6Np3rw5PXr04ODBg8hkMjZs2ICrqyu5ubkMHz6cEydOYGtri729Pa6urvTq1YvFixcDsGXLFsaOHUv16tXJyclh4MCBnDlzBnNzc7Zs2YKVldUz47p//z6rV68mJCSEzp078+233z7HTxwyMjKYMmUKu3btYsWKFcUec/PmTZydnXF2dgagXbt2fPXVV2K1QaFM0nMfoi3XRV/bBAC5TAsb47rS/ouJuzkS8wsKdS7GOlZ0q/0DZnq2HIyew6OsaFJy4kjPfYizmT9Bbt+jLdcl8v56TsQvR6XOQ0/LmO6152Jp4FLqmJKz49h+YwppuQmo1ApaOP+PelYdSMqOZWlUd+pZdeJm8lEA+tT7DUuD6ihUuWy9NoGY1DOY6FbDVM8GSwMX6lcNIix+JQCXEvcQ4DCUKvpOKFS5bLgylri0cxhom9LX43eMdJ6dvKflPuBswiYiEzZQ27I1batPKuNPO1+uMpP9t2cysP5KIhP+fOpxMuRkK1MByFakYqpr81zXE4onkoEy8vLyok6dOjg5OREYGEhgYCADBgzAyMiI69evM3/+fEJDQ9HX12ft2rV89tlnrF27FoCjR48SERGBubk53bt3Z8mSJYwePZpOnToxYMAAADZs2MCkSZNYv359qWMaPHgwc+bMwdvbm6SkJBo0aCB9qo+JiSEoKIgff/yRGTNmMGvWLJYsWcLixYtJT0/n0qVLpKSk4Ovri6urK3Xr1pWWWp0+fTqQ31MQFRXF8uXLcXd3Z/jw4SxZsoTPP/+8SCxZWVls2bKFkJAQYmNjee+999i6dav0uCM+Pp6OHTsW+z4++OADPv744yLbJ0+ezNixY5/Zs+Dm5kZ0dDQXLlzAw8ODdevWkZ6ezuPHj7GwyP/E4u/vj1Kp5P33339pj3aE15uNcT2qGrox62RDapg3obp5AD7V3kVXy5DEzFucjPudId4b0JHrc/bBZvbc/IredRcBcCcljI/89qKvbcaai0M4fW8VTew/oLZlK3xs3gXgwsMd7Lv1He/XW1LqmDZdHUf7mtOwM/YgKy+ZhREdqGHWBIDknDjcrdrS0XU6f8XM5+/YhXSrNZuw+BBylZmMbfgXOYpUfoloh6WBC9ZGtfC36w9AK5f8v4Fbyce5l3GRHu4/UtXQjS3XJnA6fjWBzkX/FvOUWVx6tIfI+xtIyYnH07or/TyWU0U/v95Has59VpzvV+z78LN5jwCHoUW277v9HQH2Q0rsWehaayYh5/uz99a35CozGez5R6H9CyM6olYr8bR+h7cciy5FLjybSAbKSC6Xs2PHDs6ePUtoaCgrVqxg0aJFhIeHs2/fPi5dukTjxo0BUCqVmJqaSud269ZNujENHjyYFStWMHr0aK5evcqUKVN4+PAhKpUKlUpV6njS09M5cuQIgwYNkrbl5eVx8+ZNrKysqFatmpQY+Pv7c/DgQQAOHz7M4MGDkcvlVKlShXfeeeeZ1/Hy8sLd3V1q58SJE8UeZ2Njg7OzM0uWLJF+Dk+ys7MrU3f9sWPHuHnzJj///PMzjzM3NyckJIRhw4ahUCgICgoCkJYejo2NxcHBgcTERIKCgrC1taVv376ljkOoHOQyOQPqh3Av/SK3k08QeX89p+JDGOW7mxtJf/Eg4xqLIzoDoEaFnpaxdG5dqw4Y6lQBwNemN5EJ62li/wEPM2+y//YwMvIeoUaFWl36v+8cZQbRKWFsvPKJtE2pzuNR9h2MdCww1qkqdfc7mHhzM+kIkH+D97PpjVwmx0DHnDqW7Z95HVujulQ1dJPaiUk9U+xxM054Y67vwDu1ZuFk6ldkv6meTZm66++khPEo6w6dXb8p8di/YhbwTq3ZuFkEcv1xKOuvjObjBqHIZXImNA7HTM+OjLxHrLowCBPdanhX617qOASRDDw3Ly8vvLy8GDlyJNbW1ly4cAG1Wk3Pnj1ZsGBBmdrq27cvwcHBNG/enPPnz9OlS5dSn6tWq9HV1SUyMrLI4Lro6Gj09fWl11paWigUz34u9zSlbWfTpk2sWLGCfv360blzZ/r374+f37//aJS1Z+DIkSNERkYWGkjp4uLCyZMnsbEp3E3Yrl072rXLf4Z4+vRpFi5cKCVjDg4OQP5ypH369OHkyZMiGRCeyta4HrbG9fC3G8CM454kZFxBjZp6VTsR5PZdmdpaf2U0PWr/RHXzJtxPv8zKCwNLf7JajZZch9F++4v8fSdlx6It15Ney2RaqNTKMsVW4Ml25M9op2+9pUQkrGf95TG4W7bGu1rPQms0lLVnIDrlFPfSLxQaSDn7pD8jfHdgomstbcvIe8SNpL/oVSf/31Y3i0AyrySRmfcYY10rzPTyBx4a6Vjiad2N2NQzIhkoIzGboIzi4uI4deqU9Prq1avk5uZib29PmzZt2Lp1K9HR0UD+J/Rz585Jx27dupWkpCRUKhUrVqygZcuWAKSkpEgrYi1ZUvruQwATExP8/PxYtGiRtC0iIoKSSk4EBgayevVq1Go1ycnJbN26VdpnampKampqmeIo0KpVK0JCQjh79iy+vr5MnDhR6raHf3sGivsq7hHBpEmTiI+PJzo6Wvq5RkdHF0kEIH88B0Bubi5ffvkln3zyCQBJSUlkZ2cD+Y8xtm3bVmichyAUSMm5R2xqhPQ6MfMmSnUuZnq2uFZ5myuP9pKUHQuAUpXH/fRL0rGXH+0lKy8ZlVpFZMJ6apg3BSBbkYaZnj0Ap++tKlM8etrG2Bt7cir+37EycWnnSvz7rmEewNkHm1Cr1WQpUrj86N+R93paJuQo0ssUR4GaVd7iXfefGdPgAHbG9dl76xvmnW7BuQf5/34U9AwU91XcI4LmTmOY1CSS8Y3DGN84DIDxjcMKJQIABtrmKNUK4tPOA3A37SwymRZGOpZk5SWTp8r/+85TZnHl0b5C4zyE0hE9A2WkUCiYOnUqMTExGBgYIJPJCAkJoVq1alSrVo2FCxfSs2dPcnNzUSqVfPTRR9KNJyAggK5du0oDCIcNGwbA7NmzadGiBVZWVnTu3LnMMa1evZrRo0ezePFilEolTk5O7Ny585nnjBgxgjNnzuDu7o6NjQ2+vr7SoMh33nmH7t274+Pjw8cff0z16tXLHJORkREDBgxgwIAB3L17lxs3bpS5jZIU9DIUPHaYNGkSp06dIjs7mx49evDpp58CcOXKFYYNG4ZcLicvL48uXbowZMiQco9HeP2p1Er2355JSk4c2nJ9ZDIZPd1/xli3Ksa6VeniOoM1Fz9Eqc5DrVbSyG6QdONxMm3AqouDpQGEDW3zPyG3rzGVZWd7Yqhjgbtl6zLH9G6dBWy/PoWweytRq5WY6dkzoP7KZ57jb9efuPRz/HT6LYx1rbEzro++dn4vWV2r9qy+OIQFZ9rQxH4IVfTLvjSvrpYhPjbv4mPzLik58TzKii5zGyUp6GUY0+AAcpkW77rPZ+PVcUB+70Vv91+QyWQ8zLzBlusTkCFHqc7D3bINfjbvl3s8bzpRtfAZIiIi8PPz48yZMy+8HHHBYLyC/2qaWq0mMzMTIyMj0tLSeOutt1i4cCEBAeU33eh1U56/b6HiK/h9j/Ld88LLER+MngP8OyhP09RqNXmqLHS1DMlRpLMk6h2C3GbgbNZQ06FpTFzaORZGtBd/308hegYqKYVCQWBgIHl5eWRnZzNw4MBKnQgIwptEpVaw9GwPlKo8FKocfG16VepEQCiZSAZekYrSI1BAR0eH06dPazoMQXgjVJQegQJach1G+e7WdBjCa0QMIBQEQRCESk4kA2+QZ03be9K2bduYNm1auVwzPT2d7t274+bmhoeHB8eOHSv2uODgYCwsLKTaAMXNHBCEyu5ZU/OedDlxLwduzyqXa+YoM1h9cQg/hjVl3ukW3EkJe+qxB27P4odTAfxwKqDQDAfIr+kw73QgP4e3ZH54a1T/rKdwMHoOc041ZspfdtJMDKHiEY8J3iB2dnbs2rWrxOOCgoKkRXle1OzZs3F2dmbTpk1ERETQq1cvrl27hlxeNM8MCgoiODi4XK4rCG8iUz0bBtYvefphHat21HliXf4XcSR2IeZ6DvStt4y4tHP8cWkE4/yPIpcV/hu+lXSM60l/MbZhKHmqLBaeaY9rleZYGrgQmxrJkbuL+NB7E4Y6FqTnJiIjf10EN4sW+Nm8x29RYt5/RSZ6Bl5D69ato1atWvj5+TF16lRpQZ4nqxxGR0fj7OzM//73P7y8vPD29pam9wUHBxdasfBFrF+/nuHDhwPg6+uLlZUV4eHh5dK2ILypzj3Yyo9hzfjlTDv2354pLbrzZCXD/O8bsuvGdKka36Os2wBE3F/HhidWJXwRFx7uwN8uvzfC3sQTIx0L4tLOFjnufOIOfG16oy3XxUDbDI+qnbn4MH8K8/G432juOEZaUthY10paJMnJ1A9zfYdyiVV4eUQy8JpJSEjgk08+4dChQ5w5c4b09KcvHlJQl+Ds2bP07t2bWbNK7lbs2LFjoVK/BV8FtRP+KzY2VioOBODk5ERsbPFdgbt378bLy4s2bdoUWrhJECqT9NyH7Lz5BUO8/uQjv73kKjOeemxB7YExDQ7gad2Vv2MXltj+ivP9CpXzLfhaf6X4R3MpOfGY6/17szbTtyclJ77ocdlxhY/T+/e4h5nXeZB5jSWRXfnlTPsijxCEik88JnjNnDx5kiZNmkjL6w4ePJgtW7YUe+zT6hI8S2keMzyPLl268N5776Gvr8+hQ4fo1q0bV69excTE5KVcTxAqqpjUMziZ+klL6Pra9OZS4p5ij31a7YFnKc1jhvKmUit5mHmdIV4byFGms/RsD6oaupVrmWTh5RLJwBvseeoSdOzYkfj4op8KPD09CQkJKbLd0dGRO3fuSEWMYmJicHR0LHLckxUHW7ZsiZ2dHdeuXStUt0AQhMKep/bAivP9SM25X2S7jXFd3nUvWvDLTM+O5Jy7UqGilOw4KVEpdJy+Pck5d6XXKTn/HmemZ0+9qp3RkutgKK9CrSotiEs7K5KB14hIBl4zjRo1YsSIEcTFxWFvb8+KFeXbHVfWnoGePXvy66+/MnfuXCIiInj48CENGjQoclx8fDx2dvn/cJw/f56YmBhq1KhRLjELwuvE0dSXrdcnkZJzDzM9WyLvl75ceWmUtWfAw6oTYfGr6OT6JXFp58jIe4S9iVexx+27PQM/m/fIU2Vx/uF2qYywp3VXbiT9Tf2qXchTZXM75SStXcaXy/sRXg2RDLxmbGxs+OGHH2jRogXGxsa0aNFCqimgCePHj6d///64ubmhq6tLcHCwNJNg6NCh0syFBQsWsHXrVrS1tdHV1SUkJIQqVapoLG5B0BQTXWs61pjGsrPvoqtlSA3zplLdAE14y3EU66+M4cewpmjJdOhR+ydpJsGmq59Sx7ItdazaUbNKM2omv8W8080BaOYwHEsDFwC8rLtxNzWSn043R4YMT+tuuFkEArD/9iwi7q8jPfcBiyO7UNWgJkO9N2rirQrPIGoTPENFXas+LS1Netb+1Vdfcffu3TJXOxSKqqi/b+HlKM/aBGWVo0hHT9sYgEPRP5KSe49utWa/0hgqG1Gb4NlEz8BraM6cOWzdupXc3Fxq1qzJ0qVLNR2SIAhlcOTuIi4n7kWpzsNC35nutX/QdEhCJSeSgdfQl19+yZdffqnpMARBeE6tXcaLZ+pChSLWGRAEQRCESk4kA4IkMDCQ0NBQjVx79+7d+Pj44O3tTYMGDThx4oRG4hCEN8XSqB7cSj7+yq+rUqtYHNGF+eGt+Tm8JWsvDiNbkQbAnZTTLI7ozLzTgcw7Hcixu2KsU0UhHhMIFcKQIUM4cOAAdevWZceOHXz88ceixLIgvIbkMjmDPNegr50/yHnXjekciV1Em+oT0Nc24d06C7A0cCFbkcbCiPa4mDV+5QM4haJEMlABZWZm0rdvX27duoVKpaJjx47MnDmTffv2MW3aNHJyctDW1mbRokXSnH6ZTMZ3333H+vXrycrKYvXq1cydO5czZ87g7OzMli1b0NPTY9CgQRgYGBAZGcmjR4/o2bMnM2bMKBJDbGwso0ePJj4+HoVCwbRp0+jWrRsJCQm8//77PH78mLy8PEaMGMGYMWNe+D3L5XJSUlIASElJwd7e/oXbFISKIFeZyZ+XR5OUHYMaFbUsWtK+xlSuPw7lYPQcFOoc5DJtgty+x+Gf+f1T/rKjbfXJnH+4HYUqm3fdF3D87m/EpZ/DXM+Bfh6/oy3XY8OVT9CR63Mv/QKZiiTqWXWiXY3Pi8SQnB3H9htTSMtNQKVW0ML5f9Sz6kB67kPWXR5FZl4SKrUCf7v+NLEf8sLvuSARUKlV5Koy0dUyBKCakXuhY6wMapKcEyeSgQpAJAMV0J49e7C2tmbz5s0AJCUlAdCwYUOOHz+OXC4nPDyckSNHFvr07OjoSEREBHPmzKFt27acOHECNzc32rVrx8aNG+nTpw+QP6Xqr7/+AuDtt99mx44ddO7cuVAMgwcPZs6cOXh7e5OUlESDBg0IDAxk9erVtGnThsmTJxeK7UnPKqX8wQcfFFu+eNWqVQQFBWFgYIBarX5qKWRBeN1cfxyKsa4V/Tx+ByArLxnIX154mM825DI5d9POsu36JEb57pbOM9OzY7TfPo7ELiL43PsM99mOlWENlp97n4sPd+JVLb8KYHz6eWne/m9R3bnyaD/ulm0KxbDp6jja15yGnbEHWXnJLIzoQA2zJkQlbMK1yts0dxpTKLYnPaussp/NewQ4DC123+9ne3Ev/SLVjNzpUP+LIvsTM29yNy2KHrXnPuOnJ7wqIhmogLy8vJg4cSLjx4+nRYsWtGuXX6r0/v379OvXjzt37qCtrc2VK1cKnffuu+8C4OPjg5ubG25u+cuL+vr6cuvWLem4Pn36SEsV9+3bl0OHDhVKBtLT0zly5EihyoZ5eXncvHmTRo0aMWTIEDIzM2nVqpVU++BJdnZ2REVFlfr9KhQKvv/+ew4cOICXlxe//fYbQ4cOZd++faVuQxAqKhvjuuy9/S27b35FDfOm0mI8abkP+fPKGJKz7yKXaZGYebPQeR5V8/8m7Yw9sDSogZVhjX9e1+dxdox0nJd1N3Tk+X/P3tbduZV0rFAykKPMIDoljI1PVDlUqvN4lH0HR1MfNl39lFxlFjWrNCt2+WBTPRvGNDhQ5vf9gdefqNRK9t76hlNxwbzt9JG0LzPvMasvDiHI7TuMdC2f0YrwqohkoAKqWbMm4eHh7N+/n5CQEObNm8fevXsZNWoUgwYNYuDAgaSlpWFqWnjVMj29/HXMtbS0pO8LXpemLkEBtVqNrq4ukZGRUhnSJx05coQ9e/YwY8YM1q5dy6+//lpof1l7BqKionj8+DFeXvldpH379mXs2LGljlcQKjJLAxdG+e7mRtLfRCas53jcUgZ7rmXb9cn42vTC16YXOYp0vjpWq9B5BXUJZDIttOW60na5TAuVuvR/z6jVaMl1GO23v9i/52HeW7iWdJi/YuZz7sEW3qlVuLrp8/YMFMTqa9ObPy6NlJKBHEU6wef70chukJTwCJonkoEK6O7du1hYWNCzZ08CAgKoV68ekP8s3cnJCaDIDbgs/vjjD4YPHw7A2rVrmTp1aqH9JiYm+Pn5sWjRIkaNGgXkP1rw8fHhzp072Nvb079/f2rWrMlHH31UpP2y9gw4ODhw48YNYmNjcXR0ZM+ePdJ7FoTXXUpOPAba5nhU7YyTaQPmhbcAIFuZirle/tiYsHsrn7v9cw+20tCu3z/fbyHQuXAiradtjL2xJ6fiV9DYfhCQvxqfnXF9knPuYqprg0+1nljoO7P9RtHxBmXtGcjIewSAkY4larWaCw93UM2oNgB5yixCLgygnlUHKRahYhDJQAV0/vx5Jk2ahEwmQ6VSsWDBAgC++eYbhg4dipmZmfRI4Hl4e3sTGBgoDSD873gBgNWrVzN69GgWL16MUqnEycmJnTt3cvjwYX744Qe0tbWRy+XMmjWrmCuUTUG9hfbt26OtrY2RkRHLli174XYFoSK4n36Ffbe/A0CNmi6u3wLQxmUim699hp62CfWrdnnu9m2N67Esqqc0gPC/4wUA3q2zgO3XpxB2byVqtRIzPXsG1F/JreRjHI39FblMC5lMTvvqU4u5Qtmk5yay4crHKNUKQI21YS06u34DwJn7fxCTcppsRSrnHmwFoLnTGDytu77wdYUXI2oTPMObuFb9oEGDCAwMLDQeQMj3Jv6+hafTZG2C8rLhyifUMG+Cr01vTYdS4YnaBM8mFh0SBEEQhEpOPCaoZIKDgzUdgiAI5aSn+0+aDkF4Q4ieAUEQBEGo5EQyUMGFhoYWO5f/VQkODsbCwqLQVMGjR4/i4eGBm5sb3bt3Jz09vdTtXb9+HUNDQ6ZPn16mOD788MNC06KioqLw9vYudqqUIFRUt5KPszSqh8auH3F/Hd8cq1toqmB0yinmnW7Bj2FNWX1xCDnKjBLbuZMSxsKIjkz724WD0XNKde1n1SzIykvm97O9+Opo7SI/n9P3VvPDqQCN/twqA5EMCCUKCgpi165dAKhUKgYNGkRISAjXr1/H2dmZ2bNnl6odtVrNRx99RFBQUJmuf+DAAfLy8gpt8/b2LtP0RUEQ8rlbtmVg/VVA/g1645Vx9HSfx//8j2Gu58CR2IUltmGqZ0dXt+95y3Fkqa9bULNgTIMDfNzgEGZ6dhyJXQSAllyXQOdP6FVnQZHzGtr2pVvt0iUcwvMTycAr9MUXXzBt2jTp9fHjx2nUqBEAM2fOpGHDhnh6etKxY0cSExOLnB8cHFxoFsD06dOlT9jZ2dmMGTMGf39/vLy8Cl2nPIWHh2NlZSWNxh0+fDjr168v1bkLFy7krbfewt3dveSD/5GRkcGUKVP44YcfniteQXhZDkTP5sDtf6fW3kk5zaKITgD8HbOAhREd+Dm8FSvO95Pm3j8p4v46NjyxKuDB6DnSp+w8VTbbr09hYURH5oe3LnSd8hSXdhYjHQtpNoW/XT8uPNxR4nlV9B2wN/FELtMq0/X+W7OgoF9PV8uQGuYB6GoZlak9ofyIZOAV6tevH2vWrJFer1y5kv79+wMwdOhQTp8+zblz52jZsiUzZ84sU9vff/89tWrVIiwsjIiICMLDw9m7d2+R47Zt24a3t3exX8ePl1zuNDY2FmdnZ+m1k5MTsbGxJZ53584dVq5cycSJE8v0viZPnszYsWOxtBRLlgoVi7d1D84+2CK9jkrYiHe1/K7sBrZ9GOW7m48bHKSGeVP+jvmlTG3/HbMAK8MajPLdxUd+e4lLP8f1x6FFjrucuJf54a2L/bqTUnLVz5SceMz1/y0KZqZnT0pOfJliLavfz/ZixvH6JGbe5C2noouWCZohZhO8Qm5ublStWpXjx4/TsGFDNm/ezNdffw3k9xLMmDGD1NRUsrOzcXV1LVPbO3fuJCMjQ1qsJz09natXr0p1DQoEBQWVuZu+PIwcOZK5c+eiq6tb8sH/OHbsGDdv3uTnn39+iZEJwvOxMqyBkY4ld1JO42DizaXE3bSuPh6AOynh/B07n2xFOgpVDpYGLmVq++rjg+QqMwm/txbIr3z4MPOGVNegQB2rdtSxaldMCxXXs2oWCJojkoFXbMCAAaxatYqHDx/SsGFDrKysyMnJYcCAAZw8eZLatWuzffv2YrvFtbW1UalU0uvs7Gyp4JBarSYkJEQqafw027Zte+ojhIULFxIQULRQyZMcHR25c+eO9DomJgZHR8dnngNw8uRJ3n//fQCSk5Ol+L///vunnnPkyBEiIyNxcXGRtrm4uHDy5ElsbGxKvKYgvGw+Nj2JerCJjLxH2Jt4YaRjiUKVw4arYxnhs52qhq5cTtzHsbtFlw+Xy7RR8+/fs0KVI9UjUKvV9HT/WSpp/DSXE/dyILr4MTtBbjNwNmv4zPPN9OxIzo6TXqfkxGGmZ/fMc8pDcTULBM0SycAr1rt3b77++mvi4uKkRwTZ2dmoVCpsbW1RKpVPXYq3Ro0aREVFoVAoyM7OZufOnfTokd8t2blzZ+bOncuKFSvQ1tYmLi4OLS2tIjfNF+0ZaNCgAQ8fPiQiIgJfX19+/fVXevbsKe13d3fn4MGD2NvbFzrv8ePH0vcF4xwK/rtgwQLi4uKYMWNGoXMmTZrEpEmTpNcymYzo6Ojnjl0Qylv9qkEcvvMTqTn38KmW/3egUOWgVqsw0a2GSq3kzP21xZ5bRd+Je+kXUaoVKFQ5XH18kHpW+bN23C1bc/zuEnq4z0NLpk1Kzj3kMi1MdK0LtfGiPQP2Jl5k5D0iLu0c9iaehMWvwsOqk7R/bthbfOD1J2Z6tqVu80Tc76Tm3KddjcJ1Dp5Vs0DQPJEMvGIWFhY0atSIQ4cOsW7dOgDMzMz47LPP8PT0xNrampYtW3Ly5Mki5wYEBNCwYUPq1q2Lo6MjPj4+0r7JkyczefJkaZuRkRHBwcHl/glaLpezfPly+vfvT25uLh4eHoSEhADw8OFDHj16hIWFRZnavHz5MtWrVy/XOAXhVTDUqYKDiQ+3ko/xXt3FAOhrm9LMcQTzw1thpGtFTfOmxKZGFDnX2awhDiZezDsdiJmeHbbGHtK+5k5j2HdrBr+caQuArtyQHu5ziyQDL0ouk9O99tx/agnkYW1Ym3fd8x/LZeQ+IlORhKG2eZHz7qdfYsX5/uQo86cGht9bS3+PYOxM6vMw8zpV9J2KnPOsmgUAc8OakalIJkeRzswTfvx/e3ceFlX1P3D8PcO+jiyCAiIQCK6AWS5okbmlVpqmldnXLZdcUltcsjK/lpWV4r4vuaQ/NTU1t1wTt0xUFBdQBAWUfYdhmJnfH5NjfAdFcGCAOa/n4XmYu5z7Gc5c5txzz/2cFz3HismMqpCYm+AxRK56zRMMR48efaLMhTt37iQyMlJnFsSydOzYkZ07d2JnZ1fu+CQSCfr6CIv6Ni61YW6C8jp/bzO3Mk89UebCqNR93M+7xksNx5frGCsvvsm7TVdjYWpbsSBLcSvzJIdv/8iwoG0VLkPMTfB44mkC4bGsrKw4duxYiaRDj/L666+XuyEAcPjw4XI3BB4kHXJ1dS338QTBWJlKLbmddapE0qFHaeLcrdwNAYChgVv02hD4K2kDv0VPwcqsjt7KFHSJ2wTCY/Xv35/+/avfjGgi6ZAglF8Ll9dr3HTBz9UfwHP1Bxg6jFpP9AwIgiAIgpETPQNP4OrVq4YOQagCop6NU0p+jKFDEKqAqOfHE42Bx3B2dsba2pp33y37/ppQO1hbW+Ps7GzoMIQq4OzsjJWlNVuujTF0KEIVsbIU5/ejiKcJyhAfH1/qPAGGolQqmThxIhEREaxZswYfHx9Dh1QuN2/eZPDgwQQHB/PTTz9hYlK+3OaVzdnZGU9P3ceihNpJnN/6Jc7vGkwt1CgTJkxQS6VS9d69ew0dSoXt3btXLZVK1RMnTjR0KIJQrYjzWzAU0RioQZYtW6YG1PPmzTN0KE8tLCxMDaiXL19u6FAEoVoQ57dgSOI2QQ1x5MgRunTpwrBhw1i0aBESiaTsnaoxtVrNqFGjWLlyJQcPHiQ0NNTQIQmCwYjzWzA00RioAaKjo2ndujUtW7Zk7969mJmZGTokvVAoFLzyyitERERw5syZcs/UKAi1gTi/hepANAaquYyMDNq0aQNoZv5zcHAwcET69eD9SSQSTp06VevenyA8jji/hepCJB2qxhQKBW+++SYpKSns3r27Vp5IDg4O7N69m+TkZPr164dCoTB0SIJQJcT5LVQnojFQTanVaj788EOOHTvGtm3b8PPzM3RIlcbPz4+tW7dy9OhRxo8fb+hwBKHSifNbqHYMNXJReLx58+apAfWyZcsMHUqVWbp0qRpQz58/39ChCEKlEue3UN2IxkA19OA53QkTJhg6lCo3fvx4tVQqVe/bt8/QoQhCpRDntzi/qyMxgLCaiYqKom3btrRv357ffvut2mXwqmxKpZLXXnuNEydOcPr0aRo3bmzokARBb8T5Lc7v6ko0BqqR1NRUWrdujbW1NeHh4djb2xs6JIPIzs6mXbt2FBQUcObMGZFLXKgVxPmtIc7v6kkMIKwm5HI5b7zxBjk5Oezatcto/1EA2Nvbs2vXLrKzs+nTpw9FRUWGDkkQnoo4vx8S53f1JBoD1YD6n2xdZ86cYfv27Xh5eRk6JIPz9vZm+/btnD59mpEjRyI6sISaSpzfusT5Xf2IxkA18MMPP7B69WpWrFhBSEiIocOpNtq3b8/y5ctZvXo1P/74o6HDEYQKEed36cT5Xc0YbuyioFar1Tt37lRLJBL1lClTDB1KtTV58mS1RCJR79y509ChCEK5iPO7bOL8rh7EAEID6NatG4MHD8bf35/27dvTtWtXtmzZglQqOmpKo1Kp6Nu3LwcOHCA8PJyrV6+ydu1a9u7da+jQBEGHOL/LR5zf1YP4dFaxe/fusX//fjIzM3nttddo1KgRP//8s/hH8RhSqZR169bh5+fHq6++SmZmJvv27eP+/fuGDk0QShDnd/mJ87t6EJ/QKnbixAkAli5dSnFxMWvWrKGwsNDAUVV/hYWFrF27FoVCwfLly4GHf0tBqC7E+V0x4vw2PNEYqGLHjx/H1taWK1eu8Oyzz/Lcc88xbtw4Q4dV7Y0bN47nn3+eVq1acfnyZWxsbDh+/LihwxKEEsT5XTHi/DY8MWagirm5uZGUlARAgwYNGD16NMOHD6+VM5bpU0ZGBsuWLWPhwoXcuXMH0PwtExISDByZIDwkzu+KEee34YnGQBWztrbGxcWF2bNn07t3b0xNTQ0dUo1SXFzM9u3b+eSTT0hOTiY/P9/QIQmClji/n444vw1HNAaqmFqtRiKRGDqMWkH8LYXqRnwm9Uf8LauWaAwIgiAIgpGr9D6s+Ph4UlNTK/swwiM4Ozvj6elZZccT9W1Yor6NS1XUt6jj6knvdV+ZGY3i4uLUltZWakD8GOjH0tpKHRcXV5nVXKK+ra2sDf6ejfnH2spa1LcR/VR2fcfFxamtLEUdV8cfK0v91n2l9gykpqZSmF+A7/w+WPmJaSqrWkF0KjFjt5GamlolV4upqankF+Tz2bDlNKzvX+nHE0qKS7rO1yveF/VtJKqivlNTUykozKeP73ycrfwq5RhC+aUWRLMtZqxe675Khrpa+Tlj29ytKg4lVAMN6/vTqGGQocMQqoio79rP2coPN9vmhg5DqEQi6ZAgCIIgGDnRGBAEQRAEI1crGwNF97K5OnB9mdulH7hG/OzDejmmMk/O9WGbiAgJ40LHhWT/Ff/IbeNnH+Z8SBjnQ8K4t/asXo5f26VmJjFpbp8ytwu/8DurdszUyzHzC3P5fOEABkwNYtAXrYmMPv3Y7e/ej6HrB66s3vmNzroDpzYROsyeiGt/6qybvXYsocPs9RJzbSHqW3ggu+ge668OLHO7a+kHOBw/Wy/HlCvz2HR9GGERISy80JH47L8eue3h+NmEnQ8h7HwIZ++t1cvxDaFWpscyr2dP43XvlrmdY5cAHLsE6OWYiYvDsXCX4b/iLXIjE7kxcgvBf45F8j+zlWWFx5J1LIagI6NRFSi49MpS6rzoi6WXo17iqK2c69Tnu/HbytwuJKg7IUHd9XLMzfvDcHVqwH9Hb+BG3AWmL/kP67+OKHUGOrVazdwNH9Eu8BWddRnZKfx2dCVNfJ7TWXcu6gjFSoVe4q1NRH0LD9ib1+PdxuvK3C7AsQsBjl30cszwxMXILNx5y38FibmRbLkxkrHBfyKVlPwsxGaFE5N1jNFBR1CoClh66RV867yIo6WXXuKoSjW6ZyB152Ui2s/jUrclxH93iPOt5wBQeCejxO9/P/8Tt6fv42KnRVzsvJiC2DQAkjdHEDN+u15iSdsdhevAVgDYNnfDzMGa3IuJpWx3hbr9gpGam2Iqs8KpZ1PSfo/SSwy1weGz23j3s2CGz3iBFdtn0H9SMwCSUuNK/v5pUxZunsLQ6e0Y+lUId+/fBGBv+AZmrRqpl1iOntvBqy8OAaBRwyBkdk5cv32+1G13HFlOC792eNZrpLNu3sZPeL/PdMxMLUosL5DnsXL7DD7o97Ve4q2JRH0LD1xO3cm8iPYsudSNQ/HfMed8awAyCu+U+P2nv59n3+3pLLrYicUXO5NWEAtARPJmtseM10ssUWm7aeWq6Y1ws22OtZkDibkXdba7krab4Lr9MJWaY2Uqo6lTT6LSftdLDFWtxvYMFKXkcnv6XprvGY6Fm4zYL/Y+etuELBy6+OM1vRsJ84+TuDicZ75/7bHlXx24nqJ7OTrLrRu74jfvDZ3l8sQszN3raF9buMsoSsyG4P+JJTELh84PH8OycJNREJPy2FiMRXpWMgs2T2bJZ0dxcXRn/qZJj9z2fvod2gV2Z3T/WWz4/Uc27Q/j4/fmPbb8SXP7kJp1T2f5Mx5NmTp0mc7y5PQE6jk10L52dWxAckYCjWlVYrt7afEcOL2JeZ/uY/2eH0qsO/73b9hY2xPYKESn/OXbptOn0yhktk6Pjbu2EvUtPJBblMLe29MZ3nwPMgs39sZ+8chts4oS8HfoQjev6RxPmE944mJee+b7x5a//upAcop0Pwuu1o15w0/3c5QlT6SOubv2tczCneyiRP73H3pWUSL+Dp3/tZ0bKQUxj42luqqxjYHc83exe7YBFm4yAFz6B5Ox/1qp25rVtUXWzhsA2yAPsk7Elln+k9xmEPQr6tZfNPV5HhdHzUn4Ssi7nIjYU+q2DvYuBAd0ACDA+1n+vnqszPKfpNu5Iuasm8CY/rMwMzUvsTwnL4N1e2bz08e7dPaJjD5NYkos497Rzz3OmkjUt/DA3dzzNLB7FpmF5hH0YJf+XMvYX+q2tmZ18Za1A8DDNojYrBNllv8ktxmMXY1tDJSH1OJfb9NEglqpKnOf8vYMWLjJKErIxMq3LgDyhCzM3XQHCZm7yZDfzdS+lidmYf5Pg0Z4cuZmltrfpRITlMriMvcp75Wii6M799Lu0LC+piv4fvodXBzcdbaLuvUXM5YNBSA3PwuAIoWctoHdSMlIYNhX7QFIz7rPjGWDmThwLvFJN4iOv6TtCgfoP6kZi6YewknmWuZ7MTaivoUHTKUPb79IMEGlVpa5T3l7BmQWbmQWJVDXyheALHkC9ua6uXJk5m5kyu9qX2fJE5GVsl1NUGMbA7bB7tyavAt5UjYW9e1J2XJBr+WXt2fAsUcT7q87h9dXr5AbmYgiPQ/bQN0PhVOPJsR/+wcubwWjKlCQtusKTX55T19h12iNfVrx0/rxpGQkUtfBjf0nN+q1/PJeKb747OvsOraKMW99y424C2TlpOLv1VJnu13zHj458mBk+eDXpwKwY84t7boPv+/OoNemaK5wg2FA94nadaHD7Nn83eVyxVfTifo2rvp+HHfbYHbdmky2PAl7i/pcSNmi1/LL2zPQxLEH5+6v4xWvr0jMjSRPkY6bbaDudk49+CP+W4Jd3kKhKuBK2i7ea/KLvsKuUjW2MWDuYkfDL7oS9eYaTGzMsW/nhYmdRdk7VhL3USFEj/uViJAwJOYm+M7prX2S4ObHO3Ho4o9jlwBk7X2QtffhQugCANxGtBVPEvzDSebKB/2+ZsIPPbCysCXYvwO2VoZ7BOutbh/y9YrhDJgahJmpOZMHL9GOLP9+zRi9jmQ3RqK+hQfszF3o2vAL1kS9ibmJDV727bAwsTNYPCHuo/g1ehxhESGYSMzp7TtH+yTBzpsf4++geXLBR9YeH1l7FlwIBaCt24ga+SQBVPIUxufPn+fZZ5+l+b4RlZKOWJkrx8RW0wC4M+coRUnZZQ4MNCa5kYlEdlvK33//TcuWulc4+vagvpd9frzC6WnzC3OwttT8E1i761tSMhLLHCgmaNyIu8Dw/74g6ttIVEV9P6jjEc33VXo6YrkyFwsTWwCO3plDdlFSmQMDjVVibiRLI7vpte5rbM8AQOKScNL3X0etUGLZ0AGfH143dEjCU9q8fx4nLvxOcXERbnW9+eQ/CwwdklCJRH0LD4QnLuF6+n6UagUOlg153eeHsncS9KZGNwYafNyRBh93NHQYgh4Nfv0zBr/+maHDEKqIqG/hgY4NPqZjg48NHYbRqtFJhwRBEARBeHo1umegslzpuxqPiaHa3ARVRZGeT8y4bRTGZSAxN8E20B2fWT1LPhop6F2JUd9VTF5UwLxfPuXijROYmpjxQsvXGNJrWpXHYUwMVd8qlYox33ZGrihEpVLiWa8Rnw5agI0BB03WRquv9CXUY6I2F0FVyVeksy1mHBmFcZhIzHG3DaSnzyxMpRao1Er2xn7B7ezTKNVFBLn04wX3sVUaX1nEt0x1IgH3MR2wb+OFWqUiesw27q0+g9tI3WxmQu2weMtnOMpcWP91BKDJyifUTlKplNkTtmu//BdunsKm/WEM7fW5gSMT9ENCB/cxeNm3QaVWsS16DGfurSbEbSR/399AjuI+owIPoFQVserKG3jZtcHTXnf+CkOp1o0BZUER0WO2IY/LQK1W49DRj4afdSHzWAx3Zh9BVVSMxFSKz6ye2AZqkoOccv8Sz8kvk7Y7ClWhAt8FfUhadoq8yCQsPGT4r3wbqYUpMeO3I7U0Je/yPYoz8nHs2YSGUzrrxCBPyCJ22h6K7uegLlbhMSEUp1caU5SSS/QHWynOLEBdrMR1YCvqD2nzVO/XzMEaszZeAEikUmxbuCFPzHqqMmuSQnk+M1cMIynlNiq1ijbNuzCi7wz+unKIVTu/RqEowsTEhAnvziHgn+e/Q4fZ8/4bX3L03A7kRQVMe38FWw4u5EbcBVydGjBz9C+Ym1kwa9VILMysiL5zkezcdF58thfD+0zXiSE5/S5hGz8mNTMJpVLJf16dRIeWr5Kelcx/lw8hOy8DpVLBay8O4Y2Xny4nfn5hLsfO7WTz9w/npnCUuTxVmTWJsdU3oG0IqFQqCuX5WFnYPHWZ1VWRsoBt0WPIkMehVqvxc+hIl4afEZN5jCN3ZlOsKkIqMaWnzyzc/3mG/8tT7rzsOZmotN0oVIX08V3AqaRlJOVFIrPw4G3/lZhKLdgeMx5TqSX38i6TX5xBE8eedG44RSeGLHkCe2KnkVN0H5W6mFCPCTR2eoXcohS2Rn9AQXEmSnUxrVwH0qb+kKd6v9ZmDniZab4DpBIpbrYtyJJr5qe5n38NH1kHpBITpCZWNLRvTWTqDtEYeFKZR2Iwc7IhYOXbABRnFgBgG+hOs9+GIpFKyb2YwK0pu2nx+wjtfuZuMlrsH0niknCuvr2OZr8Nw8rHiah3fibt9yjq9m4BQN7lJJpuHQzA5T6ryTh4vcS8AQA3J+6g4eddsGlWn+LMAi51X4qsrRepv16izgs+uI99oURs/6aZSnlDqe/N5a1g6g99dONBVaggecsFGk7TzyxcNcHZy3/gYFeXmaM1yWdy8jIACPBqycLJfyCVSrl2+zxz1k9g6bSH6WjrOriz/Is/2bR/Hh/P6cWiKX/g4erLJ3N6cfz8Tjq17gdAdPwF5n6qmcPiw++6cfLiXp1Z575d/QGj3pyJn2cLcvIyGDHzRYL82/PHmf+jVZOXGND9oxKx/VtqZhKTwvqW+t66h7xLn06jSixLTImljn1dFm/5jCsxZ5HZOTKy70yeadCs1DJqG2Or7wcm/vgaMXcu4e3WhFG1eNKimMwj2Jg58XbASgAKijMBcLcNZGiz35BKpCTkXmT3rSmMaPFwch+ZuRsjW+wnPHEJ666+zbBmv+Fk5cPPUe8QlfY7Ler2BiAp7zKDm24FYPXlPlzPOFhingCAHTcn0qXh59S3aUZBcSZLL3XHS9aWS6m/4lPnBW1X/YPY/i276B4bHjF1crDLW7SpP/SR712hKuRC8ha6NNTc8qtv04wrabsIdulPsaqQmMxjOFo2fIK/YtWp1o0Bmyb1iP/6ILf/ux9ZO2/qhGpSQxal5BI3dhvyhCwkJlIKbqaW2M+pZ1PN/k3rY+ntiJWPZmIQm+b1kcc9PKmdezVHamkGQN3ezckKjy3RGFDmyck+G0fMhB3aZWqFisK4dGxbenDzo50oCxSaREKljC8wr2dP4MHS/yE8jlqlImb8dmTtvHF4ya/c+9dUzzRoxtJtX7B4yzSC/TvwXLNOgKbr/OsV73Mv7Q4mJqbEJ90osV9oK80/Bz/PFni4PIOHq+8/r4NITLmt3e7l1m9i8U9a205t+hFx7XiJL4f8wlwio0/y7eqHdVasLCYhJZbG3q34fu1oCovyaRkQWur9Zuc69Vn5ZfgTv1+lspjYhCiG9vqcD9/5gb+uHGLawnf45dtLT1xGTWZs9f3ATx/9hlKlZOnWL9h5ZAVvvzK+3GXUBPVsmnAw/mv23/4v3rJ2+NYJBTSTEm2LG0uWPAGpxITUgpsl9mvq1BOA+jZNcbT0xsnK55/XzcmQx2m3a+7cCzOppn6b1+1NbFZ4icaAXJlHXPZZdsRM0C5TqRWkF8bhYduSnTc/QqEswEfWvtTxBfbm9RgVeLDc71ulVrE9Zjzesnb4ObwEaOZaSC+8zYrIV7EyrYOn3XPkF6eXu+zKVK0bA5ZejjTfO4Ks4zdJ2XqRpJWnabLxPWKn7KZuv2Bc+gWhzJVz1v+bEvtpB9yZSEoMvpNIpU80L4GWGiRmJrQ4MBKJRKKzutn2IWQeiSFhwZ+k7ojUSXhU0Z6B2Kl7QCrB66tuTx5rLeDu4sPSacc4F3WE/ad+YduhxcyesIM5GybSrd07dAsZQH5hDt3HlMwXb26mSTwllZiUmDZWKpU+UQ77h9SYmpiz4osTpdb3/En7OXv5IBv3/sjhs1v56L2wEuvLe6Xo6tQAS3Nr2gf3AOC5pi9TIM8lMyeNOna1f2Y7Y6vvfzORmtAtZAAzlg6utY0BR0svRjTfy82s41xM2crppJW812Qju2OnEFy3H0Eu/ZArc/nmbMne2AdzD0gwKTEPgVQifaJ5CB5SYyIxY2SLA6XW75Bm24nJPMKfCQuITN2hk+Cooj0De2KnIkFKN6+v/hW7CZ0bTqVzQ03a6t23puJs9Uw53kvlq9aNAXliFqYOVjj1bIpdqwZc6LgQAGWOHAt3zeQ+99efq3D5qTsv4/quZnrS1B2X8fjwhRLrTWwtsG3hxv21f1Fv0POAJqufTbP6yO9mYl7Pnrp9A7Fs6MCtz3RnW6tIz0DczAPIE7PxX/mWNp2xsUhOT8DexoHQVr1o5tuaQV9o5jDPK8jG9Z+pZX87trrC5R8+u007X/2hs1sZ2OOTEuutLe1o1DCInUdX0Oul9wFNljc/z0DupcVTt44bXdq+jVtdH+Zu+Ein/PJeKdaxc6aJz3Ncij5FC7+2XLt9HjNTC2S2xpGe2tjqOzMnDYA6dk6o1WqOnduBt3vjir69ai9LnoiVqQNNnXrSwK4VCy9ocsLIlTnILDQNvHP311e4/MupO2nl+u4/v+/gBY8PS6y3MLHFzbYFf91fy/P1BgGazH31bZqRKb+LvXk9Auv2xcGyIXtu6ea6qEjPwIG4mWTLE3nLf6U2fTGAQlmAUl2Mpakdyfk3iErfw/Dmvz+mpKpXrRsD+deSif/mIEgkoFbjPVNzBdXg047c/GQnpnaWOPVsUuHybZrW40rfNdoBhP87XgDAd34fYqft4f76c6iVKizcZQT8PIDsk7dJXHoSiYkUiVSil3v7+deTSVwcjpWvM5HdNbOqyV7wwevzrk9ddk0Qm3CFZdumg0SCWqXiw3+mex3aaxqz147BxkpGaKteFS7ft0ELxs/urh1Q9r/3jwGmvb+CsI0f89vRVajUSlwcPfh23FYuXPuTzQfmY2JiilQiZWTfGRWO498mDpzDd2tGk5efjYWFFdNHri31KqY2Mrb6zshOZtbKERQrFahR4+UWwLi3a++Uxsn51zgY/w0SJKhR08N7JgAdG3zKzpufYGlqR5N/bglURD2bpqy50lc7gPB/xwsA9PGdz57YaZy7vx6VWonMwp0BAT9zO/skJxOXIpWYIJFItff2n0Zy/nXCExfjbOXLskjNHBY+shfo6vU5Bcos1kb1R4IEqcSU3s/MpY6F7oyYhlSj5yZ4GjHjt2Pf1guX/sGGDqXS1MS5CSrLrFUjCfLvwCshAwwdSqWpiXMTVBZR3/pRlXMTlMf2mPF42bcl2KW/oUMxiMqYm8C4+qEFQRAEQdBRrW8TVCbfub0NHYJQhaYMWWLoEIQqJOq7duvtO9fQIdQ6omdAEARBEIxcjWgMZJ2M5Urfio8qflrJmyM42/Rbrg58OPI1+2wcFzouJCIkjOvDNqHMk5dZzv3157jw8kIudlrEpW5LyDx+s8x9APKjU7jUfSkR7edx5c01FN3PAUCRmsvFzos57TWDwju6SVFqsohrf/Lh990Ndvy94Rt4dZwnk+b20S67FH2KQV+0ZsDUID5fOID8wtwyy9l1bDWDv2zDkC/bMnzGC5yLOlKuOGavHUvosIe566PjLzH0q5ASy2qD2lLfkdGnGTkzlM4jnVm985sytwfIyk3j07lvMPCzlgz+sg3frf6AIoXm/0ltqe/YrJOsvlL6Y5hVISJ5M9+ebcr6fz0qGJd9loUXOhIWEcKm68OQK/OeqKzD8bMJOx9C2PkQzt5bW+b2KrWKTdeHMS+iPYsudmLT9WHkKx7mGDh6dw4LL3RkXkQHfo/9ApVa8/j7jYxDLLgQypzzrcv5biumRjQGqgPHzv40Xqd5jEWtUhEzYQe+Yb0JDv8QC3cZiYvLfsTI8hlnmv06hMA/PuCZOb2J/mDrE+U9uDV5Fx4fvkjwiXE4dvXXPGEBmDnbEnhwFOaudk/35oRStQvqznfjtwGa9LHfrhrJ1KFL2fCNJvXt5v1hZZQADer5MW/SPlZ9dYrJQxYzY9lglKone1b6XNQRipWKEsv8PFtUKNGNUDZ91HddRzcmDpxL/67jnvi4EiQM6P4R674+z8ovTyJXFLD9sOZpIlHf+uPv2Jl3G68DNF/QO2Im0Ns3jA+Dw5FZuBOeuLjMMmKzwonJOsbooCMMb/E7JxOXkl54u8z9guv2Y2zQn3wQ+AeOlt4cufsTANEZR7iRcYjhLX5nTNBRMuXxXE7dAUAjh5cZELCuwu+3vKq8MXDnh8PEzz6sfZ3zVzyRPTUf/ISFf3Kp+1IudlrE1YHrUaTrttSSN0cQM377w/J+PMKdHzVXW6pCBbHT9nCpxzIudlpU4jj6lHsxETMHa+0TEq4DW5G2O6qMvUDW1gtTmRUA1gEuqIuVKHMe36NQlJJLYWw6jl0DAHB5uyXp+6495TuoWqt3fs2qHTO1ry/HnGHU15rMXBv3zmHEzBcZ8mVbJs3to30W+9/2hm9g1qqR/yrvG+1Vl1xRSNjGjxk5M5Sh09uVOI4+Xb99Hpmdk3bU/KsvDuHouR1l7hfk3x476zoAeLs3QaksJr8gu8z9CuR5rNw+gw9qYLpaY67vek6eNGoYhIn0yYdj2ds6EthIMxmZVCrFv2FLktPvVCTsKnH4zg8cjn/4SGR8zl8si9Q8IvhnwkKWXurOooudWH91IHkK3Sx7Ecmb2R4zXvv6yJ0fOXLnR0CTxndP7DSWXerBooudShxHnxJzL2Jt5qB9QqKV60Ci0naXud+VtN0E1+2HqdQcK1MZTZ16EpX2+HwBUokUf8cu2keGPWyDyJInAJo5C7zs22ImtUQqMcFH1oHIfxoDVa3KBxA6vxHI1YHr8fxEk4AiZdtFnPtoJqlweftZ3Edr0n4mLgknYeGJcj1jn7DwBJY+TnjP7IFaqeLaoI1kHo3RpjF+IP3ANe7MLr271uebHtg95/nY4xQlZmPhIdO+NneXlXtCodRfL2HlWxfTOlaPP1ZSNhZuD7sITWwskFiYokjPx8zRulzHNJTObfrz6dw+2ql5D5zaROe2bwHQo8N7vPOKJl3opv3z+GXfHEa9+eT/4Df+/hMNXH358J0fUKqUTJ3Xj7OX/+D5f1LbPhB+4XdW7Sz9i3XCgJ9o5vv4rrjkjATqOT78XLg6epCcnvDEcQIcPL0Zz/qNsLNxKHPb5dum06fTKGS2NS8ToajvipMrCtl3cgMj3/xvpR+rogKd32D91YF09NQkcbqYso1AZ83tlWdd3qaD+2gAwhOXcCJhIV29nnxWxhMJC3Gy9KGH90xUaiUbrw0iJvOoNpXxA9fSD3DkTukNhR4+3+Bp9/gJgLKLEpFZeGhfy8zdtZMKPU5WUWKJfAYyCzdSCmLK3O8BtVrNufvraeyoyXlR36Yp++Nm0MF9DKYSc66l7zdYmuIqbwxY+Thh5mhNzl/x2AS5k77vGoGfahoGOefukLDgT5S5clTyYiy9ypeJLePQDVT5CpJ/0UwHq8wvouBmqk5jwLFLAI5dAvTzhiogJ+Iu8d8doskv7xkshqrk4epLHTtnLsecIcCrJX9G7NJ+UVyJOcuGvT+SV5BDkaIQdxefcpV9OnI/hfJ89pzQdKcVFOZy5160zpdDSFB3QoIMd0/66q1zrNz+X36YuKPMbSOjT5OYEsu4d2pmQhpR3xWjUqn4duVIgv070LqZbgKd6sLJygdrM0fic/7C3SaIa+n76Bj4KQB3cs7xZ8IC5MpcilVyHC29ylX2jYxDKFT5RCT/AkCRMp/Ugps6jYEAxy4EONa8SdwOxM3ETGpFK1fN2IVn6rxAYH5f1lx5E3MTa9xsA4nLPm2Q2AzyaGHdvoGk/HoJRXo+toFumDnaoJIXEzP+V5r/9j5Wvs6kH7hO0rKTOvtKTKWoVQ/zJKnkxQ/nH1CDb1hv7XTGj/K0PQPmbvbI7z7sCShKyMLCTfaYPR7Kv55M9MgtNFraD6tnnMvc3ry+PfLEh93Kyjw5anlxjekVeKBr27c5eHoTmTmpBHi1pI6dE0UKOd+sGsGiqYfwrOfHyQt72Xxgvs6+JlIT1OqHYyuKFHJtfnq1GqYMXaqd4vZRnvZK0cXBnXvp8drX99Pv4uL4ZBnEYhOuMn3pIKaPXEuDemVPPHUp+iTR8ZfoP+nh7IX9JzVj0dRDOMlcn+iYhmbM9V1Rczd8hEQqYcxb31XqcfQhsG5fLqX8Sr4iHTfbQGzMHClWyfk1ZjzvN/8NZytfrqcf4GTSMp19pRLTEvVbrJL/aw4CNb19w7RTGj/K0/YM2Ju7kSW/q32dVZSAzKLsxHgyczcy/72fPBGZ+ZMl1PszYQGJeRd5t/H6EllGQ9xGEuKmuS12ImExzpa+jyqiUhmkMeD0WjPuhi2i6F629haBSl4MKjVmrraolSqSN50vdV9LTwfyo+6hLlaikheTcegGTt01KYkdOjUiafkpfOf2RmJqgjwpG4mJBHOXkgPsnrZnwDbQDUV6HrmRidg2d+P+unM49niYFjnihfk02fwfLOqXHAFceDuda4M28sxPvbAL9iixLmn1GYruZdNwSskrAvO6tlh6OZK+/xqOXQNI/uU8Dl0N16tRUS899wY/7/6e1MwkuvzTZVykKEStVuEkc0WpUrLnxM+l7utW15uY+EiKlcUUKQo5HbmfF1pqJoVq26IrWw8uZPKQpZiamJKSkYhUaqLzpfm0V4r+Xi3JyknlRtwFGjUMYtexVbz47Ova9QOnPctPH+2irkPJfwwJybeYOr8/kwcvorFPqxLrfj28lNSMJIb3mV5i+YDuExnQfaL2degwezZ/d7nCsRuCsdb34zyqvgGWbPmc5Iy7zPxgI9IaMCdJM6fXWHQ3jOyie9pbBMUqOWpU2Jq5olIrOZ+8qdR9HSw9uZcfhVJdTLFKzo2MQzRx0tRVI4dOnEpaTm/fuZhITMmWJyGRmGBn7lKijKftGXCzDSRPkU5ibiRuts05d38dTRx7aNfPj3iB/zTZjL1F/RL7NXHqwR/x3xLs8hYKVQFX0nbxXhNNL8bVtL1cTd/LG37zdI535t4aotJ+Z1DT/9POtAia2wZ5xWnYmjmTLU/ir/tredNvUYXf19MwSGPAzMEa22B3ssNjabT4TU0g9pa4jWjHpU6LMXW2QRbiTe75uzr72j3niU2gGxdCF2LuZo9N04eV5T6mA/Gz/uBiV03CERMrc3zn9gIX/Y62l0il+P7Ui5hxv6IuUmIV4IJf2BsAKNLyKM7IL3UsQNw3BynOKuD29H3aZf7L+2Pp5UhBdAqWnqXfS/aZ1ZOY8duJm7Ef8/r2+C3oU+p21Zm9rSONfVoRce04X4xYA4CttYz+XcYyZHo7HOycCQ54kahbf+ns28y3NQHeLRn0xXO4OHjg59lCu25A949Y/ut03p/RHgBLC2smD16i9ytoqVTKpMGL+WblcBTFRXi7N2Hq0KUAZOakkp2bjn0pYwGWbZtOTn4mCzZP0S6bMWod7i4+xCddp56zl17jrC6Mtb5v3rnMpHl9yS/QPP6758TPzBq7GT/PwEfWd2zCVTbtD8OzXiNGfB0KQKsmL5VrLEVVszZzwN02mNjscN5spBmFb2lqTzu3ESy+1AkbU2e8ZSHczdW9qPO0ew43m0AWXgjF3tyN+jZNtes6uI/hj/hZLLmoGStmbmJFL9+52OGiU87TkEqk9PL9iV9jxqFUF+FiFcAbfpqnRfIUaeQXZ2BlWkdnPx9Ze3xk7VlwIRSAtm4jtLdC0gpvY2Gi+10jV+ayN3YadSw8WXVZk+yurrU/ff0WoEbN2iv9UKNCrVbxUoOP8LCr/FTipTFYBsKAlW/rLPOYEIrHhFCd5bJ23sjaeWtf+/7Yq9QypRameE2vmml/7dt4EXRkjM7ynHN3qD+0DSZWZjrr/Jc9Oo92QXQqDaeWfp/Q2t+FFntHVDzYamLm6I06y957dRLvvTpJZ3lwQIcSc8h/OmhhqWWam1kwuv8s/QX5GIGNQlgz46zO8ssxZ+jTaRQW5roNwK9GlX71CxCXdIPhfb565PoHjq4o++mD6sgY6/uZBs3YOrv0p30eVd/e7o1rZB2/HbBSZ1moxwRCPSboLPeWtcNb1k77upfvj6WWaSq1oJvXdL3F+Dhe9m0YE6R7u/hOzjna1B+KmUnpg7s7eU6mk+dkneWJeRfo7Kk74ZGFiS3T2+pe2IKmUTI6qHKeeiuv6t8fVQ1ILc3IPn27RNKhR3HsGoDH+BfLfYymWwZhYmtR9ob/8iDpkKpYaXTTHVc2CzNLLt4IL5GE5lHaB/fgvZ6flvsYcz7ejbVl+XqtHiShcbDX75WSsRP1XbuZSS25nX26RNKhRwlw7MqLHuPLfYx+jZbiYNmgAtGV7kbGITZeG4S1adU8UWS0cxOUh/PrzXB+vVnZG1axB0mHBP3r+HwfOj5f/W7HiCQ0lUPUd+3WzPl1mjm/XvaG1Ugjh5dp5PBylR1PXE4KgiAIgpGrkp6BgujUqjiM8D8M9XePS7pukOMaO0P93UV9G0ZV/t1TC6Kr7FhC2SqjPiq1MeDs7IyltRUxY7dV5mGEx7C0tsLZuex8Bvrg7OyMtZU1X694v0qOJ+iytrIW9W1EKru+nZ2dsbK0ZlvM2Eo7hlAxVpb6rXuJWq1Wl71ZxcXHx5OaKnoGDMXZ2RlPz8cnUdInUd+GJerbuFRFfYs6rp70XfeV3hgQBEEQBKF6EwMIBUEQBMHIicaAIAiCIBg50RgQBEEQBCMnGgOCIAiCYOREY0AQBEEQjJxoDAiCIAiCkRONAUEQBEEwcqIxIAiCIAhGTjQGBEEQBMHIicaAIAiCIBg50RgQBEEQBCMnGgOCIAiCYOREY0AQBEEQjJxoDAiCIAiCkRONAUEQBEEwcqIxIAiCIAhGTjQGBEEQBMHIicaAIAiCIBg50RgQBEEQBCMnGgOCIAiCYOREY0AQBEEQjJxoDAiCIAiCkRONAUEQBEEwcv8Phxjr3VBz+xEAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.ensemble import RandomForestClassifier"
      ],
      "metadata": {
        "id": "-1qVm8XbpmFF"
      },
      "execution_count": 64,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "forest = RandomForestClassifier(n_estimators=25, random_state=1, n_jobs=2)"
      ],
      "metadata": {
        "id": "hd4ay6VhqsNr"
      },
      "execution_count": 65,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "forest.fit(X_train, y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 75
        },
        "id": "77tZm2ewq6dG",
        "outputId": "c9f1adfd-0afb-4b4d-8b62-cd3692251d0f"
      },
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "RandomForestClassifier(n_estimators=25, n_jobs=2, random_state=1)"
            ],
            "text/html": [
              "<style>#sk-container-id-5 {color: black;background-color: white;}#sk-container-id-5 pre{padding: 0;}#sk-container-id-5 div.sk-toggleable {background-color: white;}#sk-container-id-5 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-5 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-5 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-5 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-5 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-5 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-5 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-5 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-5 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-5 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-5 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-5 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-5 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-5 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-5 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-5 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-5 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-5 div.sk-item {position: relative;z-index: 1;}#sk-container-id-5 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-5 div.sk-item::before, #sk-container-id-5 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-5 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-5 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-5 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-5 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-5 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-5 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-5 div.sk-label-container {text-align: center;}#sk-container-id-5 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-5 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-5\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomForestClassifier(n_estimators=25, n_jobs=2, random_state=1)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" checked><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">RandomForestClassifier</label><div class=\"sk-toggleable__content\"><pre>RandomForestClassifier(n_estimators=25, n_jobs=2, random_state=1)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plot_decision_regions(X_combined, y_combined,\n",
        "                      classifier=forest, test_idx=range(105,150))\n",
        "plt.xlabel('Petal length [cm]')\n",
        "plt.ylabel('Petal width [cm]')\n",
        "plt.legend(loc='upper left')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "UcP_a8Z0q8JI",
        "outputId": "cdcd09a3-8097-4797-91a4-dfa2b24af1d1"
      },
      "execution_count": 67,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.neighbors import KNeighborsClassifier"
      ],
      "metadata": {
        "id": "wuIoIc2krDOH"
      },
      "execution_count": 68,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "knn = KNeighborsClassifier(n_neighbors=5, p=2, metric='minkowski')"
      ],
      "metadata": {
        "id": "oSZEnY_2rp5B"
      },
      "execution_count": 69,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "knn.fit(X_train_std, y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 75
        },
        "id": "dCQloW64rupA",
        "outputId": "56d550a4-7eb8-4c00-afd3-6bd39e88f7bd"
      },
      "execution_count": 70,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "KNeighborsClassifier()"
            ],
            "text/html": [
              "<style>#sk-container-id-6 {color: black;background-color: white;}#sk-container-id-6 pre{padding: 0;}#sk-container-id-6 div.sk-toggleable {background-color: white;}#sk-container-id-6 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-6 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-6 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-6 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-6 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-6 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-6 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-6 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-6 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-6 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-6 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-6 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-6 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-6 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-6 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-6 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-6 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-6 div.sk-item {position: relative;z-index: 1;}#sk-container-id-6 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-6 div.sk-item::before, #sk-container-id-6 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-6 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-6 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-6 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-6 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-6 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-6 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-6 div.sk-label-container {text-align: center;}#sk-container-id-6 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-6 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-6\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KNeighborsClassifier()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" checked><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">KNeighborsClassifier</label><div class=\"sk-toggleable__content\"><pre>KNeighborsClassifier()</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 70
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plot_decision_regions(X_combined_std, y_combined,\n",
        "                      classifier=knn, test_idx=range(105,150))\n",
        "plt.xlabel('Petal length [standardized]')\n",
        "plt.ylabel('Petal width [standardized]')\n",
        "plt.legend(loc='upper left')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "1gRAGC7TrwlJ",
        "outputId": "88d8fb5c-f31c-4c4a-9910-906ab8a29ac6"
      },
      "execution_count": 71,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "LH-7qsElr4SW"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}