diabetes_opendata.ipynb

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    "colab": {
      "name": "diabetes_opendata.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ekaminuma/ROIS-DS-JOINT/blob/master/diabetes_opendata.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KD0ugkva2BBk",
        "colab_type": "text"
      },
      "source": [
        "#**オープンデータ入門**\n",
        "2020/1/30 神沼英里\n",
        "\n",
        "-----\n",
        "-----\n",
        "##診療オープンデータを使った糖尿病自動予測\n",
        "\n",
        "- Google Dataset Searchから、論文表データのURLを取得。\n",
        "- 学習データであるオープンデータ（表データ）を取得。\n",
        "- **年齢や検査値から糖尿病(Diabetes Mellitus)を予測**する**XGBoost (eXtreme Gradient Boosting)**モデルを構築する。\n",
        "- 論文情報　(Supplemental Table1がデータ)　\n",
        "  - Woo YC et el., \"Validation of the diabetes screening tools proposed by the American Diabetes Association in an aging Chinese population\", PLoS One. 2017 Sep 14;12(9):e0184840 [https://www.ncbi.nlm.nih.gov/pubmed/28910380](https://www.ncbi.nlm.nih.gov/pubmed/28910380)\n",
        "------\n",
        "\n",
        "##手順\n",
        "- [1]. 論文雑誌Webサイトから表データをダウンロードでColabディスクに保存\n",
        "- [2]. 表データの統計量計算（相関係数）と変数抽出\n",
        "- [3]. XGBoostによる糖尿病予測、変数重要度、木構造可視化\n",
        "\n",
        "\n",
        "-------------------------------------\n",
        "--------------------------------------\n",
        "\n",
        "### [1]. 表データをダウンロードでColabディスクに取得\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tPIY4CgV-2UX",
        "colab_type": "code",
        "outputId": "71a32fbc-bdc7-47c2-a6cc-fca9947bd9d5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "#----------[1-1: PLOS ONEのサイトからデータをダウンロード]-------------------\n",
        "#\n",
        "# 表データのファイル形式は、EXCEL形式である事に注意。\n",
        "#\n",
        "#----------------------------------------------------------------------------\n",
        "import urllib.request\n",
        "\n",
        "#URLと保存パスを指定 --- （＊２）\n",
        "url = \"https://journals.plos.org/plosone/article/file?type=supplementary&id=info:doi/10.1371/journal.pone.0184840.s001\"\n",
        "savename = \"tab1.xlsx\"\n",
        "\n",
        "#ダウンロード --- （＊3）\n",
        "urllib.request.urlretrieve(url, savename)\n",
        "print(\"File Saved.\")"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "File Saved.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zSlUd0Ea_HXq",
        "colab_type": "code",
        "outputId": "71e1ce08-4c64-4c46-8f77-bdbc4722d05f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 70
        }
      },
      "source": [
        "#----------[1-2:ファイルがColabディスクに保存されているか確認]-------------------\n",
        "#\n",
        "!ls -l"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "total 156\n",
            "drwxr-xr-x 1 root root   4096 Feb  5 18:37 sample_data\n",
            "-rw-r--r-- 1 root root 153572 Feb 14 02:35 tab1.xlsx\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "08TUJJWQCTZy",
        "colab_type": "code",
        "outputId": "52f6f210-c752-4e44-ef05-1481fdc0db69",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 53
        }
      },
      "source": [
        "#----------[1-3:EXCELファイルを読込]-------------------\n",
        "#\n",
        "#  tab1.xlsxをpandasで読み込む\n",
        "#\n",
        "#--------------------------------------------------------------------------------\n",
        "import pandas as pd\n",
        "\n",
        "filename='tab1.xlsx'\n",
        "book = pd.ExcelFile(filename) \n",
        "\n",
        "#sheet_namesメソッドでExcelブック内の各シートの名前をリストで取得できる\n",
        "sheet_name = book.sheet_names\n",
        " \n",
        "#lenでシートの総数を確認\n",
        "sheetN = len(sheet_name)\n",
        " \n",
        "#シートの数とシートの名前のリストの表示\n",
        "print (\"Sheet の数:\", sheetN)\n",
        "print (sheet_name)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Sheet の数: 1\n",
            "['Sheet1']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gW2ZNdrNFxRR",
        "colab_type": "code",
        "outputId": "0b044fee-4421-4c55-c2bd-bb2f5e950964",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 398
        }
      },
      "source": [
        "#----------[1-4:DataFrame変数にセット]-------------------\n",
        "#\n",
        "# DataFrameとして一つ目のsheetを読込\n",
        "# シートの先頭10行を表示\n",
        "#\n",
        "#  属性変数の一部\n",
        "#  [2列目] DM: 糖尿病(Diabetes Mellitus)\n",
        "#  [3列目] Age: 年齢  \n",
        "#   :\n",
        "#  [7列目] FG : 空腹時血糖値 \n",
        "#  [8列目] 2hG:ブドウ糖負荷試験の2時間後血糖値 　\n",
        "#  [9列目] HbA1c : ヘモグロビンA1c \n",
        "#\n",
        "#---------------------------------------------------------------\n",
        "sheet_df = book.parse(sheet_name[0])\n",
        "sheet_df.head(10) "
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>No.</th>\n",
              "      <th>DM</th>\n",
              "      <th>Age</th>\n",
              "      <th>Gender</th>\n",
              "      <th>smoking4</th>\n",
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              "      <th>HbA1c (IFCC)</th>\n",
              "      <th>First degree of relative with DM</th>\n",
              "      <th>History of GDM</th>\n",
              "      <th>BMI</th>\n",
              "      <th>HT</th>\n",
              "      <th>Screening criteria</th>\n",
              "      <th>Risk test</th>\n",
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              "      <td>8.0</td>\n",
              "      <td>18.8</td>\n",
              "      <td>55.196</td>\n",
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              "      <td>25.8857</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
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              "      <td>4.5</td>\n",
              "      <td>11.3</td>\n",
              "      <td>38.801</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>28.141</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
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              "    <tr>\n",
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              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>59</td>\n",
              "      <td>1</td>\n",
              "      <td>Never</td>\n",
              "      <td>1</td>\n",
              "      <td>4.8</td>\n",
              "      <td>7.9</td>\n",
              "      <td>40.987</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>28.7312</td>\n",
              "      <td>0</td>\n",
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              "      <td>5.8</td>\n",
              "      <td>36.615</td>\n",
              "      <td>1</td>\n",
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              "      <td>21.2576</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
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              "      <td>4.9</td>\n",
              "      <td>32.243</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>23.3241</td>\n",
              "      <td>0</td>\n",
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              "      <td>5</td>\n",
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            "text/plain": [
              "   No.  DM  Age  Gender  ...      BMI  HT  Screening criteria  Risk test\n",
              "0    1   1   62       1  ...  24.3589   0                   1          5\n",
              "1    2   0   51       1  ...  20.9523   0                   0          4\n",
              "2    3   1   68       1  ...  25.8857   1                   1          7\n",
              "3    4   1   47       1  ...   28.141   0                   1          2\n",
              "4    5   0   59       1  ...  28.7312   0                   1          5\n",
              "5    6   0   62       1  ...  18.8916   0                   0          4\n",
              "6    7   0   56       1  ...  21.2576   0                   0          4\n",
              "7    8   0   48       1  ...  28.9811   0                   1          3\n",
              "8    9   0   61       1  ...   23.084   0                   1          5\n",
              "9   10   0   58       1  ...  23.3241   0                   1          5\n",
              "\n",
              "[10 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LWKHrx8pF7fv",
        "colab_type": "code",
        "outputId": "421b8a55-3d9a-4a68-ebbb-fafa5b88189c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 70
        }
      },
      "source": [
        "#----------[1-5:被験者数のカウント属性数]-------------------\n",
        "#\n",
        "# 行数、列数を表示\n",
        "# 論文との被験者数が合っているか確認\n",
        "#\n",
        "print('data size of row,column=(%d,%d)' % (len(sheet_df),len(sheet_df.columns) ))\n",
        "tmp_DM=sheet_df.iloc[:,1];\n",
        "print(tmp_DM.shape)\n",
        "#print(tmp_DM.count(0))\n",
        "\n",
        "N_PAT=len([i for i in tmp_DM if i == 1]) #患者\n",
        "N_CNT=len([i for i in tmp_DM if i == 0]) #対照\n",
        "print('DMとCTLの被検者数=(%d,%d)' % (N_PAT, N_CNT))\n",
        "\n",
        "#--------------------------------------------------------------------------\n",
        "#論文p.3 Resultsでは、1415人中の95人が糖尿病患者と記載されている。\n",
        "#1415 subjects (age: 58.1±10.2) with no diabetes at the last preceding assessment\n",
        "#returned for follow up and 95 (6.7%) were diagnosed to have diabetes\n",
        "#-----------------------------------------------------------------------\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "data size of row,column=(1415,15)\n",
            "(1415,)\n",
            "DMとCTLの被検者数=(95,1320)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-RyyJJ29dhVR",
        "colab_type": "text"
      },
      "source": [
        "---\n",
        "---\n",
        "###[2]. 表データの統計量計算（相関係数）と変数抽出"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ICdYuq547T-D",
        "colab_type": "code",
        "outputId": "dccd04e4-899d-40d2-d1f3-e8dcb5ad8115",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 520
        }
      },
      "source": [
        "#--------[2-1:欠損データの確認]-----------------------------\n",
        "#\n",
        "#　結果から、今回データは欠損無し\n",
        "#\n",
        "#-----------------------------------------------------------\n",
        "def missing_values_table(df):\n",
        "    mis_val = df.isnull().sum()\n",
        "    mis_val_percent = 100 * df.isnull().sum()/len(df)\n",
        "    mis_val_table = pd.concat([mis_val, mis_val_percent], axis=1)\n",
        "    mis_val_table_ren_columns = mis_val_table.rename(\n",
        "    columns= {0 : 'Missing Values', 1: '% of total values'})\n",
        "    return mis_val_table_ren_columns\n",
        " \n",
        "# 欠損データの確認\n",
        "missing_values_table(sheet_df)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>Missing Values</th>\n",
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              "      <th>Physical inactivity</th>\n",
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              "    <tr>\n",
              "      <th>2hG</th>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>HbA1c (IFCC)</th>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>First degree of relative with DM</th>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>History of GDM</th>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>BMI</th>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>HT</th>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Screening criteria</th>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Risk test</th>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                  Missing Values  % of total values\n",
              "No.                                            0                0.0\n",
              "DM                                             0                0.0\n",
              "Age                                            0                0.0\n",
              "Gender                                         0                0.0\n",
              "smoking4                                       0                0.0\n",
              "Physical inactivity                            0                0.0\n",
              "FG                                             0                0.0\n",
              "2hG                                            0                0.0\n",
              "HbA1c (IFCC)                                   0                0.0\n",
              "First degree of relative with DM               0                0.0\n",
              "History of GDM                                 0                0.0\n",
              "BMI                                            0                0.0\n",
              "HT                                             0                0.0\n",
              "Screening criteria                             0                0.0\n",
              "Risk test                                      0                0.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zDAPerx4azpH",
        "colab_type": "code",
        "outputId": "6bdfeb13-12ea-4bd3-ccb4-89ac944e3f45",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 865
        }
      },
      "source": [
        "#----------[2-2:属性間の相関を可視化]-------------------\n",
        "#\n",
        "# 相関係数(r)を可視化 \n",
        "#\n",
        "#-----------------------------------------------------------\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "df_corr=sheet_df.corr()\n",
        "print(df_corr)\n",
        "plt.figure(figsize=(15,7),facecolor=\"w\")\n",
        "sns.heatmap(df_corr,annot=True, cmap=\"jet\")\n",
        "plt.yticks(rotation=0)\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "                                       No.  ...  Risk test\n",
            "No.                               1.000000  ...  -0.185373\n",
            "DM                               -0.031055  ...   0.200373\n",
            "Age                              -0.145164  ...   0.509872\n",
            "Gender                           -0.019996  ...  -0.367573\n",
            "Physical inactivity              -0.235695  ...   0.285137\n",
            "FG                               -0.036676  ...   0.239958\n",
            "2hG                              -0.031191  ...   0.292552\n",
            "HbA1c (IFCC)                     -0.075652  ...   0.214339\n",
            "First degree of relative with DM -0.017518  ...   0.247685\n",
            "History of GDM                   -0.045258  ...   0.034364\n",
            "HT                               -0.110371  ...   0.519524\n",
            "Screening criteria               -0.052357  ...   0.493705\n",
            "Risk test                        -0.185373  ...   1.000000\n",
            "\n",
            "[13 rows x 13 columns]\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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9CFllDoWsQvVcWjdzt6fR7WH5YTU/sClM6QFDlsIF+49bBMBHH10kMjKPyMg8li3TMXq0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\nQe6MLmVnu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XG34PXrj3Yr08BOsLSqhWBHWtVnzds6JtQbvF2V7aDED+pstxSvyU0BcLIE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\nEREZLBatREREREREZLD+H9n4mpDHKnDmAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 1080x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IYbo17G1x58W",
        "colab_type": "text"
      },
      "source": [
        "---\n",
        "#### 2-2の相関係数の分析図より、DM変数（糖尿病）と「FG,2hG,HbA1c」の3変数が正の相関が示唆される。Smoking4変数は文字列データの為に、相関分析に入っていない点に注意する。 簡便の為、デモでは**Age～HbA1cの7変数を入力変数として使う事にする**。\n",
        "---"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ba_gvQyWcZbU",
        "colab_type": "code",
        "outputId": "1f672d48-d08a-4c1b-f6f9-7d6569210ac9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 381
        }
      },
      "source": [
        "#------[2-3:出力を設定、入力を一部列から設定]---------------------------------------------\n",
        "#\n",
        "# 2列目の糖尿病(DM)を出力yとして抽出。\n",
        "# 3列目～9列目の7変数を、入力Xとして抽出。(Age,Gender,smoking4,Physical inactivity,FG,2hG,hbA1c)\n",
        "#--------------------------------------------------------------------------------\n",
        "\n",
        "X=sheet_df.iloc[:, 2:9]\n",
        "y=sheet_df.iloc[:,1]\n",
        "\n",
        "#--------------------------\n",
        "print('入力Xの変数確認')\n",
        "X.head(10)\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "入力Xの変数確認\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Age</th>\n",
              "      <th>Gender</th>\n",
              "      <th>smoking4</th>\n",
              "      <th>Physical inactivity</th>\n",
              "      <th>FG</th>\n",
              "      <th>2hG</th>\n",
              "      <th>HbA1c (IFCC)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>62</td>\n",
              "      <td>1</td>\n",
              "      <td>Never</td>\n",
              "      <td>0</td>\n",
              "      <td>5.8</td>\n",
              "      <td>11.7</td>\n",
              "      <td>45.359</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>51</td>\n",
              "      <td>1</td>\n",
              "      <td>Never</td>\n",
              "      <td>1</td>\n",
              "      <td>4.3</td>\n",
              "      <td>4.9</td>\n",
              "      <td>36.615</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>68</td>\n",
              "      <td>1</td>\n",
              "      <td>Never</td>\n",
              "      <td>1</td>\n",
              "      <td>8.0</td>\n",
              "      <td>18.8</td>\n",
              "      <td>55.196</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>47</td>\n",
              "      <td>1</td>\n",
              "      <td>Never</td>\n",
              "      <td>0</td>\n",
              "      <td>4.5</td>\n",
              "      <td>11.3</td>\n",
              "      <td>38.801</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>59</td>\n",
              "      <td>1</td>\n",
              "      <td>Never</td>\n",
              "      <td>1</td>\n",
              "      <td>4.8</td>\n",
              "      <td>7.9</td>\n",
              "      <td>40.987</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>62</td>\n",
              "      <td>1</td>\n",
              "      <td>Never</td>\n",
              "      <td>0</td>\n",
              "      <td>4.4</td>\n",
              "      <td>5.6</td>\n",
              "      <td>39.894</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>56</td>\n",
              "      <td>1</td>\n",
              "      <td>Never</td>\n",
              "      <td>0</td>\n",
              "      <td>4.2</td>\n",
              "      <td>5.8</td>\n",
              "      <td>36.615</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>48</td>\n",
              "      <td>1</td>\n",
              "      <td>Never</td>\n",
              "      <td>1</td>\n",
              "      <td>4.5</td>\n",
              "      <td>8.1</td>\n",
              "      <td>43.173</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>61</td>\n",
              "      <td>1</td>\n",
              "      <td>Never</td>\n",
              "      <td>0</td>\n",
              "      <td>5.5</td>\n",
              "      <td>11.0</td>\n",
              "      <td>43.173</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>58</td>\n",
              "      <td>1</td>\n",
              "      <td>Never</td>\n",
              "      <td>1</td>\n",
              "      <td>4.8</td>\n",
              "      <td>4.9</td>\n",
              "      <td>32.243</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Age  Gender smoking4  Physical inactivity   FG   2hG  HbA1c (IFCC)\n",
              "0   62       1    Never                    0  5.8  11.7        45.359\n",
              "1   51       1    Never                    1  4.3   4.9        36.615\n",
              "2   68       1    Never                    1  8.0  18.8        55.196\n",
              "3   47       1    Never                    0  4.5  11.3        38.801\n",
              "4   59       1    Never                    1  4.8   7.9        40.987\n",
              "5   62       1    Never                    0  4.4   5.6        39.894\n",
              "6   56       1    Never                    0  4.2   5.8        36.615\n",
              "7   48       1    Never                    1  4.5   8.1        43.173\n",
              "8   61       1    Never                    0  5.5  11.0        43.173\n",
              "9   58       1    Never                    1  4.8   4.9        32.243"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pJg6W3MGe8ZK",
        "colab_type": "code",
        "outputId": "4260b365-256e-42b5-de84-3338ba004473",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 233
        }
      },
      "source": [
        "#--------ライブラリインストール----------\n",
        "\n",
        "!pip install category_encoders"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: category_encoders in /usr/local/lib/python3.6/dist-packages (2.1.0)\n",
            "Requirement already satisfied: pandas>=0.21.1 in /usr/local/lib/python3.6/dist-packages (from category_encoders) (0.25.3)\n",
            "Requirement already satisfied: numpy>=1.11.3 in /usr/local/lib/python3.6/dist-packages (from category_encoders) (1.17.5)\n",
            "Requirement already satisfied: patsy>=0.4.1 in /usr/local/lib/python3.6/dist-packages (from category_encoders) (0.5.1)\n",
            "Requirement already satisfied: statsmodels>=0.6.1 in /usr/local/lib/python3.6/dist-packages (from category_encoders) (0.10.2)\n",
            "Requirement already satisfied: scikit-learn>=0.20.0 in /usr/local/lib/python3.6/dist-packages (from category_encoders) (0.22.1)\n",
            "Requirement already satisfied: scipy>=0.19.0 in /usr/local/lib/python3.6/dist-packages (from category_encoders) (1.4.1)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.21.1->category_encoders) (2018.9)\n",
            "Requirement already satisfied: python-dateutil>=2.6.1 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.21.1->category_encoders) (2.6.1)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from patsy>=0.4.1->category_encoders) (1.12.0)\n",
            "Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.6/dist-packages (from scikit-learn>=0.20.0->category_encoders) (0.14.1)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mAUKACnQedwQ",
        "colab_type": "code",
        "outputId": "ba105a23-2d30-48cb-d30a-f4785cdfffca",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        }
      },
      "source": [
        "#------[2-4:カテゴリ変数をOne-hot-encodingへ(新規3列へ)]---------------------------------------------\n",
        "#\n",
        "#  smoking4がカテゴリ変数のため、One-hot-encodingを適用(smoking4=>Current,Former,Never)\n",
        "#\n",
        "#----------------------------------------------------------------------------------\n",
        "import category_encoders as ce\n",
        "\n",
        "list_cols = ['smoking4']\n",
        "ce_ohe = ce.OneHotEncoder(cols=list_cols,handle_unknown='impute')\n",
        "X2 = ce_ohe.fit_transform(X)\n",
        "X2.head(10)\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Age</th>\n",
              "      <th>Gender</th>\n",
              "      <th>smoking4_1</th>\n",
              "      <th>smoking4_2</th>\n",
              "      <th>smoking4_3</th>\n",
              "      <th>Physical inactivity</th>\n",
              "      <th>FG</th>\n",
              "      <th>2hG</th>\n",
              "      <th>HbA1c (IFCC)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>62</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>5.8</td>\n",
              "      <td>11.7</td>\n",
              "      <td>45.359</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>51</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>4.3</td>\n",
              "      <td>4.9</td>\n",
              "      <td>36.615</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>68</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>8.0</td>\n",
              "      <td>18.8</td>\n",
              "      <td>55.196</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>47</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4.5</td>\n",
              "      <td>11.3</td>\n",
              "      <td>38.801</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>59</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>4.8</td>\n",
              "      <td>7.9</td>\n",
              "      <td>40.987</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>62</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4.4</td>\n",
              "      <td>5.6</td>\n",
              "      <td>39.894</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>56</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4.2</td>\n",
              "      <td>5.8</td>\n",
              "      <td>36.615</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>48</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>4.5</td>\n",
              "      <td>8.1</td>\n",
              "      <td>43.173</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>61</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>5.5</td>\n",
              "      <td>11.0</td>\n",
              "      <td>43.173</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>58</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>4.8</td>\n",
              "      <td>4.9</td>\n",
              "      <td>32.243</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Age  Gender  smoking4_1  ...   FG   2hG  HbA1c (IFCC)\n",
              "0   62       1           1  ...  5.8  11.7        45.359\n",
              "1   51       1           1  ...  4.3   4.9        36.615\n",
              "2   68       1           1  ...  8.0  18.8        55.196\n",
              "3   47       1           1  ...  4.5  11.3        38.801\n",
              "4   59       1           1  ...  4.8   7.9        40.987\n",
              "5   62       1           1  ...  4.4   5.6        39.894\n",
              "6   56       1           1  ...  4.2   5.8        36.615\n",
              "7   48       1           1  ...  4.5   8.1        43.173\n",
              "8   61       1           1  ...  5.5  11.0        43.173\n",
              "9   58       1           1  ...  4.8   4.9        32.243\n",
              "\n",
              "[10 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SRHngWxST8Yu",
        "colab_type": "code",
        "outputId": "cdf9b9b9-bd28-49fc-9299-8a468201a730",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 900
        }
      },
      "source": [
        "#----------[2-5:属性変数の分布を可視化]--------------------------------------\n",
        "#\n",
        "# 対角線上のグラフが、各属性の分布\n",
        "# 属性変数は、定量変数（数値）と定性変数（カテゴリ）が混じっている事に注意\n",
        "#\n",
        "#--------------------------------------------------------------------------------\n",
        "import matplotlib.pyplot as plt\n",
        "plt.figure(facecolor='w')\n",
        "pd.plotting.scatter_matrix(X2, figsize=(15,15))\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Sw0YsO5aBY/feuGIvRQhiIR2BIKSpdCXCHNicJhkx8KRfl9qbDPPo1na2dcfo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hlCGfZ3kiXUpJumjRHfMzn6uQKZlcThYRQlSvBBk2IZ+HC/MFPrCrk929MQzb4b+8Mo7tuqSL\nFrv7YtWrHskSC1kNTQiSBYNvHZ3imV2dHBhoQdMEmibY0xvFtBx+aX8fp2dyvHBmnvlshd29MXb3\n3jrLpuOoYW89yeX/KPVUrBiEG12IJudfsR864NMpGiYb/zSh9S23Yo1gpmRgWjabY2ijKNd4dY0v\nPDaE5Uh8Ho2xRAG/Ryfs03n3ShbDql5sWrmiY+XCgtWjoMryHa/dIiUgwUGSKl27kKUJEMBMrkKq\nZPGvXryA7bogwOfRaQ16OT2bQ9c1BlqDHBhqZWd3dLmszez0TI6wz8NkMsXZWZvzCwX+zqEBvv3O\nNOfncuQN566HQ6mSwXRG57+8NsFT2ztvOER+s9iQwV26aC1tXq2m+B9dKHBhPs9stsJAS5CB1hBh\nv4fPHRokGvDy2qVFfnpmHkdW37xSwnzO4Gt//A4CScWWTKXncAG/LhBIJpIu5VWpoldnjr5ZJmkJ\nVGyXRLZMwao2y2TBJOyvrrsO+T2Ytovfo+H1aMxkKxQrFj6PoGxXewevBpliNbPSXLZMumTy7342\nSrJokCyYeDXB8SvpaqKVTJnZXIX+1gDJvMkLZwz6W4KMJ4r8XtlkV0+Ur75vK//mxdFqitjFIk9t\n72AqXd07eLNzeAqGjaC6drxs2mzOhLuNo/Y51l/FQgV3tbbyU1pKbLWhtOYqK7r3ggWG7aj+XNl0\nRhcKvH5pkZGOMO/b0Ul3LEB/S4Bjk2lyFRvXvT/n+N7sUrgjQRfgumA6LldSJaJ+L0GvjkRW0/en\nqxk2R9qrn0JCCHye5tlTd9U7l1OcmclxYLCVhwbidEX9mI5LtmKRLVkkcgb/NlOiYrnk1pCd3Xah\nZLpMpUr0xIN87+QMXzw8XINXsv5tyOBuoDXIgcEWRhN5zs/nOTmVpWQ6BLwaH97dxcnpHBfnc7x6\nMUGiYFI0LGxHEgl4lscXV4MwVnwPYCwNOCrOvQ2wrwZ2ACWrGiiWrRym7RL1e2kJe5c6E0muDAWz\nen+vxvJyz7m8getKbNtlsWgS9lWDMc2rUbZcJhaLLBYrFCrVYCxRMNCBiwtFNA1ag16yJYsntrRh\nOdU15AD9LUEeGW5FCEHbqmMjrqSK/MeXxhAC/u77t1ExXTUYqDPbtjcQAxYOAAAgAElEQVTmG3MD\nM1WcUXMXVqSFPz2dp2jDrdcMKLVQrqj+XNl83hhLcmmhwM/OL+C6LrO5ChPJIobjUjLvfnbodlbk\n61r+XhPVo6UiPp09fTGm02U0Ae9MZmgJeXmgO9rU59pKKXnlYhJXSl4ZXaQr5ufHp+eYyVYI+XQW\n8wauW50MMe9xwVhLyMcjw614tOYLkO9Uw8eQQogR4E3gLGBKKT9yu8fYruQXFxIcv5LGo2ukiiaa\nJlgs2PzBy6NcTJRx3WrGIdtxqSwt2O0PeEgWrds8e21IoGK62BJSJYuS5RDy6bgSVm49aQ17EGgk\niyY+XaPsOuQqFq4rKRoSKauH0U4ki7gSdCRLJ6JVnwtwpUS41U3E1UMyfezojjCxWGJnV5SeWABX\nSmIBL92xAI4rKVRsYkEPr44mGV2ongH2+ljyjtc6K/dPxXa5+XH1irJxrexK1Nx0Y6hF9spm1BXz\n88evT1A0bP7Bfz9OqmTVNBP16qfWNPB7dHy64KGBVr7y1Ba+e2wa05GMLhSoWC4vjy4yvJSavxkJ\nIRjpCDGWKLKlI8xctkLZdCiZNrmyDQhc5JoDO48m8GnQ3RLkX3zqQS4sFCgZDldSJQbbNt8GgIYH\nd0tekFL+2p3e+SdnZvmLo1eomA6apuHVwLRd7KVsRVcDkoLh4F2K3AUwmSzf+knrYOWsYdlyMS0X\nXbu+IygaLpbjIGU1abXjVvf3AUQDOtmKgyuX9vwB9tIzli0Xry6WlzpJrk5RO7x8IcGbY2mKhkWi\nYPDaWJLJZJFowMOBwRbOzuQ4M5vjiW1tbO+K0BryIQRs74qoQVgDNPcqe0VRGsW+/V0UpelYlkum\nZJEsGHW/YC2oJlMRQqDrGpGAh/0DcSJ+DyemMrRHfIwlivTGAjT7RNOn9vdRNB1SBYMXzy3w8sUE\niwWDsmEtHya+Vl0RD93xEL/19Fb29Lfw9uUMAK9fSqrgroGeFUK8DHxLSvl7t7tzpmRRNl0cFzTp\nYqz4xFrdPix3RbBzHwu8Fh5xfQr2q8lYViouXbYQgGcp8Lv6kHS5GmppXDunS1t6zrJRTcWrayDk\ntceUTYejkymKRvVoB8d1SRUNkkVj6YyXEi+em8dyJPmKzX/4tYPVxC8CdvfGVG6PBrDUXiRFUWpA\n9SzKZuG6kqJpEw14uZIpEw14WCgYdfv91TFc9UzikE9nuCOMR9PoiPgBwd7+OI4rEUJwYLCFgdYQ\ne94juV0zkBKSBYM/+MUYr48lmc8bOI5Dxbr3nsmr6zyzs4sH++NEAx7aIz6SBfO6zPGbyXoI7maB\nnYAB/LUQ4kUp5YmrNwohvgp8FWBoaAiAwZYgPl1QXpXdaL0z7mK6WVLdgHsz/qXkKwLQNYHrXJvK\ndtzq5l2PLrBdiaYJgj6dWNCL7Uos22UhZ+DXqtk7h9pC9MaDjC0WGGwLIoRgT19zdzDrnTr+S1EU\nRVHW7i+OTjGdLrNvIE5HxIfl3J+kKe/FI6pjMo8u2NUdIV2y8Ht0Hhpoob81yESyyI6uCEGfjpSS\nn59P4Mrq0syB1uYMQizH5cxMjrawj7cnUvzx6xOMJ4pIquNR25X3Zbl4NOhld2+MobYQuib4wmND\nlCyHWEBly2wIKaVBNbBDCPE9YC9wYsXtXwe+DnDo0CEJ4PFoxEM+ytlK/Qt8D1Zvsr0dl+rM3OrZ\nSMORaEu320vLM1c+t9ejsX+ghflchfaIn4891M+p6SyTqRJvjifRhSAe8nJ4Sxshn4feeAAJdEWb\n41DMja7Jsx8riqIoSs1ICdPp6jaciWQJpLxpZvD7LeTTsVxJbzzAYsGiNeQl4NX5p5/cw+hCAeuM\ny6VEkVPTWfb2xxloDXJ8KkMib/DCmXkM2+GR4ebac/fyxQTHr2QRwGLBYHShQNlykVIS9OqY95i8\nEMCnCz51oI+/tbdn+WceXSO2Sc60u5mGB3dCiKiUMr/07VPAv73dY7Z0RNg/0EK+vEDhXtPq1IFP\nqwZpPq+Homnj1QSWU51V8+sahRWH+3q1a0csCAE+XcOVLivugkcDgVheoyzktcfpGgS9Ooe3trOn\nL8qT2zqIBrx0RPz89Mwc8YAXBGzrjPDY1na2dUYI+HT6W4L4vTe+ETbvW6OBmnzdvaIoiqLUihDw\n5LZ2LiwUeHSklYVchaJR2405guoF96vneVZsl9mcwVBrkHcnMxQNiyMTaRbyFRJ5gy89McIvP9zP\n1o4wPzu/ANy4TacZLL8mAY9vbeOFM/PYroWUgljQi+W6GPe4EfKDD3Tx+cc255EHt9Lw4A54nxDi\nX1CdvXtZSvnme91ZSklb2Mc/+OhOEvkyRyez634fQXvER0vIT19LkNMzWWynOhWtCUE04EEUTSzH\nxaNr9MQCXE6Wqtks/TqmC2Gvl9SKLJ/RgJcd3REcx+X8fBFXSgZaQ+QrFn6PxnO7ezg03EqiYHDk\ncpoP7Owk6NPYO9DCtq4Imib45EO9hPwePLrG3z44wNhikQd6ojeU3asCjbrzq6k7RVEURVmzw1vb\nOby1Haju84oGvWs6FPtOaQICXp19A3HCPg+xgIejkxl29sQYSxTY1hmhM+qjaNrommBsscBDA3Ee\nHm7F59UwbJf9Ay01Kl19SCkxbJeAV1/+2TM7O2gJeWkL+9jWGaG3JcTfnJ3HkS4lw+HFswvMZCtr\n/rvs6o7wm09tJbpJl1/eSsODOynlD4Af3On9v/3uNJeTJQ4OtxL2e2+51FGs+H8tL4ZcXR55KwJw\nl65Q/MrDfaSKJumSieO6S2fTmYR8Gl88PMyu3gi6ppEsGLw9nmImW2EqVULTBC1BDyPtIeJBLwdH\n2vjco0N859g0Pm+CRK7Cg71RZnIGj420sbM7StG0uZwscTlZojcW4BcXFgHojPp5ensHf/T6ZXwe\njV99dIiuWICu2M2XZEaDDW8im47fq+pcaW7q8kVjBPXb30dRmslCvsJ/fmWcomEvJ6C7Vz5d4NHA\ndCSOWx2Dhn06PTE/0YCHeNBHS8jHRx7soTXs5YmtHfTEAkxlSrRH8gy3hzm04siDB/vi916odWDl\n+Pz9OzuB6hEQK493eGS4lUeGWwH4xqvjFI7NrDmwiwV0HuyLk6s05oiz9WxDjSKlhMvJEgAX5/P0\ntQTR9WpCEQAd6In5mS+YuK7Eowv8Hg3XdXElBH0eUqWbNwJ91ZveqwkCHo2K4+I4N2741KgGPr/2\n+BB/+Mo4xVXZfny6wOvRiPm97O6Nsrs3xmNbOnjh7AIeXdAZ8XN6NkfU71nafBtlJlPBtF22d0V4\n/uEBXjgzjxDQHvbTGvLx0Qe7eWS4lUjAi1fXeLA/TsFwGF8s0hMPsqM7xv7BFvYPxrkwX+DsbJ6y\n5fD2RIqK5RDw6vTGA4wvFrFdiW06TGfKxEO3vuIR9HkanmV0s/HqmqrzOguqaKPm+iMepgvVlj3U\n6iW7oT59NibPiqOB/BrEg+rq9kY38o++f9v7TPzuJ+pQko3htdFFJlMlhBDEAl4sx6ZoyjUHFF5N\ncHC4laBXp2LanJsv4NOrieuyZZvZTIVMyebp7R185MGe6x7bzEsHV4/PrwZ37+Xp7R18/Rdj5Cr2\nHf89PAKCPp22sI/ueICiYdMTV/kiVttQH69CwGNb2jg/l+exLW0EfTpHLqe5slhAaIKgV+e3ntnC\nf31jkmTRxKMJ2iN+WkNeWkM+vLrGiak0RcOmYDp4NI2QVyfoFVQc6I35OTAQp2JLFvIG7RE/s9ky\nc9kK2bJJyXToiPrZ3hnh3FyeiN/Dlo4IT27r4K2JNK7rEg16Cfl0umNBnn2gk7+1t5fLyRIjHSGE\nBiMdYYbbwwy3hXhuTzd/8PIYXbEA79vZyZ+8OQlUz+x7fGs7C3mDrZ1hvLpge1eUx7e08823J8mV\nbT7+UA9PbutgZ3eUoEejaDm0h/3oSwelHBhsYbA1yF+8M8ViwcTn0fjsoUH6WgKkiiZT6TJBr87W\nzvB71nk44CVb87+sslIk4CXT6EJsMp3/P3v3HV3ZcR94/lv3vhyRMxrojA7sbnZgDiIlUhSVAyVZ\ntmRbY8uTPHN8xj7jHe/O7JnZHYf1rNdjz+5Ya9mePZqRRCuYEiVRVGDOndg5oBs5P7ycb6j9474G\ngc6NxsNroOtzDg8BNPBevcJFvVtVv/r9on7U2l91PdDXyrf2jyGAh/raGQ371SJGlT2+tYUfHXfO\n83xkZwc/+7FPjefKbcWWsK+ngcFYjjvXOAvfw/E8Q7M5SteRy0MH/F4Nj65hWJK2qI9//ugG9qyp\nJ1MyyeRN/suL/YwlC0ykCrh0DZ9LY1f3yg6xvFEX359fj42tYf7ss7v4n757hFi2hGnZFK5y/i7k\ngi8/tIGn9nZyZDTNWLLAPesa2d65OnY+l9KKmtwB3L+hifs3NAHOJKir3o9l20hb0hr18eQdHUym\nS0yni0T8Hnobg2xoDvFqfwyvWyNdNKgPeDg5kSbid7O1PUJrxEfJtPG4ND64rZUfvDuB26VxYjxN\nW9THx3d1srO7jk2tYc7NZDkxnubURBqX7mSlDHldbO2soyHo4Vfu6eHUZJp0wWR3Tx0vnJrm5ESG\nwyNJfv3+Xp68o52ZTIk719QR8Lj41O6uudf2sV0dTure7igRn5sv3rNwlWcwliNZ2Xnsn86ysTVc\nqZniTMIu1hjy0lUf4MxUhpawl446H0I4E95fuef6V5AuhJ76XeoAXjV0RdyMpp3f69oGL0khCHg0\nioZNU1CttFdDvVeQKDlvIs0BjYJLU5O7Knv/1lbeHkgA8EhfC99z62Su8TPKzXlocysnJrMA3Leh\nmZ/Nu2/S1XBeFZtb/JyedjI17ugIMl7j9tzuHtvaSkvYR13AzU+OT5Ipm6SKJvVBDzPpMjYQ8mr0\nNIbQhCDoc1E2LdIFA5euYVmSnsYAWzoiDM3mEcCmljB+jwu/x0VLGJ7a28W33hlhQ3OQe9c3sW9t\nwxWPuqxm8+/Pr9c96xt59l88yOGRJC1hL//n86f46cnpS0pChTyCx7Z18JWH1xPyuuhuCC1hy1ef\nFTe5m08i2dlVx86uOja0hLh/fRMNIQ+/84HNZIrGgj+uuqCbtwfifPHeXja1hHnpzDTposlTe7p4\n+WyMkXge05I0hbysaw6SLhhsbgsT9rnZ0BJiU6uTbGR9c4imoJfBWI6iaRH0unh8axu7uuupD7rR\nNbEgfrpYSX1pWDaGJdnUGp57rIutbQqytunKO2md9X7WNgVJ5MvsvM5VoQ9tb2NPTz0NQQ9C3Pi7\nuUvX6GsLM54ucme3Wh2phgc2t/H3+0cAeHhzG98X0NsYJFUw6L3K9aAs3if3ruHvXhsC4Km7evnG\nP+jzFjFq2rRVqznk4/FtbQigKejDpWtzfR5UfV4VnfX+SnSGoLPeOcbQHHSTKpp01/tr3bxV6cmd\nnQy/cB4EPLmjm7+udYNuc2Gfmwc2NhHPldE1QUvIx0y6TE9DgNaIk/PgM3vXcM/aBn58bBK/R2d7\ne4S3BuJIAam8gVvXaAh6yJcsPC6NU5OZBfeX91aiqNwu7batq3Yzgl4X929o4vnjE0xlynTW+cmX\nTFKVCXZHnZ9P7u7kl+5aQ8ir3iyux4rupZ1ddRiWxK0L7uyuR6uEJPo9On7PwpPjO7rq2DEvE9EX\n7+2d+/ixra0cHknSVe+nLuDh47s62dFVxzOHxxCIud2xC4bjeUxb4tI0zs1k6ajzXzHm99EtLRwe\nTtJR57vp8w5uXeMTd3be0M9omripeGQB/NWX9nJuJqu2vqtkb08db5yPIYDdvXU8KwT/7qPbeGsg\nvqBui7J0tndE2dweRgBbOyIIAXd0RZnNlth8mayxys3bURmvhYBtqs+XxX3rm/C6dISAPWvq0YTg\nL395jxpbqqi7LkBvcxABdDXcfrs3t6qGoIcPbW/nb14d4IENTaSKBv/+E9vpbnivePhvPLhu7uOd\na5ykH8fGUiTzBmsa/TxzaBzTlpfcE4ITKaXcnDNTWSI+N5YlefKONlojfgzb5pfv7iHgWdHTlWW3\nonvLpWvcU0l1ezOifvclhz/XNgX54j09CCFoCHoW/Nu65iBt4z7Kps2W9shVHzvic/PQdRwsvZV1\nNwQWDIDK0npsazuxbBkhBO/b3Mq/Z2EaZ2XpvX9LG9OZEkIIHtrUgiYE/+yRDbw7muTRvtZaN29V\n0jWx4CyG6vPqu7jPQY0t1Xbx2KLcOja3hfnsvm4ODMX5QFvrdd3XzF/U/tK9vZQsi5awmrRXw11r\nG9EEdDUE+PAdHXM5JJQbt6Ind9V2pZWYoNfFL921Zplbo6xW0YCbf/y+DbVuxm3lcn3++La2S7Kb\nKdWl+lxZbW6F8XypMmpez+PcSq7nNc1PxX+jnMziKuyyWu5a23DdyViUqxNS3uolwN/T1NQke3t7\nl/xxDUuSK5l4XBoBjyoENN/g4CCtnd2UDJuAR8ejCmxX3eDgINW4zpX3SAmZSm2csM/N0JC6zpeb\nGluWnxpbqu9yY4vq8+pSfV57amypvouv84MHD0gp5WXfOFfUzl1vby/79+9f8sf95tvDTKSKAHz5\ngbWqFtA8e/bs5Yt//D+QEuoCbn79/rW1btKqt3fv3qpc58p79g/GeeVsDID3bW7mNz75mLrOl5ka\nW5afGluq7+Kx5Tc/9Zjq8ypTfV57amypvouv8909DQev9L1qqRRoiTjhl2GfC79b7dzN5xRRd84c\nNofVgWFldWgKeRHCOfd14WN1nS8v1efKanTx2KJUn+pz5XZwI9f5itq5q5ZHNrewpT1CfcCjQoMu\n47P7upnNlmm9Deu2KKtTb1OQL93biwDqKxMMdZ0vP9XnympzubFFqS7V58rt4EauczW5A4QQtEdV\nzZ8r8bp0OupU/yiry8VZcNV1vvxUnyur0cVji1J9i+3zpUo+oyjL4Xqvc7VNVWWmZXN6MkM8V651\nUxYtXTQ4OZGmaFi1bsptQ/X58lN9rqxGQ7M5hmfztW7GbUX1+bWVTItTk2lSBaPWTVGUqonnypye\nzGBa9rI+r9q5q7KfnZzm5EQaj0vj1+/vXZGFGL/19gjZkkl3Q4DP7OmqdXNuC6rPl5/qc2W1OT2Z\n4UdHJwD46M72Grfm9qD6/Pr86OgEg7E8AY/OP3pgLS5d7TUoq0uhbPGNt4fnamI/sX35yv6ov6Yq\nKxgmAIZlY1grp+zEBRLmdjIKZbO2jblNqD5ffqrPldUoP+9aLpSXd+X4dqX6/Prky854WzJtrBVU\nkktRrlfZsjEqO3YX5gLLZeVtI60wj/a1cmg4QUedf0WWWBDAx3Z1cH4mx/bOaK2bc1tQfb78VJ8r\nq9GOrjpKpo0AtnZEat2c24Lq8+vzxLY2joyl6G0M4nWpLOXK6hP1u3nyjnbGkgV2r6lf1udWk7sq\ni/rdvG9zS62bcVN6GoP0NAZr3Yzbiurz5af6XFltdE1wz7rGWjfjtqL6/Po0hrw8ssLvjRTlWja1\nhtnUGl7251VhmYqiKIqiKIqiKKuAmtwpiqIoiqIoiqKsAit+clc0LJW6vMpsW5IpqnTFy0n1ubIa\nXTxeq+t8+ak+V24VmaKBbatkKsrty6rSeLyiz9yNxPP8w6ExNE3w1N4uWsK+qj1XIlfmzFSGdc0h\nmsPeqj3PrehvXhvg1ESahza38LGdHbVuzm3h2wdHGUsU2NEV5f1bWmvdnFVHSsmxsTRCwLZK0oOp\ndJHBWI6+9siKTH50qxtPFvjuwVGEEHOlJtTYsvxUnyvVNBDLMZstcUdX9KqJUl44Pc3h4SQddT4+\nu7cbIcQytlJRFidXMjk+nqajzkdXfeCmHsuyJd98Z5jpdIl9vQ08sLFpiVq5wnfuRhJ5TFtSNm3G\nk8WqPtc/HB7j9XOzfPfgaFWf51ZjS8kvTk0zkijw3LGJWjfntiAljCUKAAyqQrhVcWwszc9OTvHT\nE1OcmEgjgW8fGOX1c7M8e2S81s1blUYTBQzLGa9HEwU1ttSA6nOlmmazJZ45PMYrZ2O8dHrmqt87\nFMsBMJ4sUjJVyQhlZXj+xCSv9cf43sGxBWVPFiNfNplOlwAYmM0tRfPmrOjJ3fbOKF31fnqbAvS1\nXT4bTb5s8uLpaQ6PJG/qubTKqpJ2m60uaULQGPSQL5t0RKu3M6q8RwhY1xRkNltiS/vyZ1m6Hcz/\nM9aEQHD7/o0vl02tIUqmhWHZbGoNqbGlBlSfK9UkhMAZTa89jt6/oYmmsJd71jXic99YKYQDQwle\nOjOjjuQoy+7CdS0Ec9f6YoV9bvb1NtAU9nLf+oUZdmPZEj8/OcW5meyiHntFh2VGfG6e2tt91e95\nrX+WY2MpAJrDXjrr/It6rk/s6qR/JsPaptCifn6lkkBnnR+fW6clom4GloMEhuN5GkNe+qez3Ld+\n6bbqFce2jogzqROwpd0Jy/zMni6G47mapC2+HZyP5ebCtAZiOTW21IDqc6WaGoIePrW7k1i2xLaO\nq9cL3dgaZuMixtrBWI6Xzzi7glLKFV9qSllZHt/axokJJyzT77n5+owPbGy6bDjmT45PMp0ucXw8\nzVceWnfDCyArenJ3PYJep0N0TeC/wc6ZLxpws6enYamatWIIoCnsxevWaQzeXmcNa0UAfo9OpmgS\n9Kz6P9GaEEJcUmC4Oey97c7TLqeQ971rOeh1qbGlBlSfK9XW3RCgu+HmziJdTcCjowmBLeWCMUVR\nloPfo7Onp/oFyUNeF9OU8Lk1XNqN7xCu+r+Me9c10hrxEfa5aAh6at2cFelz+7qZSBXpaazegK0s\npPpcWW02tYbx79ERgrmD6Oo6X36qz5WVrCXi4/N3dZMrmaxtCta6OYpSFR/a3s7gbI62qA+XfuMn\n6Fb95E4Iwfrm6w+ltG3JT09OEc+VebSvhVYVusLJiQxnpjJICZuvcLZRWVqqz5ff2wNxzkxl2Nfb\noPq8Si5e0Q/73IR9KjNpteRKJs8dm0QIeGJ7G6DGFmVxjo+nODScZEt7ZFl2Lq5G3Zcpt5pUweD5\n45N4XBof3NZ2w2GUF/O4tJs6IrKiE6pUw1iywInxNJOpIm8PxGvdnJqTEl7rjzGTKfFqf6zWzbkt\nqD5ffqrPldXo+Hia4Xieodk8Jycy6jpXFu2Vs85188rZGVWbTlEucnQ0xWiiwPmZHGenFpcEZSmp\nyd1FGkMewj4XQkBvo9ryFwI6650kNL0qjGdZqD5ffqrPldWoq96PWxe4dUFnnV9d58qiXbhe1jQE\n0BZxBkhRVrPuBj+6JvC4NNrrar+zvOrDMm9UwOPiV+/rpWTa6rBuxWd2d5Etm0RU+NSyUX2+/FSf\nK6tNR52f33hwHcBcmJC6zpXF+OC2Nu7b0ERIJflSlEv0NAb5zQfXIQQ3HZK5FNRf6WW4dQ33Ig4w\nrlaaJtSNwDJTfb78VJ8rq9HFNxrqOlcWQwh13SjK1SxFaYSlomYwiqIoiqIoiqIoq4Ca3CmKoiiK\noiiKoqwCyzq5E0LcLYR4XQjxqhDizypf+73K5/9dCKH2/BVFURRFURRFURZhuXfuhoBHpZQPAC1C\niIeBRyqfHwE+sZyNKRoWL5ya5o1zs0hZu9S+JdOifzpLvmzWrA1Xc3Q0yX97fZDheL7WTblt9E9n\n+cnxSSZTxVo3ZdUaSxaYSBXmPs+VTPqns5RNu4atWr0My+blMzO8cnYG03L6WI0tympjWDbfPTTK\nM4fH5q7zlaxQdu5PioZV9ecaiOX4yfFJxpKFa3+zolRZqmBwbiaLdZOlP2xb8sa5WV44Pb0sf0ew\nzAlVpJST8z41gG3Ai5XPfwb8MvD3y9We/YMJDo8kAWgKedh4EwUDb8b3D48zmihQF3Dza/f1IsSt\nk2ZYSvjT509TNGwOjyT5s8/tqnWTVj0J/OjoBJYtmUwV+dX7emvdpFWnfzrDD96dAODjuzoA+Mbb\nw2SKJj2NAT61u6uWzVuVjoymODCUACDic6uxRVmVfnx0gm+9PQKAW7913ssX6+n9I8RzZTrqfHxu\n35qqPY9tS354ZBzDkozE83NZXhWlFoqGxf94a5iiYbGtI8Lj29oW/Vj9M1nePD8LgEfXuH9D01I1\n84pqcuZOCLEDaAaSQLry5RRQd5nv/YoQYr8QYv/MzMyStiPid+a2mhCEfLVLHJouOjt22aLJrVgb\nVCAq/1eWgwCClTIcF65RZWmlCu/tkmeKJhLIl625z5WlF513LYcr460aW5TVZuFb+Mq+sqWUZEvO\neJguVHdc1DQxV34q4lcndJTaKhk2JXNp7glCXqd2NrBsGWeX/c5RCNEA/CXwWWAPcGGJPIIz2VtA\nSvlV4KsAe/fuXdKpz46uOuoDHrxujZZwbYoOJvNl3t/XwpmpDBtbw+i3WHFQIeB3P7iZg0MJHt3S\nUuvmrFoX3kAvvLl9fl83k+ki3fWq0HA17OiKMpsrIRBs64gggCe2tXJ0LLUsq2q3ow0tYT63z3mT\na486BbV/5wMbef18jI/s6Kh18xRlSTx5RzsFw0IgeHxrK/+2xu1JFQw8uraoNO1CCD6yo53Tkxm2\ndUar0LqFPrdvDeOpAl31/qo/l7J6mZZNqmDQEPQsOhIuGnDz2NZWxpNF9vbU31R7Our8fOHuNZQM\nm+6G5bmnW9bJnRDCBXwd+F0p5aQQ4h3gnwJ/AnwAeHM52wMsW0dfzqHhBC+eniHo1fnlu3vmdmtu\nNds7o2xfhoH9djUSz/O9Q2MI4NN7nLWOoNfF+uZQbRu2ik2mipyayCCAbR0RAPYPJZlKFwmOpHgi\nqm4uqqGjbmG/Hp/IUDQkx8czdDcEa9QqRVk6k6ki0+kSApjOlGralpMTaX5yfBKPS+MLd62hLuC5\n4cfoaQzS07g8f5t+j67e95SbIqXk6f2jTKWLbO2I8MGbCKfc1hFlW8fS3Psu9wbScodlPgXsA/5E\nCPEisB54WQjxKrAL+Idlbk9NXTg0nCtZJPLlGrdGqZXJdBHLlh4Wr5EAACAASURBVJi2ZEIlUFkW\nF/e5lDCVdvpeHeZfHqrPldXoVhrPx5MFpHRCzGLZ2k40FWU5GJZ8730lcfu+ryx3QpVvAN+46Mtv\nAH98E48JUNUkJLYt0a4zXLJoWHz34BjposGH72i/6s7g3WsbKZQtmkJeOutu7Z2CG+kD5cZ0Rv0M\nzebQBHTWdde6ObcFp8+zCASddd0IAT63xsGhBE+qEMFlofq8dtR4Xj2dUT/D8VxlbFne1frj4yle\nPD1DR52Pj+3sZE9PPamCQcjrYm3T8uyIqWtLqSWPS+Phzc30T2XZ0+uEU44nC/zg3XECXhef3t1J\nwHP5qc/8a3elX8e3ZhzgdZpKF/nOwVFcmuCpPd3UB2885OBaTk6kef74FE1hD0/t6cbj0jAtm5fP\nzlA2bR7e1LIgln00UZhbNTgxkb7q5K457OWpvd3kyybHx53vjVbpIHE8V2Y8WWBjawiv68Zi77/1\nzjCHR5I8vrWNR/rUubuldmgkwZHRFEI4GQXBOYs5miiwvjm0qLMSytW9dGaal8/EQMADG5uQEr59\nYJTpTJFMyeSTd3bWuomr0rmZLAJY1xxCSvjWOyNMZ4qkCobq82WixvPqOjSS4N2RheP5UhqJ54ll\nS7h1QW9TiJDXhWVLvntwlOdPTNEQ8FA2bRL5Mk0h74LMv2XT5qUzM0gpeXhz8w3fC1zLS2dmODiU\nYEt7hCe2Lz4cTlFuRtm0GJjNEvbpdNcHODWZJl+2yJcthuN5+toil/zM+ZksPzwyQcTvpjXi5eRE\nhu2dUR7b2lqDV3DzVvTk7txM1sloAwzF81WZ3J2ezGBLyXS6RCxboqPOz+mpDO+OOIN2xOfmvnkJ\nGLrq/TSHvaSLBlvaIhQNi5MTadqiPtqvcI7nmcPjTKaKhH0u/tEDa5d8F7JkWnzznWFKhs25mSwf\n33X9N1G2lPzgXSc98XcOjqqbgSp4e3B2bkHgYCVV/NP7R8iVLE7Up/nsXrWbt9RePD1NumgggJfP\nxLBsyVgij2lLTk2kr/nzyo07OZHmuWNONZyP7GjHtJ2U57aEo2NLfxOsXEqN59X39oAznguYK/2x\nVEbieb59YJRDwwnaoj7u6IzySF8LA7EcQ7N5mkNeYtkid61toP4y5+uOjac4Vvlbawh62NvbsKTt\nOzHujJ2nJtN8cFvrLVXWSbk9FMoWf/7zs4zEC/zi5DSTqRK9TUG8Lo2Qz3XFJHVnprKYtiSeKzMc\nzxPyujg5kVaTu1roa4twZjKDS9dY3/zegd+iYZErmTSGvHNfOz2Z4Z3BOJvbwuy7gQFtZ3cdM5kS\nzWEvLWHn8RqDXnRNYNmSprB3wff73Dq/ck/P3OfPHhnn7FQWlyb49QfWzmVDnC+RKzOayNMS9iEl\nLPV4aNtgWk74asm4saKqQghKhs1wPE9rxHvtH1BuWL3fi6tSD6ku4EYCs9kysWzpsteLcvPmh0F3\n1fvQNHDpGoZlqZ3SKimWrblFjKJhoQsn/bllSVwrOPxlJRFC0BL2MpUpXZLcRlkaAY+OYdkIIOBd\n2rGkZDrv36YtGZrNk8iVGUkU8Ls14rkSQgj+yfs2cOeaS7P7pQoGAbeOJgQSSVNo6d/P9/bWc2Ao\n4WQgVhM7pQY04dSSk1Ji2fDm+VlOT2XYtaaOz+3tXnBdmpbN8yemyBQNtnVEOTuVoTHkYW9DPcfH\n0+xYwYkEV/SdY0PQw6/dv3bB14qGxdffHCJTNLlnXSP3rm8E4NX+GOmCwUymxM6uOjyu68sls7Yp\nyG8+tLCYZlvUx5fu7cG0Lz9AHhtLkS4Y7Omtn6tsL3nvfODlWFcocHdmKsNr/TF6m4I8snlxq6x+\nj87HdnYwHM+zs+uSUoJXJaVkMl3EtG0GZ/OLen7l6vb01PODI+MIYFe386acLhpMJFVK6GoJelxz\nIUn+Svy9361j2ZLgFeLxlZtjVcYSAdhIJE6NUYGa3C0XATy4qZn9gwke3qRKflRDslIPTuKE1y+l\nDS0htndGOTOVZiZdpjns5dRkhqjPhWlLNrWGGZzNXTK5OzeT5QfvjqMLwRPb22gOe2moQqTTvt6G\nG1o8V5SbZVo2B4YSuF0ad3bX4XXr/NuPbuWnJ6Zwa4KTExkGYjlMSxL1uZlMF1nTEODRvhYGZ/Oc\nnswATi0705akCiYf7qrjwY3NNX5lN+eG72KEENuA9VLK71c+/zPgwvT2L6WUB5ewfTcsXTTmCg5O\npN7LlNPTEODoWIrOOj9u/eZvJK6UUngknuenJ6YAKFs2j21t5ehoivaon/AVihdG/G56GoMEPPol\nu3ZvDcRJ5g0ODyfZ21N/xce4lt6mIL1Ni0tn7HXr2FLivc4JsXJjhuI5fG4dAQzHcyCds5uWhCE1\noa4Kl0ubm8RpApDgd2tIXPjUzl1VDM3mKVQKxQ/HnSx+INE1uLF4AmWxpITBWJ6mkHOm5P4NK/sG\n5lbk0sClaSDAVYXdq6Jh0dsUIlNMYktJxOeaiyQCZ8HkYlOVjMCmlBiWXZWJnaLUwqGRJK+fmwWc\nRdvNbWHWN4dZ/3AYgO8fHuPV/hitER8nJ9MIBMl8ij099bREvPg9OkXDmvu7KRoW8Vy5avkvlsti\nlqj/CPjDeZ9/EPhfgADwb4FPLEG7Fq0l7OOutQ1MpooLihG/f0sL+9Y2EPa6qhou4HVpCOG8iXpd\nOgGPi7vXNV71Zz62q4P+6Sy9jUGEEEgpsSXommBDc4hYpkRnnb8mOwqaEPybD/XxxvlZPrZTZbSr\nhp7GIBGfC4GgpzGIELB7TT0TqQJ33OBOq3J9PnFnJ6cmM2gCPrqzk7/RBB+/s4sjI0k+dIdKBFAN\nW9rDbGgJIYC+1jC6LtjZVcdwPM89a9Vq/3IQAnoaAwzEcmxsDde6OavSp3d30z+dQxPOmPK9JX78\n9c0hzs1ked/mFt7f18KzRyYoWzY9DUHWtwTZ0n5psoid3XXEcmU8umCT+r0rq4RlL9x0uNwGxEd3\ndrCpLYxAkC4avHo2RlvUR9jnRtcEX75/LYZlUzZtXjwzTdTvpqeG9a+XymJmC+1SytfnfZ6WUn4H\nQAjxW0vTrJszf1J3gRBiWWbiLREfn9zdSTpvzhVHBie8sWBYl03BGvG56WsL43frJPNl/vDHJ8mX\nLH770Y3cu76RO9fUVSaNtQldagp56G7wE1nhKxm3qs1tYTa3htE0wfoWJ1313b31vNJvclfvpWcn\nlJvn9+j0tYXRhJg7Y+cSEsOWeJY4g5zi2NoR5csPrEUTgrVNQQTwiTs72D+U5CN3qIWjaigaFs8d\nnUAIeOKOdgAEkpJhqVDYKulrj/BIXwsago2tS1t+oFC26GsLs645wJvn47w9GJ/LjPnghiZ2dtVd\nNn170OtSi7PKqlE2bZ7eP8Jstsz96xt5dHMzdUEPPY1B8mUTn0vn4HCC0USBe9c3LsiOeUdndMH9\ntMel4XFpBL3wyTu7rvSUK85iJncLln2klPfM+/S2T72VLZk8f2yKfNnC59bmVkefeXeck+Np7lxT\nxxPb2xf8zM9OTHF0LMXapiAel2Aw5oTiPX9ikk1tYXzu2t1sSin5N987RiJf5ucnp/lvX767Zm1Z\nrfYPxjlZifs+PJxASsl//PEpEvkyJyYyqs+rYP9gfC6UY0t7GMuW/L+vDFAybc5NZxakD1eWzvrm\n9252pZS8cGqGeK7MT05M8OiW2/7tY8n9w8FR/stL5xAIDFsipeRHRyeJ58qkCsZlF0KVm/O9Q6N8\n/c0hQFAfXLoF0QNDCV4+M0NTyMO96xt5/vgUx8ZSGJbN+pYQX3ttgIHZHE/t6V7R9bkU5VriuTIz\nmRKzuRJ/8MxRmkNefuexzYzEC7wzGKc+4CaeKyOEoGzZCzKOlwwbXRNLcjzrVraYyd24EOJuKeVb\n878ohLgHGF+aZi0vKSUzmRIRv/umJ1KTqSLZknPm70Loi5SSHx+dJJkvM5EqXDK5OzaeZCReIFs0\n+eK9PUT9bkqmzZ6e2u/a2JK515PIGzVuzeqUKZoMzebmPlZ9Xn0X97mUkqJpY9qQK1o1bt3tYzSR\nZzpdIrjEWQUVx0SqiG1LQDKVcjKVjibyTGdUn1fLZLJYOf8mmaz0+VI4P5MFIJYtky9ZvDuaZDZb\nIuDRGU/k2dwWYTxZpGBYBFWWZWUVaw572dAS4tzxLD6XjmFJDg7H8ejOmDYQy1EyLKIBD60RH+BM\nCA8OJTg6lqIx5OELd63Bpa/ePBKLGQH+NfAtIcTfAReSp+wBfhX43BK1a1m9eGaGw8NJon43X7y3\nB/cif+EvnJ7m7FQGr1sj4nOza81756Xq/C5KhnXZRCxFwyaeK+N1a6xpCPCnn92JYdoLSjnUiq4J\nPn9XN2+dj6siw1VyfipDqmgigPOxrOrzZXBxn2uawK1rWLaNT930LgsJTKZLFMoWw/HCNb9fuXGf\nv2sNA7PO+a+n9nbzNWAqXZor5qssvc/ftYaBWA5Nc/r8b5foce9a28CRsQFKhsV4qsC+3npePjOD\n16VjA5PpIneva1QTO2XV0zXBR3d2cP/6Jv74J6cwLZsntreTL1l88+1hDo8kWdccpC7g5qGNTXM1\nVk9OpOlpDEAWciWLaEBN7uZIKd8WQtwN/HPg1ypfPg7cI6WcWsK2LZsLK5qpgkG+bBH1X/oLH03k\nOT6epq8tTE/jpVkn8yWTw8NJAOoD7gW17oQQfOHuHo6Pp+ZS3c/X3RDA69IJep1smZEbyIgppaz6\nWbzHtrbR2xi8bO0c5eaZgK9yENiqpA38xw9v4Lceqv7v9nZVlpILURmGKZHSqU8lQJVCWCZSOplK\nLySgUpZee52f//xLu+c+lxLcuobXJdG11XtjU0tNYS9P7etGIG4qK+X893YpJa0RHw2VxWHnLFET\n6aJJ0bBIFwx2dEXZUDmznSkavHU+TmPIo963l0Dv7//wmt8z+EcfXoaWKPPVB9380afuWHCf1BDy\noAk4Pp5ma3sUIQSTlfqqHXV+Ql4Xe3sbiAZWdw6JRd3FSCmncTJjrjjJfJmxRIGZTImiafPgxiYe\n2tTMm+dn6W4IXDHpyo+PTpItmfRPZ/mn71u/4GLaPxjn1bMxZnMlGoOey2ajmsmUmMk4hakv9vFd\nnfRPZ+lpCNzQzfzJiTQ/PTFFW8THp3Z3zm0xW5WzFUux5SyBP3nuFOPJAru66vgPn7zjph9TWeje\ndY08/c4ICLhnXQNPA3/xizNzO3ef3tN9zcdQbkxn1I9pSwTQWe+bO6NSsmw8qzwWv1Zi2RJ//cp5\nNAS/8dA6NE1gWDZFw8aWqhhCNZRNm1fOziAEPLixGV0TtEV9DMxk2ayyJlbFC6em+ZPnTgHwBx/e\ncs3vT+TKfOfgKJYt+dTuLsI+F39/YJRErsyH72gnWXAy/PU0+ulpDDA0m6evLcIDG5u4f0MTB4fi\n/OzkNLaE9c3OwvMzh8Y4M5WlPuihPeqnLeqr6mtWlGoyLRtNiLn3acOy+ebbw7xweoY1DX6+fP86\n1jQGKJkW48kC46misxAinFXDvT31ZIomAbfOhpYQR8dSnJ7MsLlt9Y6Bi16iFkLcD/w7oLfyOAKQ\nUsp1V/u5WiqbNn/6/GkGZnK4dMGu7nq8bo1HNrdcM4FC2OciWzIJenXy5YUx7cfGUkigIeDhy/ev\nu2RFIFs0ODqWcr53PMVDmxbWFgp5Xezqvv6U91JKjo2leeHMFJYNY8kC8VyZloiPeK7M0/tHKm8U\nnbRHnSLYB4YSDM3muGttA13115/mVUrJOwOzZEsWWXUWqSp+VqmLiHQ+tmzJ198YpmBYTKWLanJX\nBUOzeWzbmVAMzuaxbEkmb2BJ55ySsvReODXNgaEEAJvPhjAtm1zJQgIzmaUt9qw43hmc5e/3OwtH\nIa8LW0qyRQOfW59bzVaW1k+OTjBYOc/7/IlrBzMNzObIFE0KhsXzxye5s6eO/qkMZ6YynJ/JolWS\nQhiWzd7eenIlk7BPx7RsQl4Xbl2nvrKjd24mR9Tv5uBwkrFkgQ3NQfw1TMimKIsxlS4ylS6yuS3M\n0GyOH747Qdjv5rP7uhmNF3h6/zAHhxJoQqALODqWZE1jgB8fnWQwlsPn0gn7XTRVjjaFfe65bLFf\ne3WAdMHg/EyO9c3BVXvu7mbij74G/A5wAFgRd/3pgkH/VJaSaVM0nSY3XmfYxCfu7GQwluO1c7N8\n9eXzPLCxiX29Tm2mXWvqef1cjPXNoUsmdu9UdvUS+TItYS8dUR8HhuJs74ziXWTK9Z+fnOJrrw5S\nKJts64zSFvHx05NTtIZ9zGSKZIoGLk1jIJajPeonVzJ5+cwMAAXD4pfv7rnGM7zHtiWpvInECU1V\nll5vUwBLOqsjayuF5hN5A8OyUXtI1ZHMlzAsQEAqX0ZKiVUJDcwbK2I4W3HcumAmU0LgFHkWOAmb\nwFmZVZbeifE0bw/EAbivUm91PFmkZNqVRCvKUovlynPh9bOXidS52PrmEO+OJDnenwJ5YZUc8mVr\nLtFbqmAQ8bn5zz8/y2SqiCUl7+9r4X/+8FbOzWQ5Np5iXWOQ+qCHQtmku8FP2Ofivg1Nqz78TFld\n8mWTv98/gmFJjoymODiUYCJdZGt7hLFEnh8emeDF0zOkCgYBr4uSafPXr57n4HCCgMdFe52zofHh\nHe18+DIldhqDHtIFg/qgU+dutbqZyV1KSvnjJWvJMqgLuNnbW89IvMDd6xp4tK/1usMVfG6d5rCX\ndMHJXjgwk6OnMcBPT0wR8bn5zQfXXTYRy8CMs4IX8bnZ29PAs0fGeflMjEf6WvjoDdSdef1cjLNT\nWfb1NjCaLGJLidetc9faBoZiOU5OpHn23Ql2dkUZnM3R3RCYC7vxujTqA24SeYO2yI2FZ9jSCc0E\nMNXNQFUEPG7cukAAPo9e6W8nZFAK1efVkC87O0ZIyJWcbJkXqMu8Otoifvb2OAtiLREfTj5Bh+rz\n6phIOdkTwUleY9lOVliAdFFl4q2Gdc1BXj/vlFnZ2BKayzp3JVG/my/e00O+bFE2baSAu9c3MBzP\nkywYICV+j85gLMtookAyX8bj0jkwlODN87PMZEqsbQzS0xSks86PlJKHNrVQMiz2VhagFeVWZNmS\nQ8MJ3LrGji7nfJxly7nFkelMkYaQh3i+jM+lsbYpRF3AjWHZeHQNr6aRLZkMzZYYni2wb209vY1B\nPrO7i/uuUOblIzvamUgVaQ57V3VOgxue3AkhLpzOfkEI8X8A3wXmlqeklNcay2rGpWv89vs3ksob\nl/3FFg2L6XSJ9jrfJRO1/YNxDg4n8Lo0wn43d69r4NBwkul0iel0ieF4fkENpwvuXtfAy2djnJvO\n8sMj47xZOeR8fDx13ZO7kmnx1nln9fWN87N8encnM5kibl3jsS2t/G8/PMGpyTQzmTIl0yLscxHw\nuBiczdMY8uLSNX7p7jVzr/tG6JpAx9maDbhX7x9CLb3eHyNbdEofvNk/W0nqoZM3LOpuILmOcv3S\n80KMnXBjdW1X2/auKCOJPJoQbOuIoM0bf1fxe2xN+d06Hl0DAV6XvuAqV5ul1dHdEKSucna/rbKL\ncCWWLRlLFGgKe/hkJTpoa0eEExNpNrWGefP8LAPxPNmiiSYEJcPA69bx6oKexiAbWkOcjzkLyGsa\n/Pz3t4awJXxsR4fasVNueYeGE7xyNgY4Gyib28KEfW4+vquD8VSBpoCHl/tjbGmL8MT2NnxunYlk\nEa9LA2zWNPo5MJzEtCWWlEwmi+hC469eOodp2zy06dLaqS5do7vh+o8mrVSL2bn7Txd9vnfexxJ4\ndPHNqT6vS6cppF12xn6h4n1PY+CSM3hvD8YpGc6hzi/s60bXNcqmzamJDAGPTvMVyhb0NAb5lYYA\nf/GLfnIlk/qAm57GwA2dsfNULsaReJ6mkId4rszvPr557jV01PnRhOC4TNES9mJUlsE98yaoV3vd\n11IfckI9WtWh7KqQyAUf65rgkW1t9E+mebhPFXauhkxlMg2QKhrM3zhS84zqCHldfHq3U9pD0zSs\nSkIbtWlXPY9va+XQiJPF+bGtLfwNToZSW4KuEgdVRWvES1vEC0LQFr76e+ZPT0xyYjxN2OfiV+/r\npaMyGbx7bSO2LRmK50gVypXfmSToddNZ72fXmjo+uauLNQ1BvnRvL4WyRf9Mhum0s85+ajLN3ZUw\nXEW5Vc3fRJlfVLy3KYjfo/PNt0ewpeSedQ0EvS4KZYODIwnqAk5oZVvUz53dEMuUaI142N5Vz/6h\nBAI4MJS87OTudrGYUgiPCCG2AB3AW1LK7IV/E0J8aCkbt9RsW/LMu2MMzeZ5cGMTe3reC1mwbMnZ\n6Swz6SKmfemSZl9bmMPDSWL5Mn/5wjke7WuhpylAT2OA6UyRr716nrVNQZ7Y1oavkkr9wpkpl67x\n+LZWTk6ked/mFsI+F33zsvQMzeY4PJJkc1uYvrbIJc8thODTuzsZS+T5v37Wz0+OTfKp3V18YGtr\npW0RxpMFtnfW0Rjy0NcWZl1ziI2VtMhXe93XomsCjy5ImLbaRaqStjrf3Hmvznrnzb1kWCSLJoap\nbn2rYXNrgFNTGQC2tIYYm/cm41qd56tr7tREmj967hQC+IMnt+DWtfcmduoyr4q+9gif39eNJgQb\nWsK4NA2PLiiakjqfKvlRDdmiwclJZ2zJl64e+npoJMn+gTjZkkm+bPHhHe2cmsxgWDaDsTzZokHJ\nsGgKebh/fTNCgA2EPTr/6adn6GkM8E/et57OugA9jUH8ngS2lHNntxXlVrajK4rfo+PSBOsuinxL\n5g1sKZnNlvhfv38Cr1tjU0uYkNfFoeEklm1TH3Txoe2d2FKSzJeJ+t08vLGZeK7ElvZL76VvJ4sJ\ny/xt4J8Bp4CvCSH+pZTymco//+/ALXsOL1c2GYw5SUFOTGTmJjljyQKv9cc4OZ4ikTcIXeZN79G+\nVra2R/hGZSXh5ESaqXSRgViOA0PxuQvu7FSW+zY0saYhwDOHx3DpGp/b201fW4TNrWFe7Y9xejJD\nS8RLS2VV79l3xxmK5zk5nuH3nghf9pCnEILxVJGRSlKTA8OJucnd6akMzWEfHpfGbz207pLsP1d6\n3dejbNrEUyVsnEyfytJ7p3I+A+CNc7OYtuS1/hgl0+bZI+P83hN9NWzd6vTGvD5/9VyMovHeTp6h\nwtWq4vVzsbkEE28NximU3+tzlcKmOvYPxnnu2CQAzWEvlm3P7ZgWTNXr1fB/v9hP5Vgjf/Fi/1W/\nN+J14XFpuE2NgmHx9P4RBmN5JtMFMgWDiVQRW0LBtJnKFtnVVUd71M9LZ6c5M5lhOl0k5HHx+09u\noSnk5SsPOsnKtVWcKEJZPYQQly0dBs551b299Xx7/yjxXImSaRPLlrBMSa7sjF0HBlNE/V56G4Po\nGpydzvLJOzvZ21O/arNgXq/FLN19BdgrpcwKIXqBbwsheqWUf84tHtEU8rrY0h5hcDbHnfPCIl85\nM8NYskD/dBaPrnG6sup2sZawj42tIcYSBXatqSNfucBKppPVyrQld3RG+e7BUfxunYBHx+9xMZYs\nUB/0MJUusX/QSQX+xrlZPr7LCVEaiOU4H8vRGDK42pi8uTXChpYQ2aLJAxveC7loDnkZSxZorpyv\nA6eu3i9OTVEX8PD+vpbLvu7roQnBhdgpeWv/eles4rzZRNGw0IRzHqZs2irRRJXMv681bJtbfOha\nFbobAuRKJkIIOuv96gZ0Gcxmy8zmnDIT8VwZhEAikEguE6CiLAFr3qBtWVcfwB/e3IJhS6ZSRdoi\nPibTRZL5MiPxAoZpYVhOFl+7aHJoKMFstsz7NjezuSXEa/2zZEtmZfxyqL8pZbXQNMGDG5uR0ikX\nYuTKFMsWscy8Ei4ChuN5WiJezk1lCXhdvNo/g6aBaUq2dUavWLt6tVvM5E67EIoppRwUQrwPZ4LX\nwy18hzSdLvJaf4wdXXU8sb1t7usXUg2PJwuV0gRyQQ07gMlUkbDPRdDr4iM7OigaFs8emaBs2jx5\nRxunJtOkCyaFssnbg3FSeYOAV6doWNzRUcfaRufwZtTvJlUoM5kusbe3/r0nqMTTg0TKKycXiAbc\n/OsP9ZEvWQuyfH7izk6mM0Va52XC3D8YZzxZZDxZpK8tvOA13whNgMelUTbsuUPiytKav1Pr0pys\nmfVBN7aUtKtzjlUxv1C5T9Mp3t6LfMvCtiRuXUPgZERT96HVd+eaeo6Pp9GEYEd3HRrvZT22VEaV\nqmgIeBhNOjvUTWEPl18qdnTXB9jTU093fYDepiBffekcU+kilm3P/X1oOFHLybyBlDmOhjzs6q5n\nZ1cUv1vnwY3NV3kGRVl5TMvmueOTxDIl2qI+/sWjG3jxzDRv9c9iI3AhQYOAx0XQo/PiqRmyJZOW\nsAcpJW+fjxMNeHhkcwtfuHtNrV9OTSxmcjclhNglpTwMUNnB+wjwN8AdS9q6mzSdKWLZkvaonz99\n/gxDszmePTLBf/2V3bhdOicn0jx3bBKXJnh8WyvposFMpkR3Q4Dh2TzdDX7eOD/LW+fjGJbN1vYI\nQa+LgViOqXQRn1tnJlOmaFR27iwbw7YpGCZF06JoWBwbT/FKf4wntrczkSrw6tkYBcPi61KiC8Fd\naxvorg8gJTQEPdc8ehLxuYlcdPbN49IuKUze3RDg9JST7KXxCslerocENJybACnVzUA1jCYLcx8P\nzeZxA4Wy6dQYLKh05dUQn5dQJZY3EGqLtOpOTWWc3SOgf8o5V6RUV3vUx97eejQhaIv4FvR5SXV/\nVcwfSeQ1hpWfHJ9kJJHn2/tHifpd9M9kSRcMskVr7nEu1L2TEizbJJU3+NGRcTrr/UQDHu5bf/mU\n74qyUr1yNsZPjk0ynSlRKFusbwlybCzF+dk8loSQR6Mj6iVvSCbTJUqmRcm0GIrnyZUtehqDlQyz\ntX4ltbOYyd2XAHP+F6SUJvAlIcRfLUmrlsBIPM93Do4ima0CGQAAIABJREFUpVPMsGhcCKG0MW1w\n4+zagbOSqQmNT+3u4tBwkrcGZvnj507xiTs752oEHR1NkS4YHBlL0RLyEM8Z9DQF+OC2VuJZpzBv\n3rCZSBTQhMClOxn5CoYTJwzODmDRsCmbNqcnMrw1EMfn0fnwjnb2DyXY2h5ZsqKK2zoi2FLSGPIQ\n8i7+4LwESpZziDtXVncD1VAw3rsDyJVtohJyJZuSaZMqmlf5SWWxyvMS1eQNG4+aaFRdQ8CNS3eK\nl9cF3NcMWVNu3qtnY/x/bwwhcOqdXi5ZmLK07Pk1M6+xaDSZLvDi6WlmMiWawx6yRYt82WL+b0ni\nTPBsJG7dw1jSOWcXzxls74jimZcByrLlqi7MrKx+qYLBj49O8O5IgulsGQ1IFMqYlj2XeC5ftgn7\nXIyn83h1DY+ukZUgbCcZXV9bmO2ddYuOWFsNFpMtc/Qq//ba1X5WCNEBPAtsBUJSSlMI8Wc45RQO\nSin/5Y2250pSBWNu1SyZN/jtRzfw7JFx7l3XiN+jA7Cnp55cyWQsWeC54xN01QfY3hnhe4fGMC2b\nnxyb4At391A2bbIl5/FimRLxXImo303ZtPi9bx8hmTedMEzTCaUwbIktnRNqHl3M1RPa29vAgxub\nOD2doadSZyPkdTGeLDKRLBL2utnRVcf5mSy5ksXG1iDTmRKHhpP0NAZvqHzCG+dnee1sDLdL40v3\n9tIQ9Mz9m5SSM1NZ/G6dNY1Xr/chpeTCht21ViGVxblQRxDgQilBty4omxK/W8ULVpvACYct17oh\nq9yGtjAbW0IIAeuaw7h01efVFsuWmEoXEThn7nRNjSfVVjLnnaE2Lz+ZzpdNzk3n0IVGT0OQmUyJ\nQsmmrc7HeDJ/yfdLwKVpSAG9jQHKlk19wDOXVM2yJd85OMp4ssBDm5rZvab+ksdQlJUgXzIZjucp\nGBaGaeNxCVyawKu7uFBS2waOjWUo21DWbR7f1kK2aHFoJIXf4+IrD66jLeqnfBsv2i53LuQ48H7g\nezBXED0kpXxQCPH/CCH2SSnfWYon6msLk8iXMS3Jzu4or5+bBQRjySJSSoQQ+N06XfUBTk9mEAjG\nEgX62kJYtiRdNBhN5Hl6/whSOuEtfrcgVzIpGRaZvEEiZxD2uXDrgqagl6DXhd+tM5stoQmNsiUJ\n+9zoAsaTBTrq/Pzhp3dg25LxVAEpnfDJF09PA3BmKsOaUT9//NxpskWnrlyuZODSBE0hHxtbQpec\nB7ycQtni6GiKA0MJ3C6Nj+zoWDC5Ozic4OUzTuHIz+zpumpBR2fF0HGlNypl6Zg4Zy7LpoVpQ7Gs\nMtpVmwRMtYtUdQKBUcnUqKH6fDkYls1stoyAuSyZSnVNzAuzH40X8Fz076m8wX/80QlyZYuGoAdN\nk7g0gSUl56dzlOYN+Rd+X7LyX2PATVPIy0AsS65k8u0Do/yrxzdTNCzGEs7znp7MqMmdsiJJKXnp\nzAypgjG3QWNYknTB5OLklxfCyg1LMjCT59G+ViKVvBDPvDvOTKZEyOvioU3N7O29/gzxq8WyTu6k\nlEWgOK+Q9j3ATysf/wy4F1j05M60bOK5Mo2VrJHzDxqfm3bK8Q3H8xiWxOMS7B9K8Fp/jFi2RNTn\nZkd3lNawj/vXNzKaLCClrAyiFvuH4mxoCVEwLIQAoQm2dUQ4PZVFCGgO+8jHc7h0QdG0kdIm4tXx\n6IIjYymOj6dZ1+ysWvs9Oo9sbqGjUtNsT08DB4bi9LVFmEg52bJi2RKxXBHDkjQGPNjSeaM+M5Uh\nmTfY2R2tJICZ61t+cWqaM5VzLaOJAiGfi8agh3SxjGHZcwUj568sli2bqXSRczNZtrRFqA8ufCtS\n52KqT2jMzaD1SoHhXNlG4mS7U6rPUudJqy5fMhlP5BECCoa5IHxNqY6DIwmSeWcMOTScWJDJUamO\n+bVJDcu6ZHL3+rkYI4kCli0Je1yAoGjYpIvmJWGzF0IyATQkQ/ECiYJBtmjSFvUxHM8T8bl58o42\ntrSHGYkX1MROWbHKls1EqsjapiDnZ7II4fwtpYvGFRcDhQBNF7wxEMO2QSB5ZyBO2bK5b30TXfUB\nNbmrgTrgfOXjFLDt4m8QQnwFp/wCa9YszHpjWjb7hxLMZEpMp4sMx/NE/W68Lp07uqLs7qmfO292\n7/pG3hmIs6k1jMelkcobTGecunEuTfDAxkYyRZOvvzVMyKezrT3ClvYwL52JcT6W5eREhncGnNpY\nHt3Z8WuL+lnXHOLIaJKxVAHTcrJd+lw6ui4oGTa2YfPa2Rlcuo5LFxwdS9PbGMCtCT67z3k9e3rq\n2dPjDMgnx1NIJFblsTQBCOio85MrWfzwyAQAuZLJ2qYgvzg1TXvUx51r6jgymmIyXSSRK9PdEHB2\nKIEXTs5wYjzDL9+9BiEE+3ob0IXA79FZ2xjkv758jpJh0z+d5Uv39i7sY3UzUHUBF6Qrc7iwF0rW\ne4fpy6r/l4UmNFVrrcq+9up5huLO7sLfvjaArgnUidLqOj2RnjuncmI8dcVMzMrSkZXSQXDpUYZ0\n0eDFM9OMxJ37jpJhMpMpUzKdMd+4THTMhYcomRJNs4hlLQIeF9mSyYbmEG8NzDKdKfGRHe08sb29\nmi9NUZZUPFfGsiXNYS+JXJmDwwlCXhfrmkMcG0symihWxq9L74NcwpnYuXTBZLKI36NjWpJcycSq\n3PsatmTf2ttvYge1n9ylgAtl5CNA8uJvkFJ+FfgqwN69exf8ht8dTfLGuVmOjCaxbEmiYLCzM8r5\nWI6yZTM8m2dzW4hfnJqmZDox6t9/d4yvvzlErmxRNi38Hp1i2eKvXj7PuZkc9QE3I4k8TUEvn9vX\nzW89vJ4XT09zciLt1HmT0Bz28Ni2Vp7Y1s6Pj00Qz5fJFU1i2TIBtyAS8NLXFqEu4OaVszMUDBu7\nbJEpGpQMi4mUU/x8IlWgPepf8Hpj2TIhr5tiwMYlQNc1+trCNIW8lE1n11BKJ33+gaEEqYLBSDzP\nbK7M6ck0qYLBxtYw2zoiPL6tjaffGSFVMIhlS3M7lm5do6POj9etIQTolXf8yx3Elmp1vepy8zbn\n0kVAhb8uKydkTfV5tU1VElgBjKeKahdpGZydV7P19ERaRWIsg3llSylaEJr3b4lcmXzZoiXsJZ4v\nMZoozIWfWfJyt7DzVOqfgpOopSnoxe3S8Ll16vxuJtPFq/20otxSRhN5vnNgjLJl0RH1M5LIc246\nS7JgsKk1iCXlXI3lyzElaNKZwJXNMr6yTtTvpiXixbIlEZ+bf/XYJtY2BZf1dd0qaj25ewP4LeBp\n4APA393ID18IS8wUTWYyJWwpGYjl0DXBYCzHuZksPzgyTr5ski6a7OyK8MLpGLbthLw1h7zY0ikc\n7XPrxLIlErkiBUOSL5n8+c/P8vyJKXZ11tEc8hDLlslrkC2Z/O1rg/z0+BS//6E+fnZiimTBoGza\nhL3ODt3Dm5p5pX8Gw7IpWzY+l/b/s3ffUXJl92Hnv/e9Vzl3zo1GzmGAyYGcGVJMMwwjiiJFBVJU\nWNnSSvae9a693j22ztFaOj7iepNky/ZatuRAymKmSQ5JiTPkcBKAAWaQBqmBzrlyfOHuH6+6kRro\nBtBVhS7czzlzBqjuKty+dfvW+7177+/HZx4a4NUL7l228WSR//TaZfb1x9nbHycR9OLRNYbaQ2zt\nDNMW9lbP8+mEfDrposnXj02wsT3EUFsYryEoViyEgMsLeZL5CslChQcGWtjcEeaFB/oAeHp7B0cu\nJ9naGV7KqvX2WIrvn5pGF4JPPzTApw71c2k+z+aO8A19rK6/au/qFSNTQlDTUAUQ6kfirlDrK36n\ncjc+ureb/+uH5wF4YX8v/6zB7bkfXB3K2YCmlu4aqj8R5LFNbbx4coqR+TxzefNW16/XcKSbfCsa\n0LEcd+eNlPALDw0yky2pkgjKupLMmzhSMrpQYDpdJl00mc+VGZ4vcGoiTbHisNKtqKu/3hLy8PMP\nDrC1081Nsas7Rjx0/abo+0ddgzshhAf4DrAP+B7wj3DP4P0YOCalfON2Xm93b4yAV2c6XUIImEoX\nGWwNcvRyknSxQkfET9CrkyuZBD0649V97m69GHf5drAtRKrgrqhpuEURS6aJI92UqsdHU7w1kiTo\nNXh+TyffPjFNsmCChOlMiW8en8C0HRxHousCw9AJ+wz+8rXLXJjNLRWi3tsXZ3NHhKH2MN87McV3\n3pnk/GyOS/MF/subo5RNh4eHWvjZQ32E/R7yZYtC2aI75uHgQJzXh+dxpOTVi/Ocmsxw5HISr6Hx\ne+/byvnpLBPpIiXLIeDV2dwRpmTabsKWROCaOxeX5/O8fHaWN4fn8eg6T21zM2tdf9ZukcqqXH8q\nlXX9mZatgrsae2hjK49fTiEEHBhsoWzaeFZ+mnIX4kEv01l3a0BLyMuEWrlrKE0TfOahAXZ2R/jc\n//fmqgO7RX6vwOcx6Ap6aAn72NUT5YktKqhT1p8d3RHmcm596B+dmSFZNOlv9VMybRxHrhjYLdIE\n+AzBY5tb+dj+3lsmCLyf1Duhiom7Qne11+/mNTe1h/ngni7+5vQMvfGAe2EsBF5dYypd4sENLXxs\nXzcvnZ1jJltCwz3HFPRqtIZ95EoWHREf/S0B3ryYpOI4hH0SiSRXsnGqU2+2ZHFuJk/RtJcCxGzJ\nwu/RkNKtbeM4krLlrvotMjSN/pYgz+7oJBH0YjoOvfEgHVH/0nm2t8dSCNzEKz88PU22bJEpmlRs\nB9uR/ODMDBG/hwP9MVKFCqcnM8xlK8SDHkYXCmzrjpIIlemM+vjUoX7+6sgYf31kDEMX9MQDfOah\nAUI+g/FUka8cHefCbA5d0+iI+vBdn4Loxvfsbt4e5Q6om+v1J9W2zJoTQLJQASHQNYFU2wJq7qoS\naBhCqIyZ94jOaICBlgDZcXPV504NDVpCPnriQbpiPn7nma30JQIrP1FR7kGGrvH09g6OjyaZyrqF\nyC9OW3gNjUxx9aexgx5BTyLE8FyB//DqJX7lsQ30JVSA1+htmWviPVvb2dwRJh70YmiCP/7eu5yd\nydId8xD06cwXLC7O5ZlIudXrfYYgV3bwFCpEfAYL+TJzuRIl28bQNFpDHiSQKxevua3mflAKdOGu\n0rWFvXzt2CSFsru1wpFuvazxVJFowINlO3gNjfdt76AnHuBH787yzniKomnTGfMTD3o4PZmlYjlY\ntqRo2ZybzWHZcmkLpV09X5cvW0ymS5yfybl3NqTE0AUTyQI7e6L0RP2Ubcm/fOk856bzpIoVBltD\nRPwe5nJlQj4Dq3rXtjvmpzXkZVdvjE0dYSbTRS7O5tneFaE17Kv326dcRyWxaQAVUdfcf3tnilOT\nGQC+e2ICFWXU3tU3GnMV083G28D2KK6o3yAa8OL1aFjm6t4RrZpJuT8R4L3bOpY9RqEo600s4CXk\n1bEcSTzoJVc2SRdXfh64JXV64kHyZYtUwWQiWcRn6Pz2M5vxe+7vvThNEdwJIehLBJlIFTk5kWY2\nVyZTNJFScvRymW1dkWrRTw8L+WpKVeHWWSqZDhOpMhI3G5VPd7dOCCGuOW8mgeH5PLrmnlsQwHS6\n5L6O4068nmqGzJLpkK+UEYDuSL52bIIvHR6jYjmkiyaxgIeI36BsOhi6ezdV18Bx3Bp1fo/Gvv44\nUZ+OpsHJiSyZksXoglsvL+Qz6E0E8Gga33x7kq8em+ChoQRzWZNowCBZqJAIekkEPWzriizdxRhs\nDfEzuzpJFUwsxyHs8+DRBF85Ok7FcrNl/spjG67p22LFbo5Bso6oFY36s9R2tZp79fzsUq6gV87O\nUTGtG9LEK2vLdK5E0JaD2grbIFJKjo6kKFZstnVFODGeomI5btKIVTJtaI/4eGJLGx/ecyUrZqZk\nki6Y9CUCCHWTSllnPvvIILbj8PK5OQ4NJvjx2RkmM6srAeUAZ2fy6AKCPp1E0E+mZJIpmSq4a3QD\n7sbilsF00eSN4QW+e2KKyXSRE+NpDF2jULYIenVsR9IZ9VGs2LQVLLJlEyE0fIZGyKeTKgqKFfeq\no2zjLpctsxN+MuOmudC4UlT06pTHli2pYC2lnl4MGOdzZaazZaSUmDZkiiamI9GrNe+KpgNIJO6d\nuaDX4PHNrZyZzPLOeJqY3yBVtDBt9/sTQQ9SwniqSLZkYjmSZD5IoeIQD3jY2x+nK+rn0GCCrV0R\ndE2QKZnMZMps7YzwxsV5jlxKIoQg6tfx6IKKxVIdvMV+FUKoM3cNcDsf+MraqKic/DV39VlSXReY\nqvZEzRUrVzq5ULQxHUcFdw1wYdY9614ybb5+bJzXh+eYSJVuKzGyBEYXcvzrly/y3RPT/MMPb6ct\n7OMvX7tM2XR4cEOLOn+nrDteQ2M6W2E+X+FLh0dJ5W4/66stwTQdBBq9CT8dEX8NWrq+rMvgrmTa\n/NsfX+TyQoGI32AmW8bQNF49P4cQEsuRCCERQmBLGE0WiAW87O2NcORyEumA0GwCtuYGWra8rUPN\ny83Hi48Vr7tgkeBO4tItUA3uRY7pSCwHSpaN41xJXOLTIeI3mEgVmUy7aZJT1ZW492xtZTxZZixd\nYGd3hCMVm6Jpo2mShbyFpgnaoz564j6SeYv/+2/OE/Dq/JPnd/KnL11geDZPPOjB79G5PO/23Uf2\ndvOpQ/2MLBTY2B5mNlvmK0fHEAI+ebAfW7rBrFI/KrSrv5vUR1XW0K6eGKen8+6fu+P8UC2W1tzV\nH0cVbqy7ptRHwKsjBJQtByHckkd3UvFmPm+TzGcZTxX5s5cv8lvv3US5uq1zPl9e4dmKcu9xHEnF\nslnIV5jPlajc4U0/S0r6WwIUyg7zufJ9f8RoXQZ3pycy/PjcHKliBUPTKFVs0iWTdMki7BXEAjr7\n+1o4Pp4kU7Qom4KUrFTLJVRX3RxIFtyzctZNPvAEbkB2s6+vllUt1xH161gOhLwaXksjV7awbDcw\n9OmgIwh6DTy6xvBsgWzJIuQ1CPt0UkWTl87OMZ4q4fdoBDw6XTE/+bKFg2RHd5TDl5McH01xatIN\nWiuWgyMlb4+l+Mm5OYqmjVfX2NkTdftOF6QKJls7I8SD7gapk+NpCtXfruG5HKZpqTu9dbZcIVul\nttQiUu1Npa/ckZ3KFdXZrwZwVOKghuiNB/iZnZ28dHaWhbzAcwdbYgzcawUJFEybC9M5/vrIOENt\nQbyGzqMbW9e62YpSc68NzyMQVCwb6y4+iA1d4DU0fB6NgPf+3pIJ6zS4awl5KVk2yXyFii2xbId4\n0EOh4p6TM204N5tlJlPBllA0HTyacGtZaQKzept+pbv1+iq+53ZEfF7m8mXSJQvLdjNuCsCjCQZa\nAqRLNqbtMJ4skixUCHh08mWLhXyJfMVZStoigIot2dEdZi5XpmjaTKVLCCRTmRKagFjAQ7Fi05MI\nMNQWpmzaFCoWobCfsNegI+Ij5PNgXPchs60rwpmpLELA5o6ISjTRAJpKeqA0obFk4cqfFwoqoG4A\nR3V6w1yaL1AyHU5PZqjcwVWsU62bEPRqbGoP0x714UiJ36Pzwd3dKz5/PXhrJMnpySwHBuLs6I42\nujlKDZi2Q6Zo0hLycvhyktcvzPHWSNK9Jr7D19SAHd1R3r+zk6e3dxL0rsvQZk2tyx5IFU3ms9Wk\nKQDS3eZQNh3ygKHZlE3nSkKUahX7N4eTS4HdaqzVMRxdgK5Bb0uAmVzJDdCEIOjRKFsOfo9Od8zH\nWCpdLaruULJsYgEvZUuicX0xcUmmUOF7JydJF01A8EB/nGzJJuDRSBYqZEsWEb/ByHyBf/3yBQxD\no8vvpyPq50N7u5lIF4n4POzsuXYCjQe9PL+vB4EbIKpEE/Vn2o6quaY0nZnslZW7iVThFt+p1Moq\nEzMqNdAV83PkcpLRhcIdnfF1JER8Gn0tIT6wu4t4wIvlSPb3J9a+sQ3gOJKXzs4iJbx8dlYFd01o\nLFngz16+iKEJZjIljo4kyZQsTNvNQXGnwV1L2MuDG1r5mV1dKrCrWpe9MJstUagGb7Z0o30fYmm1\nw3IgGjAoVgt5e3So2FBq0MEaTUBfS5CtHSGOXE5iORKfQfX/GhXLYSRZpmg6S2ciPLqG3yPoi4cA\nh+Pj2aXX64j6SRZMcmULXRPoGpyfyRHxGxQq7i+K5ThYjsSra/g9Oj5Dx7QdKqbDaxfneXZ757KH\nry/N5fnasXEEghce6EUlbqy/imWjqhcpzaZw1QVtbnXJ0JQ1phJkNc4DAwleencGj67d8aq1I+Hx\nja08t6eHwbbQmrav0TTNzXo+ulBgQBWibhpSSsaSRSJ+g78+Msa7U1myJYtcySRbsihW7LveIffA\nYILfeWazCuyusi57Ih70IoSbX1IX7jbLwnVnCVKFCkGPhunI206YstZMB+ayFU5MZJZWDh0paAl5\nSRcqSCnJlcxrAqmAR2cwEWJnb5RcybwmuCtVb78GPDqaLnBsh4otGU8VMDSNfNl0k6uEvfS3hOiO\nu5kzbSk5OpLk1ESGTe1hHt/cekPq5LlcGSndvp3LlVVGuwZwVEStKEoNqKml0e48uhaA39B56ewc\nZ6az/NqTG3nvtg7Kls0r5+fw6BqPbWpD1wRSusc+tHUWzb9woJdsySIaWJeXpsoyXr04z+sXF/Aa\nGpfnC6QKFXJli0TQi42kZN59cHdwIM6rF+aJBTw8NNSiSoKwDoO7bx6f4G/PzICUeDSNiiOvOZ9U\n3ZZOwVy+nEGjFCs2XkNbapHAzYpZLFfIWXIpYAN3G2fE72EiU2ImV2Z3bwyvLrBsiRDu3dd9/XF6\n4wEmU0VOTqYxLYtCxUYTDkIIEkEfnbEADwwm+IWHB3j57CzHRlPs7IriNTTeGklSMm0+9WA/Uf+V\nlCm7e2PM5ysI3Ox2mkqVWXe6rjpdUZS1p6aWxjrQH+Old2fu6LkSSJcshIBEyMPJiTTv3dbB0csp\njo+mATcfQX9LkC+/OUrZcvjY/p6lOrfrgaYJYkGVwq2ZpApuCbGKZRP06ezpjXF5voCmCaIBD7mi\nSbp0d6sIL52dYypdYjJdYiZb5vl9PWvR9HVtXQV3UrrbD2MBg4DXAAFm0bz2exrUtlvxadAZ89Md\nCxD2ZTBth/5EAOlILCmQuOURvLqgJWBQsGwypQo+w63R99rFebZ3RWgLe/npxQXm8hW6iiZJr87w\nfAEpwevR8eoaQoDP0NnRHeHTDw2wrz9OW9jHCw/08dF9PbxxaYHXLs5j2ZJsyWJsocjOniuTqd+j\n84FdXUt/19UNkLpTXa4oSi2okh+N9c54+o5XFQTg1SHs99AR8S0VMk+E3M9vUU2kNrrgZtoG93pp\nPQV3SvN5YksbmhC0hb1kSxbfOzlFb8I9eDKfL2Pd5XYCAUyli5i2g6FpvDOW5tFNrbSpUgjrhxCw\nvz/O6xfn2dYV4fxMjmzJ5urcglGvIFtxB4tXF9hS3lE9mbUU9hs8t7eH/f0xXj47C1KSr9gUq/8J\nIdjeFeGZHZ2cmsjw2vA8+bJNvuyenwv7dBbyFR7d1MapySwVyyFdsiiYeTIlE9tx6Ij4yZRsgh6d\nzzzUz+ef2HhDO4zqto3NHWG+/fYkAY/O0Ar79g11p7fuDHV7XVGUGlDzeWMZmnZHmTLB3bFjaBpP\nbWnnd57dTNjnBnXbu6LEAh4MTaM94qMlZNEV81My7RsSpt1vNvzP3250E+57Ub+HD+52FwzyZYsj\nl5PkSia2Izk4mGAhW+HsTPaOkz15dEE86OHpbR2kiiatIS9h37oKbWpi3fXA09s7OLQhwX98fYR0\n0WQmc201+3jQS8QvCPh1MkUTDUG6WKF4t8XqbpPGlZDTa+i8NjyPpkn3wt1yKFRsbMf9u6EJWkI+\nwn4Pv/DwAOdmcthOiZDPQ7pQwXJkNTmMZFdPjELFPYQ6mixgOxLTcrg0nydftgj7DIbnC5RMm8OX\nksSDHnb3xq5pW0fEz+cfH1rVz6Fu9NafpvaLK03Ip0O5el0bMtw5Uqkvdd+osT66v5v/8sbIbT3H\n0HBLFglBLODhrdEkf/TdM2zuiPCLjwwS9hl0x66k4Ap6DT7z0MBaN11R7ppH1zg/k+XUZIbuWIAP\n7enm4w/08pPzc7x6fo7KHQR4QZ9OIuDhkU2t9MQCRAMGfo/KN77ugjtwz6N97rENzGaKHBtJAu72\nwUTQw289vZk/e3mYhVyF1rCPdLECQrB42u1mY8cQoOsCn6GRuW7/7+I5vuX+fv3Xrn9Nj6ER9htM\npUu8PZ7GdiRBj47PoxH0GjjSbXt/S4CfnJtlLlfmub09BLw6hYrF22Mp0kWLdNHE0DXev7OT/pYg\n3zg+gWk7WI7DbLZCwGuQLlrEAh4CHp2fnJvjnfEr+/B74jfPv1is2Eymi/Qlgnivu7WrfknqT8V2\n9adOedReyKdTLrhzazjgwafGed15DdXpjfTF759jIlO8recIASGfQVvYR8hnkCtZTKRK9MaDpAoV\ntUpxj1jNKuGlP/xIHVpy7zJth65YgKlMiVShwp/86DxbOyOkCiZej45Ztm9rQUHX3JXBWNDHZKrI\nm8MLdMX8PLe3B32dJRNaa+t2VvB7dE5P5ZC4d4AjPp2wT+cvXr3MQqGC39BJ5t1VL6TE0AWdUS+j\nyfINryVwtzwIIOQ1bgjuvLqgfNVhhZhfw3IEYZ9BxG9waT6/tKTsr37vYuKThF/n8c2tvDOeIVu0\niQQ8fGBXF2Gfwf7+GDOZMrYD+Yq5VNy8NeSu4AF8/dg4F2fzOFLy5JY22iN+cmWTJza3cqA/RsWS\nnJhIIdB4cFCwty/OB3Z3LR2w1oS4IWC7mpSSL705QrJg0t8S5JMH+675uq6r4K7eDE1bsxqLyuqo\nDMq1p2saVJPAG7qOrvq85q7eQeIRUFIVNBvGcSTHRlLczq5MXYBP1/DqGq1hLxGfh7awl6G2MA8M\nJui9xU1bRam3d6eynJ/JsX8gvuzYDPkMnt/XTb5o9JI+AAAgAElEQVRiMZUq0RL2MjyXZzpTQhOC\nK58QqxPy6Ozvi/OFJ4Y4NZmhULG5OJtnPlemI+pfs59rPVrXH6/7+mIcubyAlJJowEOqaBPxe6mY\nDrbtgBB4NDf7oA4Ullnz9WgCKdy7yrmSTbZoogs3ZfRiOBf26ZSvKtIkEfQlAjy5tY2P7OnhN/7i\nMPN5E6SkM+ajUHGHZ8l00A2DBwZa6I4FuTxfwHIcon6DFx7o48jlJJfmCyQLFQZbgnTH/DiSa/bJ\nf3B3F+dncvTEAjhS8pevjeBIycNDLTy/rxeAyXSR1y7M88im1qXtGY9taqU94iMaMG55sNSRLB2+\nTl+XnAbcRC9qa2Z96bpQwV2dBdXd75oL+wxmc+4cE/bqhPzeBreo+Xk0KFc/9jyGe3GlqtvUXzJf\n4ZtvT5AIedDnYbWnRGIBDz3xAEGvzly2wq7uGF5D4wtPbqQlpH5/lHuHBL57YgpHSmazJT53k6M/\nBwdb2NEd5ctvjpIrW1yczdEa9hIyHaJ+nbHUjQswN6Npgk8c7GNXbwwETKRKdMV86neDdR7cPbuj\nk8l0ibNTWUxHEgVyZXdrotfQSBVNEIK2sIdkvsJShXDcrFMD1W2ImbKNdCQVS9IZ9VG2HAxNMLLg\nbp/oiQfJlbNLq3fZkk3JypMY9/HAQInNHWGcqQyWA09ubWc2U0YCC/kKYb+HvkSA9+3s5N2pDH97\nZpZc2eLf/GQYn67hSMnIQoGgVyfgMfjtpzddk1DDZ+js6nHPzI2nijjVn2ExgAT3FypVMJnPV/i5\ng/3Egh40TbCtK7JiH+qa4MN7uzk3nWNPX2zZr6tAo76EypdZd1L1ee1d3cVC4Eipzt3VWEvYy2TG\nrRjfFvYzpQkV3DXAlw6PcmI8jQTaIz6KFYvUKtK/7+qN8nvPbuXb70wiNLe2bdBnEPSqFVjl3iKA\nWMAgWTBJrBBcBb0Gn3t8CCklXz48yky2jM/QOTedQRerz+ob8Oi8Z0s74Jbu2tkdVTXuqtZ1cJcI\neTB0zT3XZmhMp21ifg9CQFfMz75QnIjfYDJdomLZlC2JpzpBtkZ8vH9XF6Ytmc6USBVMFgoVwj6d\nmWyZimkT8ht4NMFQe5B0ySSdL5Euu6POsiRly+bcTJaP7OmmLeRjJlsiXbT44J5untvbw9+cnsHv\n1TgwkEAIwUBLCE2bYypVIl+22dwRZkdXhIHWIJOpEm0R7y0zJfbGAzy7o4NUweTBDS1Lj5u2g2U7\nvH5xgWzJ4vHNbTw01HLNc0cXCowuFNjdF7umrh3ApvYwm9rDy/6bfkMnd6dvkHLbdMBnaJRW/E5l\nLYW8OpVGN6LJhYwrF6Qhj8CnayrQqLHPPDzIF79/DoDPPjLI//mXmhrndWTgrmjYjsRvaGRLFh5d\no6s9zDtj6Vuu4GnAh3Z3cXBDCwc3tCCl5Phoir6WoDoLr9yTPv3QADOZMj3x1W2JFELwsf29dMcC\nxAIevvjiGWazZUqWXHHHWNins7EjjHbV2ToV2F2xroO7mUyF3rhbL65iO1ycy2HmJGG/wb/4+QPX\n7Ln95J++woXZHEK4RTL39Mb4nz60g/lcmW8cnyBVcFOzDrUF+dKbo2RLJj6Pzr6+OJ99ZJBfegS+\ncmSM756aomRa+D0GRdNmdKGAJgRfeHKIvzoyRrZkMZkqcXk+z+mpDLoQbO+K0hn10xr28dzebk5P\nZjk3nUXXBHt74/TEA8xmyyQLFf723Rke6E8sFfJM5iscG0sx2BJkY3uYvX3xG/rh4/t7efPSAmXb\n3X8zlixcE9yVTJuvvTWO5UjGUkU+dah/1X3c4CoS94WeqJeJ6t31wYSPGak2wtZayIB8dUk65hNU\nVBrBmtOv6mOPR8dj6Cq4q7HTk1kWr33OTGbxqMKlNefRWDqDb7jlePn4gV6+9MYIiZCX8WSRqF/n\nwmyWTOnmn7DtER9HR1I8uaVAf0uQV87P8+alBSJ+g198ZFAFeMo9x+/RGWi9vbqKfo/OU1vd1bf/\n5SM7+fyfv8F0uowtl09WqAtoDfsIGBD16fzN6Rme2dGxBq1vLus6uNvTF2M6U8K0HcqWTTzoRdcE\nG1pCNxymDHh0wj43Rer7d3bx7I5OwB0k79vRySvn5xhoCbKvL84bl5LMZkps64ow2BpiOlOmLxHg\nHz+/k1A1gYpbdFzDcsC0JT5Dx7QkuZKFaTtMZ8pICZaUzGbLdFbbs7kjwuaOCPmye2UZqp71CfsN\nvvTmKI6UzOcqS4lNXjw1xUSqxNujaX7jqY0EltmO0RH18+E93YT9HqbSRR7d1HrN14Vw9ybjSLy3\neRGrLnlr79FNbXz12AQAj21t56sqtqu5Z3d28o23pwH4wO5uvvM1NdJrrT3qQ5uo/jnsw6NWqGtu\nNltmsUbwbLYEQixleFZxXm10Rr2Mpdybdd1RP1ncXTe/9OgG/vbdGQ70J/jeyQmQAq8ukFfV4tWr\nZQ803KRsM5kyXz82zm+9dzPT1bJP2ZJFvmyp4E5pOj3xIJ3RAMm8ScV2kPJK/gsBRPw6LSEf7REf\ntu2wULB4+ZwK7pazroO7sM/g4wd6+dpb4wzP5Xl4qJWB1uDSHtyrPba5jYDXoDfu5++9byuRwJWt\nif0tQT59VV2YP/j4biq2Q9Br8K23Jzg7neXsdJbuuJ9ff2oj48kCU5kyuZIFQtIe8bOxLcTG9hBd\nMT8DrUH298dJFir4DH3Zs2+h6xI4GJrAYwjKpiRw1aQdqKbx8xraLVO7CiF4z9Ybf25wz+196lA/\nE6niqs7hXc1j6EsZ1wIqjXZNPL+/lwtzeQTwoT09fNvQKQMWbhZYZe09vqWDk5M5BPDIpnZerCZd\nsoGARwV6tfCb79nEaLKIQPDrT27ip1/UiPoN8mWL7lVu41Fuz6MbE5yolsR5ZGMrpzWN3rif+XyF\nrZ3Lb8VX7s6TWzv48ptjALx3RyffrD7eHvHxqUP9vHR2loWCid+r0xr28dDGBOPJMroGYZ+HkmlS\nNCVtYS/dsQB+j44m4MktbbxyYY7uWIDWWyRJU5T1Kuw3eH5fD+PJIomgh6H2EBdncoyniiRCXj79\n4ACdsQB9iQBfOTpGumiyry/R6Gbfk9Z1cLfoqa3teA2Np6LtHBxc/o3+/ONDvHdbnp544JrAbjmG\nri2dfVs8n+Y1NAIenYjfs7QKd71PPzjARLrIxvYQPkPnub09q/4Z/B6dzzw4wHS2dM35tw/u6uJC\nR47umP+WJQ1W0h5x73ZcmsuTK1vs7I5es1f5ZnRN8HOHejk6kuITB7rv+N9Xbu6xTW3YjkQTgoeG\nWtE1wa8+OcTJyQzv36nuSNXCJw70MZ4qYQh4fl8P/7sm+OCeTk6MZXhuX1ejm9eUHtzQyr/6xUNo\nQjDQGkQTgj/4+G6+f3qaX3lsQ6Ob15Q+dqCPsWQJTRN8ZF8vfy7g9z+2i5fOzvFz15W9UdbGF57Y\nyFy2gqYJfvnRoaXgblHUb7C3N07QY/DIxlY+dqAXnyH4wekZNrWH8Bo68YCHaMDD8Fye3kQAIQQd\nUT+fOKDes/VM1cJb2ecfH2JTe5gzUxme39fDt45P8OqFeTa2h/nkof6l6+9N7WEW8hU2d6ibVMtp\niuCuJeTlw3tuHXj4PTo7uqO3/J7lPLmljf6WIImgh4j/1kFhLOhZOit3JxIh7w1ZhryGdkftXs54\nqshX3xoH3Kyij2xsXeEZrt5ECJ/HIBZQd9drwWtoS9uEF/3u+7YylSnRn7i9/evK6pybySJws3Jd\nnM0DsK0rRmvYT0881NjGNbENbdf27Xi6xFBbmPMzOQ4OttzkWcqd2twR4X/84HY0IeiKufP32Zk8\n8aCXk5MZdi9zhlu5O5s7IvzTj+2+ps+vdmAgQVvYh9+j0x5xV+C+884kF2fzjMwX+NzjG5auNdbq\ns19R1pOntrbz1NZ2Tk6kyZVtBltDPLuj85qFlcUFC2V5TRHc1ZIQgqG25rjYs6/KL2s7qzvYJXFX\n7xJBr6p3V0chn3HTDKbK3bOu+l0wbUeN8wZYzCII7rllpTZ6riomrPq8PnpWKC7e33LtTTur+p44\n1TNGyv1Lre5dsThXRQMeIn4VrtwO1Vv3kYHWIB/Y1UW+YrG/f3V3bAXwwgO9DM/l2anuIipNYk9v\nzK2zJgS7eqJqnDeA6vP6U31+b3p2RwdtYR9dMT+xFY6NKMpKAWCzBH+7e2JLR1Z29aj56nYIuY7S\nrre1tckNGzbU5LUXL/SUa126dIkNGzao/qmjxT5Xamtx6hNCjfNGUH1ef2puqY/l5haltlSf15/q\n88Y6cuSIlFIum4xjXa3cbdiwgcOHD6/56/70whyvX1ygPeLj0w/237KQ+P3m0KFD/IN/+VXGk0X2\n9cd4Znvnyk9S7sqhQ4dqMs6VKyZSRb5ydAwhBJ882MdHnnlCjfM6U3NL/am5pfaWm1tUn9eW6vP6\nU33eeEKIozf72roK7mrl8nwBcGsC5cs2saAK7hZJCePJIgDDc4UGt0ZR1sZYslg9cyQZSxbVOG8A\n1edKM7p+blFqT/V5/ak+v7ep4A63/s8r5+fobwneVbbLZiQEPLaplbMzOR7coOqJKM1hZ0+UkYUC\nmoAd3RE1zhtA9bnSjK6fW5TaU31ef6rP720quAOG2kJNkxGzFh7e2MrDqyyboCjrQdhn8Mnr6nyp\ncV5/qs+VZrPc3KLUlurz+lN9fm9TwZ2iKIqiKIqiKPcEVRLi7jR9cDeRKvLiySkS1ULnHpUs5bb9\n+Nws705leXiolT19sUY3576g+lxpNumiybffnkQIeG5vN6DGeSOoPlfWs7Jl8+23J8mWLD60u4uO\n6I2F4pXVee3iPCfG0xwYSHBwUG2NbyZNH+kcG02RLJhcnM0vHd5XVk9KOHwpSbZk8frwfKObc19Q\nfa40ozOTGaYzJabSJc5OZ9U4bwDV58p6NzJf4PJ8gYV8heNj6UY3Z92SUvLaxXk1FzSppg/uNneE\n0YQgFvDQqe7w3DYhWDqPuLVTHZqtB9XnSjPa0BbCa2j4PBoDLSE1zhtA9bmy3nXHA0T8Brom2NSu\nciXcKSEEWzrcOWBrh5oLmk3Tb8vc2hlhqC2ELgSapgrl3omPH+ilbNn4DL3RTblvqD5Xmk1n1M9v\nPrURIQR6dS5W47z+VJ8r61nYZ/Crjw9hS6mO2dylj+zt5n1Wh5oLmlDTB3eAmgDWgPrlrz/V50qz\nMZaZi9U4rz/V58p6pmkCDXWzfi2ouaA5qahHURRFURRFURSlCazrlbt82eL7p6bRNcH7d3bi96g7\nELVw5HKSc9NZDm1IsFntza4L1edKsylU3PlaCMHP7OwE1DhvBNXnyr3g4myON4YX2NwR5tCGlkY3\n575Wtmy+f2oay5a8b2cnYd+6Dg0U1vnK3dtjaYbn8pyfyfHuVLbRzWlKUsLLZ2eZTJd46exco5tz\nX1B9rjSjE+MZLs7muTCT4+RERo3zBlB9rtwrFsfhj8/NUTLtRjfnvvbuVJZz0zmG5/K8PZpqdHOU\nNbCug7ueuB9NCDy6oCumMmHWghAs9W1fItDg1twfVJ8rzag75kfXBIYm6I751ThvANXnyr2iLxEE\noCPqw6vyIjRUV9SPRxdoQtATV/NCM1hx7VUI8Sjwi8CTQDdQBE4A3wb+UkrZsEIjg60hvvDkEJqA\noFctI9fKzx3sI1OySAQ9jW7KfUP1udJs+luC/OoTQwggVN32o8Z5/ak+V+4Fz+7o4OBggojfUJnM\nG6wj6udXnxjCkagtmU3ilu+iEOI7wATwdeAPgBnAD2wFnga+LoT4opTyG7Vu6M2ogVh7hq7REvI2\nuhn3FdXnSjO6fr5W47z+VJ8r9wIhBAk1Du8ZaoGkuaz0bv6SlPL6jfk54Gj1vz8WQrQt90QhRA/w\nLWAnEJZSWkKI/wM4BByVUv5u9ftueExRFEVRFEVRFEW5PSttdI4LIR6//kEhxONCiE0AywR/ixaA\nZ4HXqs95ADfIexLwCiEeXO6xO/1B7kShYvG9k1O8fHYWx5H1/KfXlTNTGb55fIKxZKHRTblvqD5X\nmk3Zsvnh6Wn+5sw0pu0AapwrzWe5ca6szrnpLN88PsHl+Xyjm7LuSCn56YU5vvPOJJmS2ejmKA22\n0srdvwD+4TKPZ6pfe/5mT5RSloCSEEt7qR8Bvl/98w+ARwFrmcfeXE3D18LhS0lOTWQA6Iz62dal\n0kJfTwLfOzGNIyVzuTKff3yo0U1qeqrPlWb0zliat8fcI9qJoFeNc6UpXT/OldVxHMl3TkxhO5Kp\ndIlff2pjo5u0rowli7x+cQFwi7x/YFdXg1ukNNJKK3edUsp3rn+w+tiG2/y34rhBIUC6+vflHruG\nEOI3hBCHhRCHZ2dnb/OfvLXWsDvx6pqo2eHyd6ey/OmPLvCN4xPrcnVQAFOZIm9eWiBTshrdnPuC\n6vPG+OHpaf7kR+c5cjnZ6KY0pZaQFyHcjI0tIS8CiAXc+4utYV9jG9ekkvkKf/7KMP/+p5dIF9Td\n/HrQNcHx0RTHx1J4dJUo5GaOjab4kx+d58WTU4AbkCyewVu8NlNWL+r34DXcS/rWNT7L+JNzc/zJ\nj87z0wuqfMp6sdLK3Q3B1lVuN19qGohW/xwFUoC9zGPXkFL+GfBnAIcOHVrT6GhXT4y2sJuGt1YH\ne4+PpiiZNhdmciQLlXV3ESOleyHmN3QCHpWuuB5Un9eflCzdbX9rJMnBwUSDW9R8NraH+ezDgwgB\nbdV58NMPDTCbLdOtStnUxNnpLMlqUHd+VtWCrYeK5bClMwxA2VLbMm/mrZEkZdPh5ESGJ7e0E/Dq\nfOpQHzOZsiptdQdiQQ+/+Mgg+bK15uUMjo4ksR3JWyMpHtu0bJoN5R6z0pXjYSHEr1//oBDi14Aj\nt/lvvYp7Bg/gfbhn8ZZ7rK46o/6aZmza2RNFE4K+RID4OtyiIQTs7I4RC3rY03urWF9ZK6rP608I\n2NoZQQj3po9SG+0R31JgB+D36PS3BDFUnaua2NQRJujVCfl0htrCjW7OfWFTR5i2sI/2iE/1+S3s\n6okhBGzuCOOv3sT0Ge584FHzwR2JBTw1qVO3uzfqXpf0RFf+ZuWesNLK3e8BXxVCfJYrwdwhwAt8\n4lZPFEJ4gO8A+4DvAf8I9wzej4FjUso3qt93w2PNZHdvjF09Ua46e7jufGRvN1J2reufYb1RfV5/\nqs+VZtMW9vEbT21UY7qOVJ+vzkNDLTy4IaH6aR14ZnsnT2/rUO/VOnLL4E5KOQ08JoR4Gthdffjb\nUsq/WemFpZQm7mrc1V5f5vuavvxBM/xCNMPPsN6oPq8/1edKs1Fjuv5Un6+O6qf1Q71X68tKRcwf\nBNqklN8B/vaqxz8EzEgpb3dr5j1PSsmrF+aZz1d4YnObKrIJnJxIc34mx4H+BAOtwUY3576g+rz+\nVJ8rzaZk2rx0dhYBvHdbB6DGuXJnhufyvD2WYltXhO1danveejS6UODoSJJN7WF296rjB81spW2Z\nfwR8fpnHTwH/DnhmzVvUYBPpEq8PV9PJCsFH9nY3uEWNJSV8/9Q0UsJCvqLSldeB6vP6U32uNKMT\n4+mlcj/tEZ8a58od+/6pKfJlm8vzBbZ2RNA0tZKz3vzg9DSpgsnwXJ6tnZGl7JpK81npnY1IKS9f\n/2D1saZMmRP1G/iqh3vbI+srs2UtLKYtB9Uf9aL6vP5UnyvNqC3sQwj3RuXin9U4V+7E4nhpDXtV\nYLdOLb6HLSEvhnoPm9pKK3e3ygfelPs5In4Pv/zoBvJli86oSscL8PMP9jOfq6j+qCPV5/Wn+lxp\nNhvaQvzyoxsQsHTEQI1z5U48v7eHmWz5mmy3yvryod3dPDBQUgH6fWCllbsfCCH+QFx1klK4fh9Y\nManKehX2GeqD7yo+Q6cnHkBXk0HdqD6vP9XnSjNqCXmvOTuuxrlyJwxdoyceUFv51jFdE/TEA/gM\nvdFNUWpspZW7/wH4N8B5IcSx6mP7gMPAr9WyYYqiKIqiKIqiKMrqrVQKIQ98RgixEdhVffiklPJi\nzVt2j5lIFTk1kWFbV4T+lqbckXpTF2dzXJzNs7cvRoda0VSagGU7vD68gAAe3tgKqHHeCKrP60/1\nuVJL74ylmc2VeHBDCxG/p9HNUVZBzQnNZ6VSCL8tpfx/pJQXhRABKeXJejXsXvPttyfJlS3enc7y\nd9676b6p+SGBb709ie1IJtJFfvnRDY1ukqLctbfH07xRzYob9htqnDeA6vP6U32u1NJMpsQPTk8D\nUDIdPrzn/s42vh6YtqPmhCa00ubpX73qz39Ry4bc68J+Nw4O+4z7JrADEEDQ6+7PDnlX2sWrKOtD\nxHdlLId8hhrnDaD6vP5Unyu15PPoeHT3+ijsU+NrPdCFWJoT1HvWPG7nnbx/IpplfOJAL6MLBXoT\ngUY3pe4+/dAAk6miKnirNI0tnRE+eVBH0wS9cfd3Wo3z+lN9Xn+qz5VaiQU8fOahAVJFk6HWUKOb\no6yCpomlOWFQvWdNY6XgLi6E+ATuCl9UCPHC1V+UUn6lZi27x/g9Ols6I41uRkOEfcZ9+7Mrzev6\ns7NqnNef6vP6U32u1FJr2EerKpewrqg5ofmsFNy9BHy0+ueXgeev+poE7pvgrpaKFZuLczn6W4JE\n78EDyOmCyViqwKb2MH6PSqGrNIeLszk0IdjQ5t6tVOO8/lSfK83o+rllPcuWTEYWCgy1hQiqrbz3\nLCkl52ZyhHzG0m4U5f61UrbMz9erIfezrx8bZzJdIuI3+MITQ/fcmb4vHR4hX7bpTWT41KH+RjdH\nUe7amakM33lnCoDn9rqH/tU4rz/V50qzWW5uWc++fHiMTNGkI+rjsw8PNro5yk28eSnJK+fnEAI+\n/eAAXTGV9fJ+tlK2zL9/q69LKb+4ts25PRXL4acX5jA0jUc3ta7boqwl0wagbDlICfdSbCeByXSJ\nmUwZr34PNUxR7kK2aHJ5Pg9Avmyrcd4Aqs+VZnT93LKeSSkpW+7PUKys/LOMJQucGHdLRg01warl\nvejcdJYLs3kODMTpvKpsweJ1pJQsvWfK/WulNfZ7ehPusdEUb42kAIgHPezujTW4RXfmI3t7ODWZ\nYVN7CO0eDFA1IfDo4p5bUVSUOyYEhq4hAIkE1DhvBNXnStNZZm5Zr4QQfHx/L+dmcuzoWvly8Lsn\npsiWLM7PZPm7T29Wv9drrGzZ/Ld3pnCkZDZb4peuKlvw8MYWDE0Q9hsqMYqy4rbMf1qvhtyJWMA9\nnyYEN5xVcxy5ZoHSWr7WctojPt4Taa/Z698NAfTEA4S8Ot1xtcxfK1K6FwHqw7A+EkEPPTH30H88\n6F0a5wGPpsZ5nag+bxzbket2p8u9LhH00Fsdz/Ggt67/9q2uVRxHIsTtf8b0xAP0rPIMV9TvIVuy\niPg96rNsjdmOxNA0Qj6dTNEkGrj2mtdn6Dy2ua1BrVPuNStty/zHwP8rpUze5OvPAEEp5bdq0biV\nbOuKEPYbGJpYWp42bYf/emSMmUyZZ3d03PVq3unJDC+enKYt4uXnDvbjNVYqDdh8YgGDy/N5Wuv8\nQXW/mMmW+MrRcQTwyYN9jW7OfaFiO7x5KYkQ8NF9vQAMz+V4eyxNWCUNqBvV5/X3zeMTnJ/J8fBQ\ni7oYrIFowINpSzQBUX99xrXtSL5ydIzxVJH3bG3nwEDimq9Ppot85eg4Xl3jU4f6iQVrk7jtYwd6\nGE8W6Y6phB5r6funpjkxnmZvX5RowMPIQoHWkLoeU25upUjlHeBbQogfCiH+uRDiHwgh/jchxF8I\nId7BzZ75eu2beXO98cA1+46T+QpT6RKOlLw7lb3r1393KosjJTOZMnO58l2/3nojJYwuFEkEvZy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RVnGoAPxjMMxjMsrw2ztilC+0Cca5fX4DWdCnIIfPy31pDMWGxaUsU3n2oH4PRwkvaBBNHk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\ngJ/AiEBpX95kOwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 1080x1080 with 81 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HwfhvUcLB05W",
        "colab_type": "code",
        "outputId": "f7e8c266-c40f-492f-97ba-88f312ca628b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        }
      },
      "source": [
        "#---[2-6: 4変数のみ、ヒストグラムで分布を確認]-----------------------------\n",
        "\n",
        "%matplotlib inline\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "fig=plt.figure(figsize=(15, 3));\n",
        "\n",
        "ax1 = fig.add_subplot(1, 4, 1)  \n",
        "xtmp=X.iloc[:,0] \n",
        "ax1.hist(xtmp, range=(0, 120),bins=40)\n",
        "ax1.grid(True)     \n",
        "plt.xlabel('Age',fontsize=20)\n",
        "\n",
        "\n",
        "ax2 = fig.add_subplot(1, 4, 2)  \n",
        "xtmp=X.iloc[:,4] \n",
        "ax2.hist(xtmp, color='green', range=(0, 40),bins=30)\n",
        "ax2.grid(True)     \n",
        "plt.xlabel('FG',fontsize=20)\n",
        "\n",
        "ax3 = fig.add_subplot(1, 4, 3)  \n",
        "xtmp=X.iloc[:,5] \n",
        "ax3.hist(xtmp, color='green', range=(0, 40),bins=30)\n",
        "ax3.grid(True)    \n",
        "plt.xlabel(\"2hG\", fontsize=20)   \n",
        "\n",
        "\n",
        "ax4 = fig.add_subplot(1, 4, 4)  \n",
        "xtmp=X.iloc[:,5] \n",
        "ax4.hist(xtmp, range=(0, 40),bins=30, label=\"HbA1c\")\n",
        "ax4.grid(True)     \n",
        "plt.xlabel(\"HbA1c\", fontsize=20)    \n",
        "fig.show()\n",
        "\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Skxjr+L/Qq/9ZPTRdnMOWZzAEn31T9uWmsuT9vYlxjvt6U62j8Z8lXeRZrxpt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\n",
            "text/plain": [
              "<Figure size 1080x216 with 4 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gkURN9thd69F",
        "colab_type": "text"
      },
      "source": [
        "---\n",
        "---\n",
        "### [3]. XGBoostによる糖尿病予測、変数重要度、木構造可視化\n",
        "\n",
        "- XGBoostは勾配ブースティング決定木 (Gradient Boosting Decision Tree) のアルゴリズムを使った機械学習モデルです。\n",
        "- サンプルを「訓練」＋「テスト」に分割"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JNAJICL6uYZP",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#---------[3-1: 患者(＝ROW)を、訓練データとテストデータに分割]----------------------------\n",
        "#　\n",
        "# 1,415人の患者を、訓練データ(8割)とテストデータ(2割)に分割 \n",
        "#\n",
        "# yの糖尿病患者(1)の数が少ないので、均等割のstratifyフラグを付けた\n",
        "#-------------------------------------------------------------------------------------\n",
        "\n",
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "#---------------------------------------------------------------\n",
        "X_train, X_test, y_train, y_test = train_test_split(X2,y, test_size=0.20,stratify=y)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OgFu5ClDd3-L",
        "colab_type": "code",
        "outputId": "816f1e3b-30cf-4642-84a2-d12315944418",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 386
        }
      },
      "source": [
        "#---------[3-2: XGBoostによる糖尿病予測]----------------------------\n",
        "#　\n",
        "#  XGBoostによるモデル学習\n",
        "#  Accuracyによる評価尺度値は98.9%\n",
        "#  混同行列の表示。\n",
        "#\n",
        "#-------------------------------------------------------------------------------------\n",
        "\n",
        "import pandas as pd\n",
        "import xgboost as xgb\n",
        "from xgboost.sklearn import XGBClassifier\n",
        "from sklearn.model_selection import GridSearchCV\n",
        "from sklearn.metrics import accuracy_score\n",
        "from sklearn.metrics import plot_confusion_matrix\n",
        "\n",
        "\n",
        "#---------学習-------------------------------\n",
        "\n",
        "reg = xgb.XGBClassifier()\n",
        "reg_cv = GridSearchCV(reg, {'max_depth': [2,4,6]},verbose=1) # ハイパーパラメータ探索(木構造の深さ)\n",
        "reg_cv.fit(X_train, y_train)\n",
        "print(reg_cv.best_params_)\n",
        "#print(reg_cv.best_score_)\n",
        "\n",
        "model_xgb = xgb.XGBClassifier(**reg_cv.best_params_)\n",
        "model_xgb.fit(X_train, y_train)\n",
        "\n",
        "#---------予測と評価(Accuracy)-------------------------------\n",
        "\n",
        "y_pred = model_xgb.predict(X_test)\n",
        "acc = accuracy_score(y_test, y_pred)\n",
        "print('[Accuracy: %.5f]' % acc)\n",
        "\n",
        "#---------混同行列----------------------\n",
        "plot_confusion_matrix(model_xgb, X_test, y_test, cmap=plt.cm.Blues)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Fitting 5 folds for each of 3 candidates, totalling 15 fits\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "{'max_depth': 2}\n",
            "[Accuracy: 1.00000]\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "[Parallel(n_jobs=1)]: Done  15 out of  15 | elapsed:    0.7s finished\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<sklearn.metrics._plot.confusion_matrix.ConfusionMatrixDisplay at 0x7ff68cf09470>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 80
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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9UkgTcG9IGg6EpEbgdGBWdZtlZvUsJ/mWKuBOoTRM3RZYANyXlJnZBkgqwFStFhGxEBi7\nHtpiZjmRk3xLtaLv1axjTmpEnFiVFplZ3auHK6RppBmi3lf2eiNKzyl8ozrNMbN6J6iLxSzTSDNE\nXW15cknXAw9XrUVmVt/q5B63NDoyVWt7oE+lG2Jm+aG6eOJC+9Kcg1vKp+fgGig9CHp8NRtlZvWr\nMI8NVOnu3j0oPYcBYFVEVGZBKTPLrbwEXJtTtZIwuysimpPN4WZmSEq11VqauahPSdqz6i0xs1wo\nPTYw3VZrbT2ToSkiVgJ7Ak9KegV4n9IQPCJi6Hpqo5nVmSLMZPgzMBQ4bD21xcxyoCgXGQSlp9mv\np7aYWU7kpAPXZsBtKel7rX0YEZdWoT1mVvdEQ07ug2vrNGAj0APo2cpmZhsgUbkFLyVdK2mhpOfK\nyraQdK+kl5OfvZJySbpc0mxJz0hq9zpAWz24+RHxb+030cw2KIKmyp2Em0zpGcxTysrGA/dHxEWS\nxifvzwZGAYOTbR/gyuRnq9rqweWjD2pm61Ule3AR8RCl2VHlRgPXJa+vAw4vK58SJY8Dm0vq29bx\n2+rBfaH95pnZhijDbSK9JU0rez8pIia1850+ETE/ef0Wn85978fqKxnNTcrm04q2nmy/ZqqamQGZ\nrqIujohhHa0nIkJSh2dQ1cG9xmaWJ6IUHGm2DlrQMvRMfi5MyucBA8r268+n8+TXyQFnZtmoNERN\ns3XQHcCxyetjgdvLyo9JrqbuCywrG8quU0fWgzOzDVhpJkNlrkFKuhE4kNK5urnAecBFwFRJxwOv\nA2OS3e8CDgFmAx8A/9Le8R1wZpZZpW6xiIhxrXy01kXOZDWjU7Mc3wFnZpkVYaqWmdk61Mdab2k4\n4Mwsk5arqHnggDOzzIqwHpyZ2dqEh6hmVkweoppZobkHZ2aFlY94c8CZWUYCGt2DM7Oiykm+OeDM\nLCuhnAxSHXBmlpl7cGZWSKXbRPKRcA44M8sm5fMW6oEDzswy81QtMyuk0oKXtW5FOg44M8vMV1HN\nrLByMkJ1wFXTfY8+zzmX/JbmVas4evR+fPe4EbVukq3hzItu5IHHnuczvXpwz+SzAXh+9jx+cMlv\n+GD5Cvpv3Yuf/fBoem6yUY1bWl/y0oOr2qIAkq6VtFDSc9Wqo541N6/izIun8puff5PHp57LLfdM\n58VX23wAkNXA10YN57qfnLha2fiLb+bskw7l7sln8aX/vTuTbnqgRq2rTy3n4NJstVbNVU8mAyOr\nePy6Nn3mHHYY0JuB/XvTtUsTRxw8lLv++Eytm2Vr2GePQWzWc5PVyl6bu4h99hgEwN/vvSP/47/b\n6lI+MrAerrRWLeAi4iFgSbWOX+/mL1pGvz69Pnm/TZ9ezF+0rIYtsrQGD9yaex4uDTzuevBp5i98\nu8Ytqj9KudVazdetk3SipGmSpi1avKjWzTHj4rPH8p//9TCHnnAJ7y3/kC5dGmvdpLrS8lzUPPTg\nan6RISImAZMA9tprWNS4ORXTd8vNmLdg6Sfv31ywlL5bblbDFllan92uD9dfcgoAr76xkAcfe6HG\nLao/tY+udGregyuqobtuxyt/XcTr8xaz4uOV3HrvDEYdsHutm2UpLF76LgCrVq1iwpR7Oeqw/Wrc\nojqUkzFqzXtwRdXU1MjFZ43hq9+aSHNzcNRh+7LLoL61bpat4fQLpvD4U7NZuux99v3a+Xz3X0by\n/vKPuP62RwD40gF/x5GHDK9xK+tPPQw/06hawEm6ETgQ6C1pLnBeRFxTrfrq0Yj9d2PE/rvVuhnW\nhivOO2ad5V//2ufXc0vyJR/xVsWAi4hx1Tq2mdVYThLOQ1Qzy6R0ei0fCeeAM7NsvB6cmRVZTvLN\nAWdmWckPfjaz4qpUvkmaA7wLNAMrI2KYpC2Am4GBwBxgTEQsbe0YbfGNvmaWSdp7fDNk4D9ExJCI\nGJa8Hw/cHxGDgfuT9x3igDOz7Ko7k2E0cF3y+jrg8I4eyAFnZpkp5T8pBHCPpOmSWhbm6xMRLYsn\nvgX06Wg7fQ7OzDLLcA6ut6RpZe8nJQtstPj7iJgnaSvgXkkvln85IkJShxfhcMCZWTbZ7oNbXHZu\nbS0RMS/5uVDSbcBwYIGkvhExX1JfYGFHm+ohqpllVokhqqRNJPVseQ2MAJ4D7gCOTXY7Fri9o+10\nD87MMhEVu02kD3Bbck9dE3BDRPxe0pPAVEnHA68DYzpagQPOzDKrRL5FxKvAHuso/xvwhQpU4YAz\nsw7Ix0QGB5yZZbfBL3hpZsWVj3hzwJlZR+Qk4RxwZpaJF7w0s+LygpdmVmQ5yTcHnJll5QUvzazA\ncpJvDjgzy6ZOHlqfigPOzLLLScI54MwsM98mYmaF5XNwZlZMggYHnJkVVz4SzgFnZplUcMHLqnPA\nmVlmOck3B5yZZecenJkVlqdqmVlh5SPeHHBmlpG8XJKZFZlnMphZceUj3xxwZpZdTvLNAWdmWcmP\nDTSzYsrTTIaGWjfAzKxa3IMzs8zy0oNzwJlZZr5NxMyKyTf6mllR5ekigwPOzDLzENXMCisvPTjf\nJmJmmSnl1u5xpJGSXpI0W9L4SrfTAWdm2VUg4SQ1AhOBUcCuwDhJu1aymQ44M8tEQIOUamvHcGB2\nRLwaESuAm4DRlWxrXZ2DmzFj+uLuXfR6rdtRBb2BxbVuhGVS1L/Zdp09wIwZ0+/u3kW9U+6+kaRp\nZe8nRcSk5HU/4I2yz+YC+3S2feXqKuAiYstat6EaJE2LiGG1boel579Z6yJiZK3bkJaHqGZWK/OA\nAWXv+ydlFeOAM7NaeRIYLGl7SV2BscAdlaygroaoBTap/V2szvhvVmURsVLSacDdQCNwbUTMrGQd\niohKHs/MrG54iGpmheWAM7PCcsBVUbWnoVjlSbpW0kJJz9W6LdZ5DrgqWR/TUKwqJgO5uc/L2uaA\nq56qT0OxyouIh4AltW6HVYYDrnrWNQ2lX43aYrZBcsCZWWE54Kqn6tNQzKxtDrjqqfo0FDNrmwOu\nSiJiJdAyDeUFYGqlp6FY5Um6EXgM2EnSXEnH17pN1nGeqmVmheUenJkVlgPOzArLAWdmheWAM7PC\ncsCZWWE54HJEUrOkpyQ9J+k3kjbuxLEOlHRn8vqwtlY7kbS5pG92oI7zJf1r2vI19pks6WsZ6hro\nFUBsTQ64fFkeEUMi4nPACuDk8g9VkvlvGhF3RMRFbeyyOZA54MxqzQGXX38CPpv0XF6SNAV4Dhgg\naYSkxyTNSHp6PeCT9elelDQDOKLlQJKOkzQhed1H0m2Snk62/YCLgEFJ7/EnyX5nSnpS0jOSLig7\n1g8kzZL0MLBTe7+EpBOS4zwt6ZY1eqVflDQtOd6hyf6Nkn5SVvdJnf0XacXlgMshSU2U1pl7Nika\nDPwiInYD3gfOBb4YEUOBacD3JG0EXA38I7AXsHUrh78c+GNE7AEMBWYC44FXkt7jmZJGJHUOB4YA\ne0k6QNJelKakDQEOAfZO8evcGhF7J/W9AJTPHBiY1PFl4KrkdzgeWBYReyfHP0HS9inqsQ2Qn6qV\nL90lPZW8/hNwDbAN8HpEPJ6U70tpgc1HJAF0pTT1aGfgtYh4GUDSfwInrqOOg4BjACKiGVgmqdca\n+4xItr8k73tQCryewG0R8UFSR5q5t5+T9P8oDYN7UJra1mJqRKwCXpb0avI7jAB2Lzs/t1lS96wU\nddkGxgGXL8sjYkh5QRJi75cXAfdGxLg19lvte50k4N8j4pdr1PGdDhxrMnB4RDwt6TjgwLLP1pxH\nGEndp0dEeRAiaWAH6raC8xC1eB4H9pf0WQBJm0jaEXgRGChpULLfuFa+fz9wSvLdRkmbAe9S6p21\nuBv4etm5vX6StgIeAg6X1F1ST0rD4fb0BOZL6gIctcZnR0pqSNq8A/BSUvcpyf5I2lHSJinqsQ2Q\ne3AFExGLkp7QjZK6JcXnRsQsSScCv5P0AaUhbs91HOLbwKRkFY1m4JSIeEzSI8ltGP+TnIfbBXgs\n6UG+B/yfiJgh6WbgaWAhpSWj2vND4AlgUfKzvE1/Bf4MbAqcHBEfSvoPSufmZqhU+SLg8HT/dmxD\n49VEzKywPEQ1s8JywJlZYTngzKywHHBmVlgOODMrLAecmRWWA87MCuv/A3mChOZxflt2AAAAAElF\nTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tCvtW3aU9Phb",
        "colab_type": "code",
        "outputId": "c20e3d5b-ff1d-4764-f6f3-5155924f0c91",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 195
        }
      },
      "source": [
        "#---------[3-3: 属性(変数)重要度]----------------------------\n",
        "#　\n",
        "#  [1] 2hG:ブドウ糖負荷試験の2時間後血糖値 　\n",
        "#  [2] FG : 空腹時血糖値 \n",
        "#  [3] Age: 年齢  \n",
        "#  [4] HbA1c : ヘモグロビンA1c \n",
        "#\n",
        "#---------------------------------------------------------\n",
        "fti = model_xgb.feature_importances_   \n",
        "\n",
        "print('Feature Importances:')\n",
        "for i, feat in enumerate(X2.columns.values):\n",
        "    print('\\t{0:20s} : {1:>.4f}'.format(feat, fti[i]))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Feature Importances:\n",
            "\tAge                  : 0.0098\n",
            "\tGender               : 0.0000\n",
            "\tsmoking4_1           : 0.0000\n",
            "\tsmoking4_2           : 0.0000\n",
            "\tsmoking4_3           : 0.0000\n",
            "\tPhysical inactivity  : 0.0000\n",
            "\tFG                   : 0.0687\n",
            "\t2hG                  : 0.9215\n",
            "\tHbA1c (IFCC)         : 0.0000\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YgrJjtByo5MU",
        "colab_type": "code",
        "outputId": "17ae1e46-8335-4dd0-e060-36cd31eb381b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 312
        }
      },
      "source": [
        "#---------[3-4: 木構造分類による可視化]------------------------------------------\n",
        "#\n",
        "# XGBoostは、決定木アルゴリズム（Gradient Boosting Decision Tree）のため、\n",
        "# 学習した木構造を可視化できる。\n",
        "#\n",
        "#----------------------------------------------------------\n",
        "# 結果の木構造の解釈\n",
        "#\n",
        "# (1)2hG値が11.1より大きいと糖尿病に分類\n",
        "#             yes(DM=0)、no(DM=1)          \n",
        "# (2)2hG値が小さくても、FG値（空腹時血糖値）が6.8より大きいと糖尿病に分類\n",
        "#             yes(DM=0)、no(DM=1)  \n",
        "#-----------------------------------------------------------------------------\n",
        "\n",
        "xgb.to_graphviz(model_xgb)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<graphviz.dot.Digraph at 0x7ff68d2c0cc0>"
            ],
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          "metadata": {
            "tags": []
          },
          "execution_count": 82
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sDdCRL53CT-t",
        "colab_type": "text"
      },
      "source": [
        "-----\n",
        "-----\n",
        "-----\n"
      ]
    }
  ]
}