2988 lines
864 KiB
Plaintext
2988 lines
864 KiB
Plaintext
{
|
||
"cells": [
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 1. Датасет: Диабет у индейцев Пима\n",
|
||
"https://www.kaggle.com/datasets/uciml/pima-indians-diabetes-database\n",
|
||
"##### О наборе данных: \n",
|
||
"Этот набор данных был получен из Национального института диабета, болезней органов пищеварения и почек. Цель набора данных - диагностически предсказать, есть ли у пациента сахарный диабет, на основе определенных диагностических измерений, включенных в набор данных. На выбор этих образцов из более обширной базы данных было наложено несколько ограничений. В частности, все пациенты были женщинами в возрасте не менее 21 года, родом из племени пима.\n",
|
||
"##### Таким образом:\n",
|
||
"* Объект наблюдения - женщины племени пима, возрастом от 21 года.\n",
|
||
"* Атрибуты: Pregnancies, Glucose, BloodPressure, SkinThickness, Insulin, BMI, DiabetesPedigreeFunction, Age, Outcome.\n",
|
||
"* Проблемная область: Предсказание диабета у пациента на основе измерений."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 347,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Количество колонок: 9\n",
|
||
"Колонки: Pregnancies, Glucose, BloodPressure, SkinThickness, Insulin, BMI, DiabetesPedigreeFunction, Age, Outcome\n",
|
||
"\n",
|
||
"<class 'pandas.core.frame.DataFrame'>\n",
|
||
"RangeIndex: 768 entries, 0 to 767\n",
|
||
"Data columns (total 9 columns):\n",
|
||
" # Column Non-Null Count Dtype \n",
|
||
"--- ------ -------------- ----- \n",
|
||
" 0 Pregnancies 768 non-null int64 \n",
|
||
" 1 Glucose 768 non-null int64 \n",
|
||
" 2 BloodPressure 768 non-null int64 \n",
|
||
" 3 SkinThickness 768 non-null int64 \n",
|
||
" 4 Insulin 768 non-null int64 \n",
|
||
" 5 BMI 768 non-null float64\n",
|
||
" 6 DiabetesPedigreeFunction 768 non-null float64\n",
|
||
" 7 Age 768 non-null int64 \n",
|
||
" 8 Outcome 768 non-null int64 \n",
|
||
"dtypes: float64(2), int64(7)\n",
|
||
"memory usage: 54.1 KB\n"
|
||
]
|
||
},
|
||
{
|
||
"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>Pregnancies</th>\n",
|
||
" <th>Glucose</th>\n",
|
||
" <th>BloodPressure</th>\n",
|
||
" <th>SkinThickness</th>\n",
|
||
" <th>Insulin</th>\n",
|
||
" <th>BMI</th>\n",
|
||
" <th>DiabetesPedigreeFunction</th>\n",
|
||
" <th>Age</th>\n",
|
||
" <th>Outcome</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>6</td>\n",
|
||
" <td>148</td>\n",
|
||
" <td>72</td>\n",
|
||
" <td>35</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>33.6</td>\n",
|
||
" <td>0.627</td>\n",
|
||
" <td>50</td>\n",
|
||
" <td>1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>1</td>\n",
|
||
" <td>85</td>\n",
|
||
" <td>66</td>\n",
|
||
" <td>29</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>26.6</td>\n",
|
||
" <td>0.351</td>\n",
|
||
" <td>31</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>8</td>\n",
|
||
" <td>183</td>\n",
|
||
" <td>64</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>23.3</td>\n",
|
||
" <td>0.672</td>\n",
|
||
" <td>32</td>\n",
|
||
" <td>1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>1</td>\n",
|
||
" <td>89</td>\n",
|
||
" <td>66</td>\n",
|
||
" <td>23</td>\n",
|
||
" <td>94</td>\n",
|
||
" <td>28.1</td>\n",
|
||
" <td>0.167</td>\n",
|
||
" <td>21</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>0</td>\n",
|
||
" <td>137</td>\n",
|
||
" <td>40</td>\n",
|
||
" <td>35</td>\n",
|
||
" <td>168</td>\n",
|
||
" <td>43.1</td>\n",
|
||
" <td>2.288</td>\n",
|
||
" <td>33</td>\n",
|
||
" <td>1</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" Pregnancies Glucose BloodPressure SkinThickness Insulin BMI \\\n",
|
||
"0 6 148 72 35 0 33.6 \n",
|
||
"1 1 85 66 29 0 26.6 \n",
|
||
"2 8 183 64 0 0 23.3 \n",
|
||
"3 1 89 66 23 94 28.1 \n",
|
||
"4 0 137 40 35 168 43.1 \n",
|
||
"\n",
|
||
" DiabetesPedigreeFunction Age Outcome \n",
|
||
"0 0.627 50 1 \n",
|
||
"1 0.351 31 0 \n",
|
||
"2 0.672 32 1 \n",
|
||
"3 0.167 21 0 \n",
|
||
"4 2.288 33 1 "
|
||
]
|
||
},
|
||
"execution_count": 347,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"import pandas as pd\n",
|
||
"df = pd.read_csv(\".//static//csv//diabetes.csv\", sep=\",\")\n",
|
||
"print('Количество колонок: ' + str(df.columns.size)) \n",
|
||
"print('Колонки: ' + ', '.join(df.columns)+'\\n')\n",
|
||
"\n",
|
||
"df.info()\n",
|
||
"df.head()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"#### Получение сведений о пропущенных данных\n",
|
||
"Типы пропущенных данных:\n",
|
||
"\n",
|
||
"- None - представление пустых данных в Python\n",
|
||
"- NaN - представление пустых данных в Pandas\n",
|
||
"- '' - пустая строка"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 348,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Pregnancies 0\n",
|
||
"Glucose 0\n",
|
||
"BloodPressure 0\n",
|
||
"SkinThickness 0\n",
|
||
"Insulin 0\n",
|
||
"BMI 0\n",
|
||
"DiabetesPedigreeFunction 0\n",
|
||
"Age 0\n",
|
||
"Outcome 0\n",
|
||
"dtype: int64\n",
|
||
"\n",
|
||
"Pregnancies False\n",
|
||
"Glucose False\n",
|
||
"BloodPressure False\n",
|
||
"SkinThickness False\n",
|
||
"Insulin False\n",
|
||
"BMI False\n",
|
||
"DiabetesPedigreeFunction False\n",
|
||
"Age False\n",
|
||
"Outcome False\n",
|
||
"dtype: bool\n",
|
||
"\n",
|
||
"Pregnancies процент пустых значений: %0.00\n",
|
||
"Glucose процент пустых значений: %0.00\n",
|
||
"BloodPressure процент пустых значений: %0.00\n",
|
||
"SkinThickness процент пустых значений: %0.00\n",
|
||
"Insulin процент пустых значений: %0.00\n",
|
||
"BMI процент пустых значений: %0.00\n",
|
||
"DiabetesPedigreeFunction процент пустых значений: %0.00\n",
|
||
"Age процент пустых значений: %0.00\n",
|
||
"Outcome процент пустых значений: %0.00\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Количество пустых значений признаков\n",
|
||
"print(df.isnull().sum())\n",
|
||
"print()\n",
|
||
"\n",
|
||
"# Есть ли пустые значения признаков\n",
|
||
"print(df.isnull().any())\n",
|
||
"print()\n",
|
||
"\n",
|
||
"# Процент пустых значений признаков\n",
|
||
"for i in df.columns:\n",
|
||
" null_rate = df[i].isnull().sum() / len(df) * 100\n",
|
||
" print(f\"{i} процент пустых значений: %{null_rate:.2f}\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"##### Проверим выбросы и устраним их:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 349,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Колонка Pregnancies:\n",
|
||
" Есть выбросы: Да\n",
|
||
" Количество выбросов: 4\n",
|
||
" Минимальное значение: 0.0\n",
|
||
" Максимальное значение: 13.5\n",
|
||
" 1-й квартиль (Q1): 1.0\n",
|
||
" 3-й квартиль (Q3): 6.0\n",
|
||
"\n",
|
||
"Колонка Glucose:\n",
|
||
" Есть выбросы: Да\n",
|
||
" Количество выбросов: 5\n",
|
||
" Минимальное значение: 37.125\n",
|
||
" Максимальное значение: 199.0\n",
|
||
" 1-й квартиль (Q1): 99.0\n",
|
||
" 3-й квартиль (Q3): 140.25\n",
|
||
"\n",
|
||
"Колонка BloodPressure:\n",
|
||
" Есть выбросы: Да\n",
|
||
" Количество выбросов: 45\n",
|
||
" Минимальное значение: 35.0\n",
|
||
" Максимальное значение: 107.0\n",
|
||
" 1-й квартиль (Q1): 62.0\n",
|
||
" 3-й квартиль (Q3): 80.0\n",
|
||
"\n",
|
||
"Колонка SkinThickness:\n",
|
||
" Есть выбросы: Да\n",
|
||
" Количество выбросов: 1\n",
|
||
" Минимальное значение: 0.0\n",
|
||
" Максимальное значение: 80.0\n",
|
||
" 1-й квартиль (Q1): 0.0\n",
|
||
" 3-й квартиль (Q3): 32.0\n",
|
||
"\n",
|
||
"Колонка Insulin:\n",
|
||
" Есть выбросы: Да\n",
|
||
" Количество выбросов: 34\n",
|
||
" Минимальное значение: 0.0\n",
|
||
" Максимальное значение: 318.125\n",
|
||
" 1-й квартиль (Q1): 0.0\n",
|
||
" 3-й квартиль (Q3): 127.25\n",
|
||
"\n",
|
||
"Колонка BMI:\n",
|
||
" Есть выбросы: Да\n",
|
||
" Количество выбросов: 19\n",
|
||
" Минимальное значение: 13.35\n",
|
||
" Максимальное значение: 50.550000000000004\n",
|
||
" 1-й квартиль (Q1): 27.3\n",
|
||
" 3-й квартиль (Q3): 36.6\n",
|
||
"\n",
|
||
"Колонка DiabetesPedigreeFunction:\n",
|
||
" Есть выбросы: Да\n",
|
||
" Количество выбросов: 29\n",
|
||
" Минимальное значение: 0.078\n",
|
||
" Максимальное значение: 1.2\n",
|
||
" 1-й квартиль (Q1): 0.24375\n",
|
||
" 3-й квартиль (Q3): 0.62625\n",
|
||
"\n",
|
||
"Колонка Age:\n",
|
||
" Есть выбросы: Да\n",
|
||
" Количество выбросов: 9\n",
|
||
" Минимальное значение: 21.0\n",
|
||
" Максимальное значение: 66.5\n",
|
||
" 1-й квартиль (Q1): 24.0\n",
|
||
" 3-й квартиль (Q3): 41.0\n",
|
||
"\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"numeric_columns = ['Pregnancies', 'Glucose', 'BloodPressure', 'SkinThickness', 'Insulin', 'BMI', 'DiabetesPedigreeFunction', 'Age']\n",
|
||
"for column in numeric_columns:\n",
|
||
" if pd.api.types.is_numeric_dtype(df[column]): # Проверяем, является ли колонка числовой\n",
|
||
" q1 = df[column].quantile(0.25) # Находим 1-й квартиль (Q1)\n",
|
||
" q3 = df[column].quantile(0.75) # Находим 3-й квартиль (Q3)\n",
|
||
" iqr = q3 - q1 # Вычисляем межквартильный размах (IQR)\n",
|
||
"\n",
|
||
" # Определяем границы для выбросов\n",
|
||
" lower_bound = q1 - 1.5 * iqr # Нижняя граница\n",
|
||
" upper_bound = q3 + 1.5 * iqr # Верхняя граница\n",
|
||
"\n",
|
||
" # Подсчитываем количество выбросов\n",
|
||
" outliers = df[(df[column] < lower_bound) | (df[column] > upper_bound)]\n",
|
||
" outlier_count = outliers.shape[0]\n",
|
||
"\n",
|
||
" # Устраняем выбросы: заменяем значения ниже нижней границы на саму нижнюю границу, а выше верхней — на верхнюю\n",
|
||
" df[column] = df[column].apply(lambda x: lower_bound if x < lower_bound else upper_bound if x > upper_bound else x)\n",
|
||
"\n",
|
||
" print(f\"Колонка {column}:\")\n",
|
||
" print(f\" Есть выбросы: {'Да' if outlier_count > 0 else 'Нет'}\")\n",
|
||
" print(f\" Количество выбросов: {outlier_count}\")\n",
|
||
" print(f\" Минимальное значение: {df[column].min()}\")\n",
|
||
" print(f\" Максимальное значение: {df[column].max()}\")\n",
|
||
" print(f\" 1-й квартиль (Q1): {q1}\")\n",
|
||
" print(f\" 3-й квартиль (Q3): {q3}\\n\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"#### Постараемся выявить зависимости Outcome от остальных колонок:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 350,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 400x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 400x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 400x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAaIAAAIjCAYAAABBDx+PAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAABLK0lEQVR4nO3dd1QU1/8+8Gel96LUiIBgxZZootjAiKJRI4oaSyKW2CUa9WM0iUGsUaNRYzexJRbs0dhFxIYmscYaRLCDBQEBQYH7+yM/9uu6C+7A4uDyvM7hHObO7Ox7y+yzd+bujEIIIUBERCSTcnIXQEREZRuDiIiIZMUgIiIiWTGIiIhIVgwiIiKSFYOIiIhkxSAiIiJZMYiIiEhWDCIiIpIVg4jo/5s4cSIUCgUePXpU6HJ9+vSBh4dHidayatUqKBQK/P33369d1t/fH/7+/pLWn5CQAIVCgR9++KGIFRLpjk6DKC4uDoMGDULlypVhamoKa2trNGnSBPPmzcOzZ890eVdEWnv+/DnmzZuHd999F9bW1rC1tYWPjw8GDhyIq1evvpEa8j/4tflLSEh4IzVR8R0/fhydOnWCk5MTTExM4OHhgUGDBuHWrVtFXmdmZiYmTpyIw4cP667QUs5QVyvatWsXunbtChMTE/Tu3Ru1atXC8+fPcezYMfzvf//DpUuXsGzZMl3dHZHWgoODsWfPHvTo0QMDBgzAixcvcPXqVfzxxx9o3LgxqlevLml9y5cvR15enqTbODg44Ndff1Vpmz17Nu7cuYMff/xRbVkp9u/fL2l50o2ffvoJI0aMQOXKlREaGgoXFxdcuXIFP//8MyIiIrB79240btxY8nozMzMRHh4OAJJ7um8rnQRRfHw8unfvDnd3dxw6dAguLi7KecOGDcP169exa9cuXdwVkSR//fUX/vjjD0ydOhVff/21yrwFCxYgJSVF8jqNjIwk38bCwgKffvqpStuGDRvw5MkTtXapjI2Ni3V7ku748eMYOXIkmjZtir1798Lc3Fw5b8iQIWjSpAm6dOmCS5cuwc7OTsZK3w462TU3c+ZMpKen45dfflEJoXze3t4YMWKEclqhUGD48OFYu3YtqlWrBlNTU9SvXx9HjhxRu+3du3fRr18/ZdfXx8cHK1as0FhH/j7+V/9e/Vbh7++PWrVqqd3+hx9+0LhrZM+ePWjWrBksLCxgZWWFdu3a4dKlS2q3v3r1Krp06QJ7e3uYmpqiQYMG2LFjh8ZaX3bt2jV8+OGHcHZ2homJCdzc3DB48GAkJycrlzl8+DAUCgU2b96sdntLS0v06dNHOZ2cnIwxY8agdu3asLS0hLW1Ndq2bYvz589rfL5e5eHhobI+AEhJScHIkSPh5uYGExMTeHt7Y8aMGSo9g8KOO9SqVUvldch/PK/ufmjXrh0UCgUmTpyo0i7lffCyuLg4AECTJk3U5hkYGKB8+fKF3v7mzZvw9vZGrVq1kJSUBED9GNHLj3vZsmXw8vKCiYkJ3n//ffz111+vrbEw2dnZGDVqFBwcHGBhYYFOnTrh4cOHKstoOkaUlZWFiRMnomrVqjA1NYWLiws6d+6sfD40EUJg4MCBMDY2xtatWwH837Gq48ePv7YOQLttJTExEX379kXFihVhYmICFxcXdOzYUWW7+/vvvxEYGIgKFSrAzMwMnp6e6Nev32ufLw8Pj0J3e74sJycHkydPVr5eHh4e+Prrr5Gdnf3a+5k8eTIUCgVWr16tEkIA4OXlhZkzZ+L+/ftYunSpsr2gY3kvv58SEhKUPeLw8HBl3S9vD1evXkW3bt3g4OAAMzMzVKtWDd98843KOs+ePYu2bdvC2toalpaWaNmyJU6ePKmyTP5re+zYMXzxxRdwcHCAra0tBg0ahOfPnyMlJQW9e/eGnZ0d7OzsMHbsWLx6sYa8vDzMnTsXPj4+MDU1hZOTEwYNGoQnT5689jl8mU56RDt37kTlypUldUOjo6MRERGBL774AiYmJli0aBHatGmDP//8UxkSSUlJaNSokTK4HBwcsGfPHvTv3x9paWkYOXKkxnUvXrwYlpaWAIDx48cX67H9+uuvCAkJQWBgIGbMmIHMzEwsXrwYTZs2xdmzZ5VvoEuXLqFJkyZ45513MG7cOFhYWGDjxo0ICgrCli1b0KlTpwLvIyMjAxUrVkSHDh1gbW2NixcvYuHChbh79y527twpueYbN25g+/bt6Nq1Kzw9PZGUlISlS5fCz88Ply9fhqurq6T1ZWZmws/PD3fv3sWgQYNQqVIlnDhxAuPHj8f9+/cxd+5cyTVqcuTIEezevVutvajvAwBwd3cHAKxduxZNmjSBoaH2b/m4uDh8+OGHsLe3x4EDB1ChQoVCl1+3bh2ePn2KQYMGQaFQYObMmejcuTNu3LhRpF4UAISGhsLOzg5hYWFISEjA3LlzMXz4cERERBR4m9zcXLRv3x6RkZHo3r07RowYgadPn+LAgQO4ePEivLy8NN6mX79+iIiIwLZt29CuXTvJdWi7rQQHB+PSpUsIDQ2Fh4cHHjx4gAMHDuDWrVvK6datW8PBwQHjxo2Dra0tEhISlOH4OvXq1cPo0aNV2tasWYMDBw6otH3++edYvXo1unTpgtGjR+PUqVOYPn06rly5gm3bthW4/szMTERGRqJZs2bw9PTUuMwnn3yCgQMH4o8//sC4ceO0qhv4b7fs4sWLMWTIEHTq1AmdO3cGANSpUwcAcOHCBTRr1gxGRkYYOHAgPDw8EBcXh507d2Lq1KkA/vssatasGaytrTF27FgYGRlh6dKl8Pf3R3R0NBo2bKhyn6GhoXB2dkZ4eDhOnjyJZcuWwdbWFidOnEClSpUwbdo07N69G7NmzUKtWrXQu3dv5W0HDRqEVatWoW/fvvjiiy8QHx+PBQsW4OzZszh+/Lj273tRTKmpqQKA6Nixo9a3ASAAiL///lvZdvPmTWFqaio6deqkbOvfv79wcXERjx49Url99+7dhY2NjcjMzFRp//rrrwUAleV9fHyEn5+fynJ+fn7Cx8dHra5Zs2YJACI+Pl4IIcTTp0+Fra2tGDBggMpyiYmJwsbGRqW9ZcuWonbt2iIrK0vZlpeXJxo3biyqVKnymmdE3dChQ4WlpaVyOioqSgAQmzZtUlvWwsJChISEKKezsrJEbm6uyjLx8fHCxMRETJo0SdkWHh4uAIi8vDyVZd3d3VXWN3nyZGFhYSH+/fdfleXGjRsnDAwMxK1bt5T3AUDMmjVLrcZXX4f8xxMVFaVsa9iwoWjbtq0AIMLCwpTtUt8HL8vLyxN+fn4CgHBychI9evQQCxcuFDdv3lRbNiwsTAAQDx8+FFeuXBGurq7i/fffF8nJySrLhYSECHd3d+V0/uMuX768yrK///67ACB27typsbZ27dqprOdlK1euFABEQECAyuvz5ZdfCgMDA5GSkqJs8/PzU3luV6xYIQCIOXPmaHw+Xq551qxZ4sWLF+KTTz4RZmZmYt++fUWqQ9tt5cmTJwW+R/Jt27ZNABB//fVXgcsUxN3dXbRr106tfdiwYeLlj7tz584JAOLzzz9XWW7MmDECgDh06FCB95F/2xEjRhRaS506dYS9vb1y+tXXKd+r76eHDx+qbQP5mjdvLqysrNTevy+/NkFBQcLY2FjExcUp2+7duyesrKxE8+bNlW35r21gYKDK7X19fYVCoRCDBw9WtuXk5IiKFSuq1H/06FEBQKxdu1allr1792psL0yxd82lpaUBAKysrCTdztfXF/Xr11dOV6pUCR07dsS+ffuQm5sLIQS2bNmCDh06QAiBR48eKf8CAwORmpqKM2fOqKwzKysLAGBqavra+8/NzVVZ56NHj5CZmamyzIEDB5CSkoIePXqoLGdgYICGDRsiKioKwH+7wg4dOoRu3brh6dOnyuUeP36MwMBAxMbG4u7du6+tKTU1FUlJSYiMjMSuXbvQvHlztWVeXn/+36tMTExQrlw55eN8/PgxLC0tUa1aNZXnzNHREQBw586dQuvatGkTmjVrBjs7O5X7DQgIQG5urtou1czMTLUac3NzC72PrVu34q+//sL333+v0l6U98HLFAoF9u3bhylTpsDOzg7r16/HsGHD4O7ujk8++UTjMaKLFy/Cz88PHh4eOHjwoNb7+D/55BOVZZs1awbgvx5qUQ0cOFBll1KzZs2Qm5uLmzdvFnibLVu2oEKFCggNDVWb9+ruqefPn6Nr1674448/sHv3brRu3bpIdWi7rZiZmcHY2BiHDx8ucPeNra0tAOCPP/7AixcvCnycxZHf8x41apRKe35PqrBj2k+fPgXw+s88Kysr5eejLjx8+BBHjhxBv379UKlSJZV5+a9Nbm4u9u/fj6CgIFSuXFk538XFBT179sSxY8fUaurfv7/Ka9uwYUMIIdC/f39lm4GBARo0aKDyXt60aRNsbGzQqlUrlde8fv36sLS0VL7m2ij2rjlra2sA//fiaKtKlSpqbVWrVkVmZiYePnyIcuXKISUlBcuWLStwtN2DBw9Uph89egQjIyO1fbaaXL169bWjk2JjYwEAH374ocb5+Y/9+vXrEEJgwoQJmDBhQoG1vvPOO4XeX2BgIE6dOgUAaNOmjcbdL9rsJ8/Ly8O8efOwaNEixMfHq4TAy8dEfH19oVAoMH78eEyZMkW5O/PVEWGxsbG4cOFCgc/Xq69DWFgYwsLC1JZzcnLSePvc3Fx8/fXX6NWrl3IXRL6HDx9Kfh+8ysTEBN988w2++eYb3L9/H9HR0Zg3bx42btwIIyMj/PbbbyrLd+jQAU5OTti3b5/yOdHGqx8O+aEkdX95cdcZFxeHatWqabUbcvr06UhPT8eePXsKHaH1ujq03VZMTEwwY8YMjB49Gk5OTmjUqBHat2+P3r17w9nZGQDg5+eH4OBghIeH48cff4S/vz+CgoLQs2dPmJiYvPYxaePmzZsoV64cvL29VdqdnZ1ha2tbaNDnB9DrPvOePn0q+Qt6YfJDQNPx7XwPHz5EZmYmqlWrpjavRo0ayMvLw+3bt+Hj46Nsf/W1tbGxAQC4ubmptb/8vouNjUVqaqryC+2rXrddvkwnQeTq6oqLFy8Wd1Uq8j8MP/30U4SEhGhc5tUPrYSEBFSqVEnjAfhXeXh4YPny5SptmzZtUvmwy6/h119/VW4kL8vf0POXGzNmDAIDAzXe36tveE1++uknPHr0CJcvX8b06dMxePBgtQ/J7777TvlNO1+HDh1UpqdNm4YJEyagX79+mDx5Muzt7VGuXDmMHDlSJWTq1q2LsLAwhIeHY+3atQXWlZeXh1atWmHs2LEa51etWlVleuDAgejatatK24ABAwpc/y+//IKEhATs27dP430D0t4HhXFxcUH37t0RHBwMHx8fbNy4EatWrVL50A4ODsbq1auxdu1aDBo0SOt1GxgYaGwXrxzglaIk1vmywMBA7N27FzNnzoS/v3+BexNeV4e22woAjBw5Eh06dMD27duxb98+TJgwAdOnT8ehQ4fw7rvvKgflnDx5Ejt37sS+ffvQr18/zJ49GydPnpT05eB1tPmseJW3tzcMDQ1x4cKFApfJzs7GtWvX0KBBA5X70vS6vW5vQUkr6LXV1P5y/Xl5eXB0dCzws0PKzxB0Mlihffv2WLZsGWJiYuDr66vVbfK/Qb3s33//hbm5ufIBWFlZITc3FwEBAa9dX05ODs6fP482bdpodf8WFhZq6z137pzKdP5BXUdHx0JryO8CGxkZaVVrQd5//30AQNu2beHo6IjevXvjm2++QY0aNZTL1K5dW+0+Xn3DbN68GS1atMAvv/yi0p6SkqJ2wD0sLEz5w878DeLV4cReXl5IT0/X+rFVqVJFbVkLCwuNy+b/ZmLo0KHKgQUvc3BwkPQ+0JaRkRHq1KmD2NhYPHr0SOXDc9asWTA0NMTQoUNhZWWFnj176ux+3wQvLy+cOnUKL168eO3B4kaNGmHw4MFo3749unbtim3btkka0PHyfQKv31ZeXn706NEYPXo0YmNjUa9ePcyePVvli1ejRo3QqFEjTJ06FevWrUOvXr2wYcMGfP7555Lre5W7uzvy8vIQGxursn0lJSUhJSVF43sxn4WFBVq0aIFDhw7h5s2bGpfduHEjsrOz0b59e2WbnZ2dxt20r/a+CgrH/M+Zwr70Ozg4wNzcHNeuXVObd/XqVZQrV06tp1NUXl5eOHjwIJo0aQIzM7NirUsnw7fHjh0LCwsLfP7558ohri+Li4vDvHnzVNpiYmJU9u3fvn0bv//+O1q3bg0DAwMYGBggODgYW7Zs0fjEvzp0dP/+/UhNTUXHjh118ZAA/Pdt0draGtOmTdO4rzq/BkdHR/j7+2Pp0qW4f//+a2vVRv6xH22Gkr7KwMBA7ZvXpk2bCjxO5eLighYtWiAgIAABAQFq34q7deuGmJgYjT2WlJQU5OTkSK4x37x585CRkaE2/DSf1PfBq2JjYzX+yj0lJQUxMTGws7NT++amUCiwbNkydOnSBSEhIVoNwS9NgoOD8ejRIyxYsEBtnqZv5AEBAdiwYQP27t2Lzz77TPKPdQHtt5XMzEzlsdx8Xl5esLKyUr7Xnzx5olZnvXr1ABRte9Dko48+AgC1EZ9z5swBALVRg6/69ttvIYRAnz591M4aEx8fj7Fjx8LFxUWlR+3l5YWrV6+qvGfPnz+P48ePq9w+/9DCq8cvHRwc0Lx5c6xYsULtPZ3/fBkYGKB169b4/fffVYbDJyUlYd26dWjatKlyN2lxdevWDbm5uZg8ebLavJycHEm/0dNJj8jLywvr1q3DJ598gho1aqicWeHEiRPYtGmT2u9SatWqhcDAQJXh2wCUvygGgO+//x5RUVFo2LAhBgwYgJo1ayI5ORlnzpzBwYMHlb+ziYiIwJgxY2BiYoJnz56pfKtKTU1Fbm4utm/fjqCgIEmPy9raGosXL8Znn32G9957D927d4eDgwNu3bqFXbt2oUmTJsqNfeHChWjatClq166NAQMGoHLlykhKSkJMTAzu3Lmj9huel02aNAl3795FrVq1YGJigjNnzmDlypWoU6eOpN1O+dq3b49Jkyahb9++aNy4Mf755x+sXbtW5eClFP/73/+wY8cOtG/fHn369EH9+vWRkZGBf/75B5s3b0ZCQsJrhzYXZP/+/Zg6dWqhv+fR9n2gyfnz59GzZ0+0bdsWzZo1g729Pe7evYvVq1fj3r17mDt3rsZdEOXKlcNvv/2GoKAgdOvWDbt37y7w+Edp07t3b6xZswajRo3Cn3/+iWbNmiEjIwMHDx7E0KFDNX5ZCwoKwsqVK9G7d29YW1ur/P5FG9puK//++y9atmyJbt26oWbNmjA0NMS2bduQlJSE7t27AwBWr16NRYsWoVOnTvDy8sLTp0+xfPlyWFtbKwOkuOrWrYuQkBAsW7YMKSkp8PPzw59//onVq1cjKCgILVq0KPT2zZs3xw8//IBRo0ahTp066NOnD1xcXHD16lXlmTd2796tMnilX79+mDNnDgIDA9G/f388ePAAS5YsgY+Pj8oAAjMzM9SsWRMRERGoWrUq7O3tUatWLdSqVQvz589H06ZN8d5772HgwIHw9PREQkICdu3apdyjM2XKFBw4cABNmzbF0KFDYWhoiKVLlyI7OxszZ87UyfMH/Hcsb9CgQZg+fTrOnTuH1q1bw8jICLGxsdi0aRPmzZuHLl26aLcyrcfXaeHff/8VAwYMEB4eHsLY2FhYWVmJJk2aiJ9++kllWDMAMWzYMPHbb7+JKlWqCBMTE/Huu++qDOXNl5SUJIYNGybc3NyEkZGRcHZ2Fi1bthTLli1TLuPu7q4cEl7Q38vDI7Udvp0vKipKBAYGChsbG2Fqaiq8vLxEnz59VIafCyFEXFyc6N27t3B2dhZGRkbinXfeEe3btxebN28u9HnbvHmzeP/994W1tbUwMzMT3t7eYvTo0eLhw4cqNUDC8O3Ro0cLFxcXYWZmJpo0aSJiYmIKHD76qleHbwvx3/Dc8ePHC29vb2FsbCwqVKggGjduLH744Qfx/PlzIUTRhm+7uLiIjIwMlWWhYeiqNu8DTZKSksT3338v/Pz8hIuLizA0NBR2dnbiww8/VHtdXh6+nS8zM1P4+fkJS0tLcfLkSSFEwcO3NT1uTY8lnzbDt18dwqxp2Lum1zUzM1N88803wtPTU/l8denSRTmkt6CaFy1aJACIMWPGSK4jv72wbeXRo0di2LBhonr16sLCwkLY2NiIhg0bio0bNyrXcebMGdGjRw9RqVIlYWJiIhwdHUX79u3VtjdNtB2+LYQQL168EOHh4crnyM3NTYwfP17ls+p1jhw5Ijp27CgqVKggjIyMRKVKlcSAAQNEQkKCxuV/++03UblyZWFsbCzq1asn9u3bp/Z+EkKIEydOiPr16wtjY2O199DFixdFp06dhK2trTA1NRXVqlUTEyZMULn9mTNnRGBgoLC0tBTm5uaiRYsW4sSJEyrLFPTaatoOhPjvfW9hYaH2mJYtWybq168vzMzMhJWVlahdu7YYO3asuHfv3uuePiWFEDo66imBQqHAsGHDNO46KAoPDw9MnDhRrdeV7/Dhw+jTpw9PJklEVArxMhBERCQrvQii/H3JBXFycir0FDtERCQfvdg1R0REby+dXY9IChmyj4iISim92DVHRERvLwYRERHJSpZdc29SXl4e7t27BysrqyKdV4qIqLQRQuDp06dwdXVVnmn/bab3QXTv3j2dnVuJiKg0uX37NipWrCh3GcWm90GUfxr227dv6+wcS0REckpLS4Obm5tOLzMhJ70PovzdcdbW1gwiItIr+nK44e3fuUhERG81BhEREcmKQURERLJiEBERkawYREREJCsGERERyYpBREREsmIQERGRrBhEREQkKwYRERHJikFERESyYhAREZGsGERERCQrBhEREcmKQURERLJiEBERkawYREREJCsGERERyYpBREREsjKUuwAienv9eOBfuUt4633ZqqrcJciOPSIiIpIVg4iIiGTFICIiIlkxiIiISFYMIiIikhWDiIiIZMUgIiIiWTGIiIhIVgwiIiKSFYOIiIhkxSAiIiJZMYiIiEhWDCIiIpIVg4iIiGTFICIiIlkxiIiISFYMIiIikhWDiIiIZMUgIiIiWTGIiIhIVgwiIiKSFYOIiIhkxSAiIiJZMYiIiEhWDCIiIpIVg4iIiGTFICIiIlkxiIiISFYMIiIikhWDiIiIZMUgIiIiWTGIiIhIVgwiIiKSFYOIiIhkxSAiIiJZMYiIiEhWDCIiIpKVrEE0ffp0vP/++7CysoKjoyOCgoJw7do1lWWysrIwbNgwlC9fHpaWlggODkZSUpJMFRMRka7JGkTR0dEYNmwYTp48iQMHDuDFixdo3bo1MjIylMt8+eWX2LlzJzZt2oTo6Gjcu3cPnTt3lrFqIiLSJYUQQshdRL6HDx/C0dER0dHRaN68OVJTU+Hg4IB169ahS5cuAICrV6+iRo0aiImJQaNGjdTWkZ2djezsbOV0Wloa3Nzc8OjRI1hbW7+xx0JUFiyMui53CW+9YS28Jd8mLS0NFSpUQGpqql58rhnKXcDLUlNTAQD29vYAgNOnT+PFixcICAhQLlO9enVUqlSpwCCaPn06wsPD1dr3798Pc3PzEqqcqGzylLsAPbB797+Sb5OZmVkClcin1ARRXl4eRo4ciSZNmqBWrVoAgMTERBgbG8PW1lZlWScnJyQmJmpcz/jx4zFq1CjldH6PqHXr1nrxzYGoNGGPqPiK2iPSJ6UmiIYNG4aLFy/i2LFjxVqPiYkJTExM1NqNjIxgZGRUrHUTkSqhMJC7hLdeUT6X9O2zrFQM3x4+fDj++OMPREVFoWLFisp2Z2dnPH/+HCkpKSrLJyUlwdnZ+Q1XSUREJUHWIBJCYPjw4di2bRsOHToET0/VPc7169eHkZERIiMjlW3Xrl3DrVu34Ovr+6bLJSKiEiDrrrlhw4Zh3bp1+P3332FlZaU87mNjYwMzMzPY2Nigf//+GDVqFOzt7WFtbY3Q0FD4+vpqHKhARERvH1mDaPHixQAAf39/lfaVK1eiT58+AIAff/wR5cqVQ3BwMLKzsxEYGIhFixa94UqJiKikyBpE2vyEydTUFAsXLsTChQvfQEWqfjwgfVglqfqyVVW5SyCiUq5UDFYgIqKyi0FERESyYhAREZGsGERERCQrBhEREcmKQURERLJiEBERkawYREREJCsGERERyYpBREREsmIQERGRrBhEREQkKwYRERHJikFERESyYhAREZGsGERERCQrBhEREcmKQURERLJiEBERkawYREREJCsGERERyYpBREREsmIQERGRrBhEREQkKwYRERHJikFERESyYhAREZGsGERERCQrBhEREcmKQURERLJiEBERkawYREREJCsGERERyYpBREREsmIQERGRrBhEREQkKwYRERHJikFERESyYhAREZGsGERERCQrBhEREcmKQURERLKSHETPnj1DZmamcvrmzZuYO3cu9u/fr9PCiIiobJAcRB07dsSaNWsAACkpKWjYsCFmz56Njh07YvHixTovkIiI9JvkIDpz5gyaNWsGANi8eTOcnJxw8+ZNrFmzBvPnz9d5gUREpN8kB1FmZiasrKwAAPv370fnzp1Rrlw5NGrUCDdv3tR5gUREpN8kB5G3tze2b9+O27dvY9++fWjdujUA4MGDB7C2ttZ5gUREpN8kB9F3332HMWPGwMPDAw0bNoSvry+A/3pH7777rs4LJCIi/WYo9QZdunRB06ZNcf/+fdStW1fZ3rJlS3Tq1EmnxRERkf6THEQA4OzsDGdnZwBAWloaDh06hGrVqqF69eo6LY6IiPSf5F1z3bp1w4IFCwD895uiBg0aoFu3bqhTpw62bNmi8wKJiEi/SQ6iI0eOKIdvb9u2DUIIpKSkYP78+ZgyZYrOCyQiIv0mOYhSU1Nhb28PANi7dy+Cg4Nhbm6Odu3aITY2VucFEhGRfpMcRG5uboiJiUFGRgb27t2rHL795MkTmJqa6rxAIiLSb5IHK4wcORK9evWCpaUlKlWqBH9/fwD/7bKrXbu2rusjIiI9JzmIhg4dig8++AC3b99Gq1atUK7cf52qypUr8xgRERFJVqTh2w0aNECdOnUQHx8PLy8vGBoaol27drqujYiIyoAinWuuf//+MDc3h4+PD27dugUACA0Nxffff6/zAomISL9JDqLx48fj/PnzOHz4sMrghICAAEREROi0OCIi0n+Sd81t374dERERaNSoERQKhbLdx8cHcXFxOi2OiIj0n+Qe0cOHD+Ho6KjWnpGRoRJMRERE2pAcRA0aNMCuXbuU0/nh8/PPPyvPxE1ERKQtybvmpk2bhrZt2+Ly5cvIycnBvHnzcPnyZZw4cQLR0dElUSMREekxyT2ipk2b4ty5c8jJyUHt2rWxf/9+ODo6IiYmBvXr1y+JGomISI8V6XdEXl5eWL58ua5rISKiMqhIQZSXl4fr16/jwYMHyMvLU5nXvHlznRRGRERlg+QgOnnyJHr27ImbN29CCKEyT6FQIDc3V2fFERGR/pMcRIMHD1aOnHNxceGQbSIiKhbJQRQbG4vNmzfD29u7JOohIqIyRvKouYYNG+L69eslUQsREZVBkntEoaGhGD16NBITE1G7dm0YGRmpzK9Tp47OiiMiIv0nOYiCg4MBAP369VO2KRQKCCE4WIGIiCSTHETx8fElUQcREZVRkoPIzs4O1tbWGufx2BEREUklebBCu3btkJWVpdZ+7do1+Pv766ImIiIqQyQHkaWlJTp37oycnBxl25UrV+Dv7688fkRERKQtyUG0detWpKamolevXhBC4OLFi/D390ePHj0wb968kqiRiIj0mOQgMjMzw65du3Dt2jV069YNLVu2RO/evTFnzpySqI+IiPScVoMV0tLSVKbLlSuHiIgItGrVCsHBwZgwYYJymYIGMhAREWmiVRDZ2tpqPKecEAJLlizB0qVL+TsiIiIqEq2CKCoqqqTrICKiMkqrIPLz8yvpOoiIqIySPFhh5cqV2LRpk1r7pk2bsHr1ap0URUREZYfkIJo+fToqVKig1u7o6Ihp06bppCgiIio7JAfRrVu34Onpqdbu7u6OW7du6aQoIiIqOyQHkaOjIy5cuKDWfv78eZQvX14nRRERUdkhOYh69OiBL774AlFRUcjNzUVubi4OHTqEESNGoHv37iVRIxER6THJZ9+ePHkyEhIS0LJlSxga/nfzvLw89O7dm8eIiIhIMsk9ImNjY0RERODq1atYu3Yttm7diri4OKxYsQLGxsaS1nXkyBF06NABrq6uUCgU2L59u8r8Pn36QKFQqPy1adNGaslERFSKSe4R5atatSqqVq1arDvPyMhA3bp10a9fP3Tu3FnjMm3atMHKlSuV0yYmJsW6TyIiKl20CqJRo0Zh8uTJsLCwwKhRowpdVsrJT9u2bYu2bdsWuoyJiQmcnZ21XicREb1dtAqis2fP4sWLF8r/C6LpfHTFdfjwYTg6OsLOzg4ffvghpkyZUujovOzsbGRnZyun80/G+uLFC+Vj0JZC8Lx5xSX1Oae3C7eR4ivKNqJv25VCCCHkLgL4L8S2bduGoKAgZduGDRtgbm4OT09PxMXF4euvv4alpSViYmJgYGCgcT0TJ05EeHi4Wvu6detgbm5eUuUTEb0xmZmZ6NmzJ1JTU/XiigelOohedePGDXh5eeHgwYNo2bKlxmU09Yjc3Nzw6NEjyS/YwqjrkpYndcNaeMtdApUgbiPFV5RtJC0tDRUqVNCbIJI8WCEjIwPff/89IiMj8eDBA+Tl5anMv3Hjhs6Ke1XlypVRoUIFXL9+vcAgMjEx0TigwcjICEZGRpLuTyg097pIe1Kfc3q7cBspvqJsI/q2XUkOos8//xzR0dH47LPP4OLiUiLHhQpy584dPH78GC4uLm/sPomIqGRJDqI9e/Zg165daNKkSbHvPD09Hdev/1/XPj4+HufOnYO9vT3s7e0RHh6O4OBgODs7Iy4uDmPHjoW3tzcCAwOLfd9ERFQ6SA4iOzs72Nvb6+TO//77b7Ro0UI5nT80PCQkBIsXL8aFCxewevVqpKSkwNXVFa1bt8bkyZP5WyIiIj1SpFP8fPfdd1i9enWxR6H5+/ujsLES+/btK9b6iYio9NMqiN59912VY0HXr1+Hk5MTPDw81A6anTlzRrcVEhGRXtMqiAobUk1ERFQcWgVRWFgYjhw5gsaNGyvPuE1ERKQLWp99u0WLFkhOTi7JWoiIqAzSOohKyQkYiIhIz0i6HtGb/PEqERGVDZIO+PTp0+e1v+HZunVrsQoiIqKyRVIQWVlZwczMrKRqISKiMkhSEM2fPx+Ojo4lVQsREZVBWh8j4vEhIiIqCRw1R0REstI6iKKionR2slMiIqJ8Wh8j8vPzU/4fGRlZ4IXxVqxYobvqiIhI70k+X094eDgmTZqEBg0avPEL4xERkf6RHERLlizBqlWr8Nlnn5VEPUREVMZIOrMCADx//hyNGzcuiVqIiKgMkhxEn3/+OdatW1cStRARURkkeddcVlYWli1bhoMHD6JOnTpqF8abM2eOzoojIiL9JzmILly4gHr16gEALl68qDKPAxeIiEgqyUEUFRVVEnUQEVEZJfkYERERkS5p1SPq3LkzVq1aBWtra3Tu3LnQZXkZCCIikkKrILKxsVEe/7GxsSnRgoiIqGzRKohWrlyp8X8iIqLiknyMaP369QXO+9///lesYoiIqOyRHERDhgzBnj171Nq//PJL/PbbbzopioiIyg7JQbR27Vr06NEDx44dU7aFhoZi48aNHNpNRESSSQ6idu3aYdGiRfj4449x+vRpDB06FFu3bkVUVBSqV69eEjUSEZEek/yDVgDo2bMnUlJS0KRJEzg4OCA6Ohre3t66ro2IiMoArYJo1KhRGtsdHBzw3nvvYdGiRco2nmuOiIik0CqIzp49q7Hd29sbaWlpyvk81xwREUmlVRBxEAIREZWUYp9r7ubNm7h8+TLy8vJ0UQ8REZUxWgfRihUr1I7/DBw4EJUrV0bt2rVRq1Yt3L59W+cFEhGRftM6iJYtWwY7Ozvl9N69e7Fy5UqsWbMGf/31F2xtbREeHl4iRRIRkf7Sevh2bGwsGjRooJz+/fff0bFjR/Tq1QsAMG3aNPTt21f3FRIRkV7Tukf07NkzWFtbK6dPnDiB5s2bK6crV66MxMRE3VZHRER6T+sgcnd3x+nTpwEAjx49wqVLl9CkSRPl/MTERF4igoiIJNN611xISAiGDRuGS5cu4dChQ6hevTrq16+vnH/ixAnUqlWrRIokIiL9pXUQjR07FpmZmdi6dSucnZ2xadMmlfnHjx9Hjx49dF4gERHpN62DqFy5cpg0aRImTZqkcf6rwURERKSNYv+glYiIqDgYREREJCsGERERyYpBREREsipyED1//hzXrl1DTk6OLushIqIyRnIQZWZmon///jA3N4ePjw9u3boFAAgNDcX333+v8wKJiEi/SQ6i8ePH4/z58zh8+DBMTU2V7QEBAYiIiNBpcUREpP+0/h1Rvu3btyMiIgKNGjVSuSKrj48P4uLidFocERHpP8k9oocPH8LR0VGtPSMjg5cKJyIiySQHUYMGDbBr1y7ldH74/Pzzz/D19dVdZUREVCZI3jU3bdo0tG3bFpcvX0ZOTg7mzZuHy5cv48SJE4iOji6JGomISI9J7hE1bdoU586dQ05ODmrXro39+/fD0dERMTExKmfjJiIi0obkHhEAeHl5Yfny5bquhYiIyiDJQZSWllbo/Jev4kpERPQ6koPIzs5OY7sQAgqFArm5ucUuioiIyg7JQeTp6YkHDx5g3LhxKpcKJyIiKgrJQXTlyhX89NNPmDp1Ks6ePYuZM2fC09OzJGojIqIyQPKoOSMjI4waNQqxsbF45513UKdOHYwePRopKSklUB4REem7Ip99297eHnPnzsXZs2eRkJAAb29vzJ07V4elERFRWSB519y7776rdiofIQSys7MxevRojBw5Ule1ERFRGSA5iIKCgkqgDCIiKqskB1FYWFhJ1EFERGUULxVORESyKtIPWgu73ENycnKxCiIiorJFchDlj4wTQmDIkCGYNGmSxusTERERaUNyEIWEhCj/Dw0NRXBwMCpXrqzTooiIqOzgMSIiIpJVsYOIlwcnIqLikLxrrnPnzsr/s7KyMHjwYFhYWCjbtm7dqpvKiIioTJAcRDY2Nsr/P/30U50WQ0REZY/kIFq5cmVJ1EFERGVUkY4R5eTk4ODBg1i6dCmePn0KALh37x7S09N1WhwREek/yT2imzdvok2bNrh16xays7PRqlUrWFlZYcaMGcjOzsaSJUtKok4iItJTkntEI0aMQIMGDfDkyROYmZkp2zt16oTIyEidFkdERPpPco/o6NGjOHHiBIyNjVXaPTw8cPfuXZ0VRkREZYPkHlFeXh5yc3PV2u/cuQMrKyudFEVERGWH5CBq3bq1ypVYFQoF0tPTERYWho8++kiXtRERURkgedfc7NmzERgYiJo1ayIrKws9e/ZEbGwsKlSogPXr15dEjUREpMckB1HFihVx/vx5bNiwARcuXEB6ejr69++PXr16qQxeICIi0obkIAIAQ0NDnlWBiIh0QnIQ7dixo9D5H3/8cZGLISKiskdyEAUFBalMKxQKCCGU/2saUUdERFSQIg3ffvnP3Nwc169fL3BYNxERUWF4PSIiIpJVsYIoISEBGRkZ/CErEREVWZEvjPfs2TOcPHkSLVu2hIODg84LIyKisqHIF8ZzdnZGhw4d0K9fP50XRUREZQcvjEdERLIq1jGirKwspKWlqfxJceTIEXTo0AGurq5QKBTYvn27ynwhBL777ju4uLjAzMwMAQEBiI2NLU7JRERUykgOooyMDAwfPhyOjo6wsLCAnZ2dyp/UddWtWxcLFy7UOH/mzJmYP38+lixZglOnTsHCwgKBgYHIysqSWjYREZVSkoNo7NixOHToEBYvXgwTExP8/PPPCA8Ph6urK9asWSNpXW3btsWUKVPQqVMntXlCCMydOxfffvstOnbsiDp16mDNmjW4d++eWs+JiIjeXpKPEe3cuRNr1qyBv78/+vbti2bNmsHb2xvu7u5Yu3YtevXqpZPC4uPjkZiYiICAAGWbjY0NGjZsiJiYGHTv3l3j7bKzs5Gdna2czt9d+OLFC7x48UJSDQrBH+gWl9TnnN4u3EaKryjbiL5tV5KDKDk5GZUrVwYAWFtbIzk5GQDQtGlTDBkyRGeFJSYmAgCcnJxU2p2cnJTzNJk+fTrCw8PV2vfv3w9zc3NJNXhKWpo02b37X7lLoBLEbaT4irKNZGZmlkAl8pEcRJUrV0Z8fDwqVaqE6tWrY+PGjfjggw+wc+dO2NralkCJ0owfPx6jRo1STqelpcHNzQ2tW7eGtbW1pHUtjLqu6/LKnGEtvOUugUoQt5HiK8o2InVgWGknOYj69u2L8+fPw8/PD+PGjUOHDh2wYMECvHjxAnPmzNFZYc7OzgCApKQkuLi4KNuTkpJQr169Am9nYmICExMTtXYjIyMYGRlJqkEoDCQtT+qkPuf0duE2UnxF2Ub0bbuSHERffvml8v+AgABcvXoVp0+fhre3N+rUqaOzwjw9PeHs7IzIyEhl8KSlpeHUqVM63QVIRETyKtKF8V7m7u4Od3f3It02PT0d16//X9c+Pj4e586dg729PSpVqoSRI0diypQpqFKlCjw9PTFhwgS4urqqXYqCiIjeXpKDaP78+YXO/+KLL7Re199//40WLVoop/OP7YSEhGDVqlUYO3YsMjIyMHDgQKSkpKBp06bYu3cvTE1NpZZNRESllELkX9VOS56e/zdO5vbt23BxcYGh4X95plAocOPGDd1WWExpaWmwsbFBamqq5MEKPx7giK/i+rJVVblLoBLEbaT4irKNFOdzrTSS3COKj49X/m9lZYXo6GjlcG4iIiKpin1hPCIiouJgEBERkawk75q7cOGC8n8hBK5evYr09HRlmy6HcBMRkf6THET16tWDQqFA/hiH9u3bK6cVCgVyc3nuKSIi0l6xBisQEREVl+QgKuqPV4mIiDSRPFghKysLU6ZMQXh4OLKysrB+/Xp8/PHHmDhxInJyckqiRiIi0mOSe0ShoaGIjIyEtbU1Ll26hFOnTiE4OBhLly5FZmYmZs6cWRJ1EhGRnirShfG2bNmCKlWqwNnZGTt27ED79u3h7++PESNGMIiIiEgSybvmUlJS4OHhAUdHR5ibm6N69eoA/htNV9gF64iIiDSRHEROTk64d+8eAGDZsmXKawWlpKTA3t5et9UREZHek7xrbvTo0cjLywMA9OzZU9l+5swZtG/fXneVERFRmSA5iAq6zEOfPn3Qp0+f4tZDRERlDM81R0REsmIQERGRrBhEREQkKwYRERHJqshB9Pz5c1y7do2n9SEiomKRHESZmZno378/zM3N4ePjg1u3bgH479Q/33//vc4LJCIi/SY5iMaPH4/z58/j8OHDMDU1VbYHBAQgIiJCp8UREZH+k/w7ou3btyMiIgKNGjWCQqFQtvv4+CAuLk6nxRERkf6T3CN6+PAhHB0d1dozMjJUgomIiEgbkoOoQYMG2LVrl3I6P3x+/vln+Pr66q4yIiIqEyTvmps2bRratm2Ly5cvIycnB/PmzcPly5dx4sQJREdHl0SNRESkxyT3iJo2bYpz584hJycHtWvXxv79++Ho6IiYmBjUr1+/JGokIiI9JrlHBABeXl5Yvny5rmshIqIyqEg/aI2Li8O3336Lnj174sGDBwCAPXv24NKlSzotjoiI9J/kIIqOjkbt2rVx6tQpbNmyBenp6QCA8+fPIywsTOcFEhGRfpMcROPGjcOUKVNw4MABGBsbK9s//PBDnDx5UqfFERGR/pMcRP/88w86deqk1u7o6IhHjx7ppCgiIio7JAeRra0t7t+/r9Z+9uxZvPPOOzopioiIyg7JQdS9e3d89dVXSExMhEKhQF5eHo4fP44xY8agd+/eJVEjERHpMclBNG3aNFSvXh1ubm5IT09HzZo10bx5czRu3BjffvttSdRIRER6TPLviIyNjbF8+XJMmDABFy9eRHp6Ot59911UqVKlJOojIiI9V6QftAJApUqVUKlSJV3WQkREZZDkIBo1alSh8+fMmVPkYoiIqOyRHERnz55V/n/s2DHUr18fZmZmAMDLQBARkWSSgygqKkr5v5WVFdatW4fKlSvrtCgiIio7inSuOSIiIl1hEBERkawk75rbsWOH8v+8vDxERkbi4sWLyraPP/5YN5UREVGZIDmIgoKCVKYHDRqk/F+hUCA3N7fYRRERUdkhOYjy8vJKog4iIiqjeIyIiIhkJblHlJaWprH9wYMHqFatGmxsbODk5IQrV64UuzgiItJ/koPI1tZW4w9XhRBQKBRITk7WSWFERFQ2FOlcc5s3b4a9vb1K2+PHj9G1a1edFEVERGVHkYKoSZMmcHR0VGlLSkrSSUFERFS2FCmILl++jMePH8Pa2hqurq48xxwRERVZkYKoZcuWyv+NjY3RuHFjdO7cWWdFERFR2SE5iOLj4wEA2dnZePz4MW7cuIHo6Gh89dVXOi+OiIj0n+Qgcnd3V5n29fVFr1698Omnn8Lf3x+VK1eGg4MDTp06pbMiiYhIfxX5Cq2vatq0qbK3ZGBgoKvVEhGRnitSEOXk5ODw4cOIi4tDz549YWVlhcTERJQvXx6Wlpa6rpGIiPSY5CC6efMm2rRpg1u3biE7OxutWrWClZUVZsyYgezsbCxZsqQk6iQiIj0l+VxzI0aMQIMGDfDkyRPlJcIBoFOnToiMjNRpcUREpP8k94iOHj2KEydOwNjYWKXdw8MDd+/e1VlhRERUNkjuEeXl5Wm85tCdO3dgZWWlk6KIiKjskBxErVu3xty5c5XTCoUC6enpCAsLw0cffaTL2oiIqAyQvGtu9uzZCAwMRM2aNZGVlYWePXsiNjYWFSpUwPr160uiRiIi0mOSg6hixYo4f/48NmzYgAsXLiA9PR39+/dHr169VAYvEBERaaNIvyMyNDTEp59+qutaiIioDCpSEF27dg0//fST8iqsNWrUwPDhw1G9enWdFkdERPpP8mCFLVu2oFatWjh9+jTq1q2LunXr4syZM6hduza2bNlSEjUSEZEek9wjGjt2LMaPH49JkyaptIeFhWHs2LEIDg7WWXFERKT/JPeI7t+/j969e6u1f/rpp7h//75OiiIiorJDchD5+/vj6NGjau3Hjh1Ds2bNdFIUERGVHZJ3zX388cf46quvcPr0aTRq1AgAcPLkSWzatAnh4eHYsWOHyrJERESFUQghhJQblCunXSdKoVBoPBXQm5aWlgYbGxukpqbC2tpa0m1/PPBvCVVVdnzZqqrcJVAJ4jZSfEXZRorzuVYaSe4R5eXllUQdRERURkk+RkRERKRLWgfRoUOHULNmTaSlpanNS01NhY+PD44cOaLT4oiISP9pHURz587FgAEDNO6PtLGxwaBBg/Djjz/qtDgiItJ/WgfR+fPn0aZNmwLnt27dGqdPn9ZJUUREVHZoHURJSUkwMjIqcL6hoSEePnyok6KIiKjs0DqI3nnnHVy8eLHA+RcuXICLi4tOiiIiorJD6yD66KOPMGHCBGRlZanNe/bsGcLCwtC+fXudFkdERPpP698Rffvtt9i6dSuqVq2K4cOHo1q1agCAq1evYuHChcjNzcU333xTYoUSEZF+0jqInJyccOLECQwZMgTjx49H/gkZFAoFAgMDsXDhQjg5OZVYoUREpJ8knVnB3d0du3fvxpMnT3D9+nUIIVClShXY2dmVVH1ERKTninSFVjs7O7z//vu6roWIiMognuKHiIhkxSAiIiJZMYiIiEhWDCIiIpIVg4iIiGTFICIiIlmV6iCaOHEiFAqFyl/16tXlLouIiHSoSL8jepN8fHxw8OBB5bShYakvmYiIJCj1n+qGhoZwdnaWuwwiIiohpT6IYmNj4erqClNTU/j6+mL69OmoVKlSgctnZ2cjOztbOZ1/afMXL17gxYsXku5bIXKLVjQpSX3O6e3CbaT4irKN6Nt2pRD5Zy8thfbs2YP09HRUq1YN9+/fR3h4OO7evYuLFy/CyspK420mTpyI8PBwtfZ169bB3Ny8pEsmIipxmZmZ6NmzJ1JTU2FtbS13OcVWqoPoVSkpKXB3d8ecOXPQv39/jcto6hG5ubnh0aNHkl+whVHXi1UvAcNaeMtdApUgbiPFV5RtJC0tDRUqVNCbICr1u+ZeZmtri6pVq+L69YLf/CYmJjAxMVFrNzIyKvRS55oIhYHkGkmV1Oec3i7cRoqvKNuIvm1XpXr49qvS09MRFxfHS5ITEemRUh1EY8aMQXR0NBISEnDixAl06tQJBgYG6NGjh9ylERGRjpTqXXN37txBjx498PjxYzg4OKBp06Y4efIkHBwc5C6NiIh0pFQH0YYNG+QugYiISlip3jVHRET6j0FERESyYhAREZGsGERERCQrBhEREcmKQURERLJiEBERkawYREREJCsGERERyYpBREREsmIQERGRrBhEREQkKwYRERHJikFERESyYhAREZGsGERERCQrBhEREcmKQURERLJiEBERkawYREREJCsGERERyYpBREREsmIQERGRrBhEREQkKwYRERHJikFERESyYhAREZGsGERERCQrBhEREcmKQURERLJiEBERkawYREREJCsGERERyYpBREREsmIQERGRrBhEREQkKwYRERHJikFERESyYhAREZGsGERERCQrBhEREcmKQURERLJiEBERkawYREREJCsGERERyYpBREREsmIQERGRrBhEREQkKwYRERHJikFERESyYhAREZGsGERERCQrBhEREcmKQURERLJiEBERkawYREREJCsGERERyYpBREREsmIQERGRrBhEREQkKwYRERHJikFERESyYhAREZGsGERERCQrBhEREcmKQURERLJiEBERkawYREREJCsGERERyYpBREREsmIQERGRrBhEREQkKwYRERHJikFERESyYhAREZGsGERERCQrBhEREcmKQURERLJiEBERkawYREREJCsGERERyYpBREREsmIQERGRrBhEREQkKwYRERHJikFERESyYhAREZGsGERERCQrBhEREcnqrQiihQsXwsPDA6ampmjYsCH+/PNPuUsiIiIdKfVBFBERgVGjRiEsLAxnzpxB3bp1ERgYiAcPHshdGhER6UCpD6I5c+ZgwIAB6Nu3L2rWrIklS5bA3NwcK1askLs0IiLSAUO5CyjM8+fPcfr0aYwfP17ZVq5cOQQEBCAmJkbjbbKzs5Gdna2cTk1NBQAkJyfjxYsXku4/Oz21CFXTyx4/fix3CVSCuI0UX1G2kadPnwIAhBC6LkcWpTqIHj16hNzcXDg5Oam0Ozk54erVqxpvM336dISHh6u1e3p6lkiNVLjxr1+EqEwrzjby9OlT2NjY6KwWuZTqICqK8ePHY9SoUcrpvLw8JCcno3z58lAoFDJWpltpaWlwc3PD7du3YW1tLXc5RKWSvm4nQgg8ffoUrq6ucpeiE6U6iCpUqAADAwMkJSWptCclJcHZ2VnjbUxMTGBiYqLSZmtrW1Ilys7a2lqvNjCikqCP24k+9ITylerBCsbGxqhfvz4iIyOVbXl5eYiMjISvr6+MlRERka6U6h4RAIwaNQohISFo0KABPvjgA8ydOxcZGRno27ev3KUREZEOlPog+uSTT/Dw4UN89913SExMRL169bB37161AQxljYmJCcLCwtR2QxLR/+F28nZQCH0Z/0dERG+lUn2MiIiI9B+DiIiIZMUgIiIiWTGIiIhIVgyitxQvjUFUsCNHjqBDhw5wdXWFQqHA9u3b5S6JCsEgegvx0hhEhcvIyEDdunWxcOFCuUshLXD49luoYcOGeP/997FgwQIA/51tws3NDaGhoRg3bpzM1RGVLgqFAtu2bUNQUJDcpVAB2CN6y+RfGiMgIEDZ9rpLYxARlWYMordMYZfGSExMlKkqIqKiYxAREZGsGERvmaJcGoOIqDRjEL1leGkMItI3pf7s26SOl8YgKlx6ejquX7+unI6Pj8e5c+dgb2+PSpUqyVgZacLh22+pBQsWYNasWcpLY8yfPx8NGzaUuyyiUuHw4cNo0aKFWntISAhWrVr15guiQjGIiIhIVjxGREREsmIQERGRrBhEREQkKwYRERHJikFERESyYhAREZGsGERERCQrBhEREcmKQURlxi+//ILWrVvLXQbpwLhx4xAaGip3GaQjDCI9dvv2bfTr1w+urq4wNjaGu7s7RowYgcePH0taT0JCAhQKBc6dO1cyhb4BWVlZmDBhAsLCwlTaN23ahOrVq8PU1BS1a9fG7t27ZarwzZs6dSoaN24Mc3Nz2Nrayl2OJGPGjMHq1atx48YNuUshHWAQ6akbN26gQYMGiI2Nxfr163H9+nUsWbJEeZbu5ORkuUt8ozZv3gxra2s0adJE2XbixAn06NED/fv3x9mzZxEUFISgoCBcvHhRxkrfnOfPn6Nr164YMmSI3KVIVqFCBQQGBmLx4sVyl0K6IEgvtWnTRlSsWFFkZmaqtN+/f1+Ym5uLwYMHK9sAiG3btqksZ2NjI1auXKmc//Kfn5+fcrlffvlF1KxZUxgbGwtnZ2cxbNgw5bybN2+Kjz/+WFhYWAgrKyvRtWtXkZiYqJwfFhYm6tatK3755Rfh5uYmLCwsxJAhQ0ROTo6YMWOGcHJyEg4ODmLKlCkqtT158kT0799fVKhQQVhZWYkWLVqIc+fOFfp8tGvXTowZM0alrVu3bqJdu3YqbQ0bNhSDBg0qdF3Fkf+YXxYVFSUAiCdPnijbjh49Kpo2bSpMTU1FxYoVRWhoqEhPTxdCCOHn56f2muT/hYWFSa5p5cqVwsbGpugPqgj392rdLz8nOTk5ol+/fsLDw0OYmpqKqlWrirlz56qtZ/Xq1aJixYpvrG4qOewR6aHk5GTs27cPQ4cOhZmZmco8Z2dn9OrVCxERERBanu/2zz//BAAcPHgQ9+/fx9atWwEAixcvxrBhwzBw4ED8888/2LFjB7y9vQH8d42kjh07Ijk5GdHR0Thw4ABu3LiBTz75RGXdcXFx2LNnD/bu3Yv169fjl19+Qbt27XDnzh1ER0djxowZ+Pbbb3Hq1Cnlbbp27YoHDx5gz549OH36NN577z20bNmy0F7esWPH0KBBA5W2mJgYBAQEqLQFBgYiJiamwPUcPXoUlpaWhf6tXbtWi2e1YHFxcWjTpg2Cg4Nx4cIFRERE4NixYxg+fDgAYOvWrbh//z7u378PX19fjB49Wjk9ZsyYYt336wwePPi1j18b1tbWyppHjx6tMi8vLw8VK1bEpk2bcPnyZXz33Xf4+uuvsXHjRpXlPvjgA9y5cwcJCQm6engkE16PSA/FxsZCCIEaNWponF+jRg08efIEDx8+hKOj42vX5+DgAAAoX768ylVgp0yZgtGjR2PEiBHKtvfffx8AEBkZiX/++Qfx8fFwc3MDAKxZswY+Pj7466+/lMvl5eVhxYoVsLKyQs2aNdGiRQtcu3YNu3fvRrly5VCtWjXMmDEDUVFRaNiwIY4dO4Y///wTDx48gImJCQDghx9+wPbt27F582YMHDhQrf6UlBSkpqbC1dVVpT0xMRFOTk4qbU5OTkhMTCzwuWjQoMFrj5W9uk6ppk+fjl69emHkyJEAgCpVqmD+/Pnw8/PD4sWLYW9vr1zW2NgYlpaWb+zqvJMmTSp22GVnZ8PY2FhZ86vhZWRkhPDwcOW0p6cnYmJisHHjRnTr1k3Znv963rx5Ex4eHsWqieTFINJj2vZ4iuLBgwe4d+8eWrZsqXH+lStX4ObmpgwhAKhZsyZsbW1x5coVZRB5eHjAyspKuYyTkxMMDAxQrlw5lbYHDx4AAM6fP4/09HSUL19e5f6ePXuGuLg4jbU8e/YMAGBqalqER6rKzMxM2esrqn/++Uflwzc3N1dl/vnz53HhwgWVnpUQAnl5eYiPjy/wC8ab4OjoqNWXl8I8fvwY1tbWhS6zcOFCrFixArdu3cKzZ8/w/Plz1KtXT2WZ/N5+ZmZmseoh+TGI9JC3tzcUCgWuXLmCTp06qc2/cuUK7OzslD0dhUKhFlovXrwo9D5e3eVXVEZGRirTCoVCY1teXh6A/6686eLigsOHD6utq6CRX+XLl4dCocCTJ09U2p2dnZGUlKTSlpSUVGjv4ujRo2jbtm2B8wFg6dKl6NWrV4Hzq1Wrhh07diinT506hU8//VQ5nZ6ejkGDBuGLL75Qu63cVxcdPHgwfvvtt0KXSU9PL3T+jRs34OnpWeD8DRs2YMyYMZg9ezZ8fX1hZWWFWbNmqeyeBaDcFZv/Pqa3F4NID5UvXx6tWrXCokWL8OWXX6qERmJiItauXYvevXtDoVAA+G9Dvn//vnKZ2NhYlW+ZxsbGAFS/uVtZWcHDwwORkZEar4RZo0YN3L59G7dv31b2ii5fvoyUlBTUrFmzyI/tvffeQ2JiIgwNDbXeHWNsbIyaNWvi8uXLKr8j8vX1RWRkpHIXGAAcOHAAvr6+Ba5LF7vmjI2NVXpVd+7cUZn/3nvv4fLly8XueZUEXeyaO3LkSKFBffz4cTRu3BhDhw5Vtmnq7V68eBFGRkbw8fEpVj0kPwaRnlqwYAEaN26MwMBATJkyBZ6enrh06RL+97//4Z133sHUqVOVy3744YdYsGABfH19kZubi6+++kqlV+Lo6AgzMzPs3bsXFStWhKmpKWxsbDBx4kQMHjwYjo6OaNu2LZ4+fYrjx48jNDQUAQEBqF27Nnr16oW5c+ciJycHQ4cOhZ+fn9qgASkCAgLg6+uLoKAgzJw5E1WrVsW9e/ewa9cudOrUqcB1BwYG4tixYyqhM2LECPj5+WH27Nlo164dNmzYgL///hvLli0r8P51sWvudb766is0atQIw4cPx+effw4LCwtcvnwZBw4cwIIFC3R2P7du3UJycjJu3bqF3NxcZcB6e3sXOOigOLvmnj17hp9//hlxcXFo27at8lhceno6cnJykJycDHt7e1SpUgVr1qzBvn374OnpiV9//RV//fWXWi/q6NGjaNasmc565yQjWcfsUYlKSEgQISEhwsnJSRgZGQk3NzcRGhoqHj16pLLc3bt3RevWrYWFhYWoUqWK2L17t8rwbSGEWL58uXBzcxPlypVTGb69ZMkSUa1aNWFkZCRcXFxEaGiocp62w7dfFhISIjp27KjS5ufnJ0aMGKGcTktLE6GhocLV1VX5uHr16iVu3bpV4HNx6dIlYWZmJlJSUlTaN27cKKpWrSqMjY2Fj4+P2LVrV4Hr0AVth2//+eefolWrVsLS0lJYWFiIOnXqiKlTp6qtz8/PT+OQ7bCwMOHu7l5oLSEhIRqHgEdFRUl/YFrQNGwbGn4WkJWVJfr06SNsbGyEra2tGDJkiBg3bpza81atWjWxfv36EqmV3iyFECV4RJuoFOnatSvee+89jB8/Xu5SSlxISAgUCgVWrVoldylKq1atwuHDhzXWdO7cOYwcOVLjsT9N9uzZg9GjR+PChQswNOSOnbcdf0dEZcasWbO0/p3L20wIgcOHD2Py5Mlyl6LCzMwMNjY2GucZGRmpDEt/nYyMDKxcuZIhpCfYIyIiIlmxR0RERLJiEBERkawYREREJCsGERERyYpBREREsmIQERGRrBhEREQkKwYRERHJikFERESy+n86XRN9w9BZMQAAAABJRU5ErkJggg==",
|
||
"text/plain": [
|
||
"<Figure size 400x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 400x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 400x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 400x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 400x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import matplotlib.pyplot as plt\n",
|
||
"# Создание диаграмм зависимости\n",
|
||
"for column in numeric_columns:\n",
|
||
" plt.figure(figsize=(4, 6)) # Установка размера графика\n",
|
||
" if pd.api.types.is_numeric_dtype(df[column]): # Проверяем, является ли колонка числовой\n",
|
||
" # Проверяем, содержит ли колонка только два уникальных значения (0 и 1)\n",
|
||
" if df[column].nunique() == 2 and set(df[column].unique()).issubset({0, 1}):\n",
|
||
" counts = df[column].value_counts() \n",
|
||
" counts.plot(kind='bar', width=0.4) # Создаем столбчатую диаграмму\n",
|
||
" plt.title(f'Количество значений для {column}')\n",
|
||
" plt.xlabel(column)\n",
|
||
" plt.ylabel('Количество повторений')\n",
|
||
" else:\n",
|
||
" grouped_data = df.groupby('Outcome')[column].mean()\n",
|
||
"\n",
|
||
" # Создаем столбчатую диаграмму\n",
|
||
" plt.bar(grouped_data.index, grouped_data.values, alpha=0.5, width=0.4)\n",
|
||
" plt.title(f'Среднее значение {column} по Outcome')\n",
|
||
" plt.xlabel('Outcome (0 = нет, 1 = да)')\n",
|
||
" plt.ylabel(f'Среднее значение {column}')\n",
|
||
" plt.xticks([0, 1]) # Установка меток по оси X\n",
|
||
" plt.grid(axis='y')\n",
|
||
" else:\n",
|
||
" # Если колонка не числовая, строим столбчатую диаграмму\n",
|
||
" counts = df[column].value_counts() # Считаем количество повторений каждого значения\n",
|
||
" counts.plot(kind='bar', width=0.4) # Создаем столбчатую диаграмму\n",
|
||
" plt.title(f'Количество значений для {column}')\n",
|
||
" plt.xlabel(column)\n",
|
||
" plt.ylabel('Количество повторений')\n",
|
||
"\n",
|
||
" plt.show() # Отображение графика"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"#### Разобьем наш набор на выборки относительно параметра Outcome:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 351,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Функция для создания выборок\n",
|
||
"from sklearn.model_selection import train_test_split\n",
|
||
"\n",
|
||
"def split_stratified_into_train_val_test(\n",
|
||
" df_input,\n",
|
||
" stratify_colname=\"y\",\n",
|
||
" frac_train=0.6,\n",
|
||
" frac_val=0.15,\n",
|
||
" frac_test=0.25,\n",
|
||
" random_state=None,\n",
|
||
"):\n",
|
||
"\n",
|
||
" if frac_train + frac_val + frac_test != 1.0:\n",
|
||
" raise ValueError(\n",
|
||
" \"fractions %f, %f, %f do not add up to 1.0\"\n",
|
||
" % (frac_train, frac_val, frac_test)\n",
|
||
" )\n",
|
||
"\n",
|
||
" if stratify_colname not in df_input.columns:\n",
|
||
" raise ValueError(\"%s is not a column in the dataframe\" % (stratify_colname))\n",
|
||
"\n",
|
||
" X = df_input # содержит все столбцы\n",
|
||
" y = df_input[\n",
|
||
" [stratify_colname]\n",
|
||
" ] # датафрейм с колонкой, относительно которой разбиваем\n",
|
||
"\n",
|
||
" # Разделяем датафрейм на обучающую выборку и временную\n",
|
||
" df_train, df_temp, y_train, y_temp = train_test_split(\n",
|
||
" X, y, stratify=y, test_size=(1.0 - frac_train), random_state=random_state\n",
|
||
" )\n",
|
||
"\n",
|
||
" # разделяем временную на тестовую и контрольную\n",
|
||
" relative_frac_test = frac_test / (frac_val + frac_test)\n",
|
||
" df_val, df_test, y_val, y_test = train_test_split(\n",
|
||
" df_temp,\n",
|
||
" y_temp,\n",
|
||
" stratify=y_temp,\n",
|
||
" test_size=relative_frac_test,\n",
|
||
" random_state=random_state,\n",
|
||
" )\n",
|
||
" # проверяем, что в сумме все три выборки дают то же количество значений, что и было в изначальной выборке\n",
|
||
" assert len(df_input) == len(df_train) + len(df_val) + len(df_test)\n",
|
||
"\n",
|
||
" return df_train, df_val, df_test"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 352,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Outcome\n",
|
||
"0 500\n",
|
||
"1 268\n",
|
||
"Name: count, dtype: int64\n",
|
||
"\n",
|
||
"Обучающая выборка: (460, 9)\n",
|
||
"Outcome\n",
|
||
"0 299\n",
|
||
"1 161\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 200x200 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Контрольная выборка: (154, 9)\n",
|
||
"Outcome\n",
|
||
"0 101\n",
|
||
"1 53\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 200x200 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Тестовая выборка: (154, 9)\n",
|
||
"Outcome\n",
|
||
"0 100\n",
|
||
"1 54\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAekAAADECAYAAAC7i9nLAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAA1QklEQVR4nO3dd1xT1/sH8E8SEvbeKAKKiHug8lNkuEWsq9a6t1Kr1tZ+v7S2tY5qtdpq3drWPeqs2lonVr/uDbiQooIiKks2hITk/P6gSbkkICBwQ3jerxev1puTc597cnOfnHPPvVfAGGMghBBCiM4R8h0AIYQQQrSjJE0IIYToKErShBBCiI6iJE0IIYToKErShBBCiI6iJE0IIYToKErShBBCiI6iJE0IIYToKErShBBCajXGGF6/fo3Y2Fi+Q6lylKQJIYRode/ePRw+fFj978jISPz555/8BVRMdnY2vvrqKzRp0gQSiQS2trbw8vJCTEwM36FVqQol6a1bt0IgEKj/jIyM4OXlhenTpyMpKam6YiSkzrh06RIGDRoER0dHGBoawt3dHaGhoXj27Fml68zLy8O8efNw7ty5qguU1AnZ2dkIDQ3F1atXERsbi5kzZ+Lu3bt8h4W0tDR06tQJq1atwpAhQ3DkyBGcPn0a586dg7u7O9/hVSmDyrxpwYIF8PDwgFQqxcWLF7F+/XocO3YM9+7dg4mJSVXHSEidsHr1asycORMNGzbEjBkz4OzsjOjoaPzyyy/Yu3cvjh07hs6dO1e43ry8PMyfPx8AEBQUVMVRE33WqVMn9R8AeHl5YfLkyTxHBfz3v//Fy5cvceXKFTRv3pzvcKpVpZJ0cHAw2rdvDwCYNGkSbG1tsXz5chw5cgTDhw+v0gAJqQsuXbqEjz/+GF26dMGJEyc4P3anTp0KPz8/DBkyBPfv34e1tTWPkZK65vDhw3jw4AHy8/PRsmVLSCQSXuNJTk7Gtm3bsGHDBr1P0EAVnZPu1q0bACAuLg4A8Pr1a/znP/9By5YtYWZmBgsLCwQHByMqKkrjvVKpFPPmzYOXlxeMjIzg7OyMwYMH4/HjxwCA+Ph4zhB7yb/iPYNz585BIBBg7969+OKLL+Dk5ARTU1P0798fCQkJGuu+du0a+vTpA0tLS5iYmCAwMBCXLl3Suo1BQUFa1z9v3jyNsjt37oSPjw+MjY1hY2ODYcOGaV1/WdtWnFKpxI8//ojmzZvDyMgIjo6OCA0NRXp6Oqecu7s7+vXrp7Ge6dOna9SpLfZly5ZptCkAFBQUYO7cufD09IShoSFcXV0RFhaGgoICrW1VXFBQkEZ9ixYtglAoxO7duyvVHt9//z06d+4MW1tbGBsbw8fHBwcOHNC6/p07d6Jjx44wMTGBtbU1AgICcOrUKU6Z48ePIzAwEObm5rCwsECHDh00Ytu/f7/6M7Wzs8OoUaOQmJjIKTNu3DhOzNbW1ggKCsKFCxfe2E7ffPMNBAIBtm3bpjEa1ahRIyxduhQvX77Exo0b1cu1ta0qDtWQX3x8POzt7QEA8+fP17rfPnz4EEOHDoW9vT2MjY3RpEkTfPnll5w6IyIiEBwcDAsLC5iZmaF79+64evUqp4zqdNjFixfx0Ucfwd7eHlZWVggNDYVMJkNGRgbGjBkDa2trWFtbIywsDCUfwlfefV2byrZ/yfdp+4uPj1eXP378OPz9/WFqagpzc3OEhITg/v37GvWW1a7z5s174zqLn56o6v1v3bp1aN68OQwNDeHi4oJp06YhIyODU6b4/tWsWTP4+PggKipK63dSm5LHTDs7O4SEhODevXuccgKBANOnTy+1HtV+pfoMbty4AaVSCZlMhvbt28PIyAi2trYYPny41tNCf/31l/rzsrKywoABAxAdHc0po/o8VJ+ZhYUFbG1tMXPmTEilUo14i39/CgsL0bdvX9jY2ODBgwecsuXNBWWpVE+6JFVCtbW1BQA8efIEhw8fxnvvvQcPDw8kJSVh48aNCAwMxIMHD+Di4gIAUCgU6NevH86cOYNhw4Zh5syZyM7OxunTp3Hv3j00atRIvY7hw4ejb9++nPXOnj1bazyLFi2CQCDAZ599huTkZPz444/o0aMHIiMjYWxsDKDogwsODoaPjw/mzp0LoVCILVu2oFu3brhw4QI6duyoUW/9+vWxePFiAEBOTg6mTp2qdd1z5szB0KFDMWnSJKSkpGD16tUICAhAREQErKysNN4zZcoU+Pv7AwB+++03HDp0iPN6aGgotm7divHjx+Ojjz5CXFwc1qxZg4iICFy6dAlisVhrO1RERkaGetuKUyqV6N+/Py5evIgpU6agadOmuHv3LlasWIG///6bM6mkPLZs2YKvvvoKP/zwA0aMGKG1zJvaY+XKlejfvz9GjhwJmUyGPXv24L333sPRo0cREhKiLjd//nzMmzcPnTt3xoIFCyCRSHDt2jX89ddf6NWrF4CiA8CECRPQvHlzzJ49G1ZWVoiIiMCJEyfU8anavkOHDli8eDGSkpKwcuVKXLp0SeMztbOzw4oVKwAAz58/x8qVK9G3b18kJCRo/eyBouHoM2fOwN/fHx4eHlrLvP/++5gyZQqOHj2Kzz///M0N/Q97e3usX78eU6dOxaBBgzB48GAAQKtWrQAAd+7cgb+/P8RiMaZMmQJ3d3c8fvwYf/zxBxYtWgQAuH//Pvz9/WFhYYGwsDCIxWJs3LgRQUFB+N///gdfX1/OOmfMmAEnJyfMnz8fV69exU8//QQrKytcvnwZDRo0wLfffotjx45h2bJlaNGiBcaMGaN+79vu65Vp/9DQUPTo0UP979GjR3PaStWOALBjxw6MHTsWvXv3xnfffYe8vDysX78eXbp0QUREhPrH0ZvadfDgwfD09FTX/8knn6Bp06aYMmWKelnTpk0BVP3+N2/ePMyfPx89evTA1KlTERMTg/Xr1+PGjRtvbOPPPvuszPYvydvbG19++SUYY3j8+DGWL1+Ovn37vtUci7S0NABFnQ8fHx8sWbIEKSkpWLVqFS5evIiIiAjY2dkBAMLDwxEcHIyGDRti3rx5yM/Px+rVq+Hn54fbt29rnL8eOnQo3N3dsXjxYly9ehWrVq1Ceno6tm/fXmo8kyZNwrlz53D69Gk0a9ZMvbwyuUArVgFbtmxhAFh4eDhLSUlhCQkJbM+ePczW1pYZGxuz58+fM8YYk0qlTKFQcN4bFxfHDA0N2YIFC9TLNm/ezACw5cuXa6xLqVSq3weALVu2TKNM8+bNWWBgoPrfZ8+eZQBYvXr1WFZWlnr5vn37GAC2cuVKdd2NGzdmvXv3Vq+HMcby8vKYh4cH69mzp8a6OnfuzFq0aKH+d0pKCgPA5s6dq14WHx/PRCIRW7RoEee9d+/eZQYGBhrLY2NjGQC2bds29bK5c+ey4h/LhQsXGAC2a9cuzntPnDihsdzNzY2FhIRoxD5t2jRW8qMuGXtYWBhzcHBgPj4+nDbdsWMHEwqF7MKFC5z3b9iwgQFgly5d0lhfcYGBger6/vzzT2ZgYMA+/fRTrWXL0x6MFX1OxclkMtaiRQvWrVs3Tl1CoZANGjRIY19UfeYZGRnM3Nyc+fr6svz8fK1lZDIZc3BwYC1atOCUOXr0KAPAvv76a/WysWPHMjc3N049P/30EwPArl+/rnWbGWMsMjKSAWAzZ84stQxjjLVq1YrZ2Nio/128bYsrGYe2fVUlICCAmZubs6dPn3KWF/9eDBw4kEkkEvb48WP1shcvXjBzc3MWEBCgXqY6PpT8XnXq1IkJBAL2wQcfqJcVFhay+vXrc+KvyL6uTWXbv6TS2io7O5tZWVmxyZMnc5a/evWKWVpacpaXp12Lc3NzY2PHjtVYXtX7X3JyMpNIJKxXr16c78WaNWsYALZ582b1spL717FjxxgA1qdPH43vpDba9s8vvviCAWDJycnqZQDYtGnTSq1HtV/FxcVx/t2sWTPOsUB1/C9+fGnTpg1zcHBgaWlp6mVRUVFMKBSyMWPGqJepjjP9+/fnrPvDDz9kAFhUVBQnXtX+MXv2bCYSidjhw4c576toLihLpYa7e/ToAXt7e7i6umLYsGEwMzPDoUOHUK9ePQCAoaEhhMKiqhUKBdLS0mBmZoYmTZrg9u3b6noOHjwIOzs7zJgxQ2Md5RlOKc2YMWNgbm6u/veQIUPg7OyMY8eOASi6jCA2NhYjRoxAWloaUlNTkZqaitzcXHTv3h3nz5+HUqnk1CmVSmFkZFTmen/77TcolUoMHTpUXWdqaiqcnJzQuHFjnD17llNeJpMBKGqv0uzfvx+Wlpbo2bMnp04fHx+YmZlp1CmXyznlUlNTNYZrSkpMTMTq1asxZ84cmJmZaay/adOm8Pb25tSpOsVRcv2luX79OoYOHYp3330Xy5Yt01qmPO0BQD0aAgDp6enIzMyEv78/Z986fPgwlEolvv76a/W+qKLat06fPo3s7Gx8/vnnGp+tqszNmzeRnJyMDz/8kFMmJCQE3t7eGpejKJVKdRtFRkZi+/btcHZ2VveKtMnOzgYAzj6rjbm5ObKyssosUxEpKSk4f/48JkyYgAYNGnBeU22/QqHAqVOnMHDgQDRs2FD9urOzM0aMGIGLFy9qxDRx4kTO99fX1xeMMUycOFG9TCQSoX379njy5Il6WUX3dW0q0/7ldfr0aWRkZGD48OGc+EQiEXx9fdXxladdy6uq97/w8HDIZDJ8/PHHnO/F5MmTYWFhUerlVYwxzJ49G++++67GyElZVMejlJQUXLlyBYcOHUKrVq3UPV0VqVSK1NRUpKWlaRx7SzNt2jTOsSAoKAg+Pj7qbXj58iUiIyMxbtw42NjYqMu1atUKPXv2VOeDknUWp8pN2squWbMGixcvxqpVqzBgwADOaxXNBWWp1HD32rVr4eXlBQMDAzg6OqJJkyacD1ypVGLlypVYt24d4uLioFAo1K+phsSBomHyJk2awMCgSkbd1Ro3bsz5t0AggKenp/qchuqC97Fjx5ZaR2ZmJmeCTmpqqka9JcXGxoIxVmq5ksNIqnNAJRNjyTozMzPh4OCg9fXk5GTOv0+dOqUemiuvuXPnwsXFBaGhoRrndmNjYxEdHV1qnSXXr01iYiJCQkKQm5uLtLS0Ug9U5WkPADh69CgWLlyIyMhIznnx4vU+fvwYQqGQM/xUkuo0TYsWLUot8/TpUwBAkyZNNF7z9vbGxYsXOcsSEhI4beXs7IyDBw+WuU2q5KxK1qXJzs5+YyKvCFWCLGv7U1JSkJeXp3X7mzZtCqVSiYSEBM4EnpKJydLSEgDg6uqqsbz4ueaK7uvaVKb9y0t13FD9QC3JwsICQPnatbyqev8rrT6JRIKGDRuqXy9p165duH//Pvbt26cxX6Msly9f5sTTuHFjHD58WOMYsGnTJmzatEkdi6+vL5YvX66eoFyc6r3e3t4arzVt2lR9DCur7Zo2bYqTJ08iNzcXpqamnPiKa9SoEYRCIWdOAlA0L+HmzZsAiuZglVTRXFCWSmXHjh07am08lW+//RZz5szBhAkT8M0338DGxgZCoRAff/xxuX8lVSdVDMuWLUObNm20lin+pZbJZHj58iV69uz5xnoFAgGOHz8OkUhUZp0A8OrVKwCAk5NTmXU6ODhg165dWl8vmTx9fX2xcOFCzrI1a9bgyJEjWt8fHR2NrVu3YufOnVp3HKVSiZYtW2L58uVa31/ywKvNo0eP0K5dO6xYsQKjR4/Gtm3btP5AKk97XLhwAf3790dAQADWrVsHZ2dniMVibNmypUIHj+ri6OiInTt3Aij6obd582b06dMHFy9eRMuWLbW+x9PTEwYGBrhz506p9RYUFCAmJobzvRMIBBoTrwBwfhTzQdu+X9ry4vFXdF/XpjLtX16q48aOHTu07qNV3dmojOrYfplMhjlz5mDixInw8vKq0HtbtWqFH374AQDU542DgoJw+/ZtThsOGDAA06dPB2MMcXFxWLBgAfr166f1DmLFe8/VrbQOxfXr1zF58mSYmppi4cKFeO+99zg/BiqaC8pSLXvVgQMH0LVrV/UvI5WMjAzOMEejRo1w7do1yOXyKpn8pFLyg2WM4dGjR+rJMqoJaRYWFpwJI6WJioqCXC4v84eJql7GGDw8PMq1Mz948AACgUDrL73idYaHh8PPz69cO6ednZ3GNpU1uWv27Nlo06YN3n///VLXHxUVhe7du1f6FITqVIOjoyOOHDmCTz/9FH379tU46JanPQ4ePAgjIyOcPHmSMyy+ZcsWjbiVSiUePHhQ6g8x1X5w7949ziSe4tzc3AAAMTExGj2omJgY9esqRkZGnPbv378/bGxssGbNGs7M7OJMTU3RtWtX/PXXX3j69KlGnQCwb98+FBQUcGbvW1tbc4aLVUr2hkr73FTD1yVn2xZnb28PExMTrXdxevjwIYRCYbl+qJVHRfd1bSrT/hWJDwAcHBzKPG6Up13Lq6r3v+L1FT99IZPJEBcXp3W71q1bh+TkZK1XsryJtbU1p86goCC4uLhgy5YtnIm/9evX55QzMzPDyJEjERERoVGnanKltjZ5+PChejJY8W0t6eHDh7Czs+P0ooGi3FF88uajR4+gVCo1Jpj17NkT69evh1QqxeHDhzFlyhT11UVAxXNBWarltqAikUjjF/7+/fs1Lhl49913kZqaijVr1mjUoa2HUF7bt2/nDB0eOHAAL1++RHBwMADAx8cHjRo1wvfff4+cnByN96ekpGjELhKJtF7eVNzgwYMhEokwf/58jfgZY+pZiUDRtP2DBw+iY8eOZf6qGjp0KBQKBb755huN1woLCzUum6iIK1eu4MiRI1iyZEmpB/KhQ4ciMTERP//8s8Zr+fn5yM3NfeN6vLy84OjoCKDohh1KpRIzZ87klClve4hEIggEAk5vMT4+XuOHyMCBAyEUCrFgwQKN0RvVZ9OrVy+Ym5tj8eLFGuftVWXat28PBwcHbNiwgTO0fvz4cURHR3Nmk2sjk8lQWFj4xsvVvvrqKzDGMG7cOOTn53Nei4uLQ1hYGJydnREaGqpe3qhRIzx8+JCzv0ZFRWlcRqi6pKvkvmJvb4+AgABs3rxZY7atavtFIhF69eqFI0eOcIb8kpKSsHv3bnTp0kU9zPu2qmNfL2/7l0fv3r1hYWGBb7/9FnK5XON11edQnnYtr6re/3r06AGJRIJVq1ZxYtm0aRMyMzM16svOzsaiRYvwySeflDnCVV6qfftNn4fqO6utF9q2bVs4OTlptMmFCxdw8+ZN9XHa2dkZbdq0wbZt2zj7zr1793Dq1CmNq4WAolO5xa1evRoA1LlDpXPnzhCJRDA1NcWGDRtw/vx5zjGyIrngTaqlJ92vXz8sWLAA48ePR+fOnXH37l3s2rWL88sNKJrgtX37dsyaNQvXr1+Hv78/cnNzER4ejg8//FDjZHx52djYoEuXLhg/fjySkpLw448/wtPTU32nHKFQiF9++QXBwcFo3rw5xo8fj3r16iExMRFnz56FhYUF/vjjD+Tm5mLt2rVYtWoVvLy8ONctqpL7nTt3cOXKFXTq1AmNGjXCwoULMXv2bMTHx2PgwIEwNzdHXFwcDh06hClTpuA///kPwsPDMWfOHNy5cwd//PFHmdsSGBiI0NBQLF68GJGRkejVqxfEYjFiY2Oxf/9+rFy5EkOGDKlUO506dQo9e/Yss1cwevRo7Nu3Dx988AHOnj0LPz8/KBQKPHz4EPv27cPJkyffOMJQnJOTE5YtW4ZJkyZh1KhR6Nu3b4XaIyQkBMuXL0efPn0wYsQIJCcnY+3atfD09OQMF3t6euLLL7/EN998A39/fwwePBiGhoa4ceMGXFxcsHjxYlhYWGDFihWYNGkSOnTogBEjRsDa2hpRUVHIy8vDtm3bIBaL8d1332H8+PEIDAzE8OHD1ZfAuLu745NPPuHEl5ubyxlu3LFjB6RSKQYNGlTmdgUEBOD777/HrFmz0KpVK4wbNw7Ozs54+PAhfv75ZyiVShw7dowzT2LChAlYvnw5evfujYkTJyI5OVl9g4fik7mMjY3RrFkz7N27F15eXrCxsUGLFi3QokULrFq1Cl26dEG7du0wZcoUeHh4ID4+Hn/++SciIyMBAAsXLsTp06fRpUsXfPjhhzAwMMDGjRtRUFCApUuXlutzL4+q2Ncr2/7lYWFhgfXr12P06NFo164dhg0bBnt7ezx79gx//vkn/Pz81B2O8rRreVT1/mdvb4/Zs2dj/vz56NOnD/r374+YmBisW7cOHTp0wKhRozj13b59G3Z2dggLC6tUmyUlJanjSU1NxcaNG2FgYKDR4Xn27BlOnDihHu5etGgR3Nzc0LZtW42RUQMDAyxduhRjxoyBv78/Ro4cqR5Kr1+/PucysWXLliE4OBidOnXCxIkT1ZdgWVpaah0ZiIuLQ//+/dGnTx9cuXIFO3fuxIgRI9C6detSt7F3794YNWoUwsLC8M4778DZ2bncuaBcyj0PnP079f3GjRtllpNKpezTTz9lzs7OzNjYmPn5+bErV65onZKfl5fHvvzyS+bh4cHEYjFzcnJiQ4YMUV/uUZlLsH799Vc2e/Zs5uDgwIyNjVlISIjGpRCMMRYREcEGDx7MbG1tmaGhIXNzc2NDhw5lZ86c4az7TX8lL504ePAg69KlCzM1NWWmpqbM29ubTZs2jcXExDDGGJsxYwYLCAhgJ06c0IhJ2yVHjBVdSuHj48OMjY2Zubk5a9myJQsLC2MvXrxQl6noJVgCgYDdunWLs1zbZySTydh3333HmjdvzgwNDZm1tTXz8fFh8+fPZ5mZmRrre1N9jDHWrVs31qBBA5adnV3h9ti0aRNr3LgxMzQ0ZN7e3mzLli2lttvmzZtZ27Zt1XEHBgay06dPc8r8/vvvrHPnzszY2JhZWFiwjh07sl9//ZVTZu/evep6bGxs2MiRI9WXHKqMHTuWs1+YmZmxdu3asR07dpTZRsWdP3+eDRgwgNnZ2TGxWMwaNGjAJk+ezOLj47WW37lzJ2vYsCGTSCSsTZs27OTJk1ovxbl8+TLz8fFhEolE4xKje/fusUGDBjErKytmZGTEmjRpwubMmcN5/+3bt1nv3r2ZmZkZMzExYV27dmWXL1/mlCnt+KD6bFJSUjTay9TUVGObyrOva1MV7c9Y6ZdgqZw9e5b17t2bWVpaMiMjI9aoUSM2btw4dvPmTU658rSrSmmXYKlU9f63Zs0a5u3tzcRiMXN0dGRTp05l6enpnDKBgYEMAFuxYgVneWnftZJU71f9WVlZMT8/P3bs2DFOueJlBAIBc3JyYoMHD2bR0dGMMc1LsFT27dvHaZPhw4drPc6Hh4czPz8/9ff7nXfeYQ8ePNC6TQ8ePGBDhgxh5ubmzNramk2fPl3j8kxt+0dqaiqzt7dngwYN4ix/Uy4oD8E/K9UL586dQ9euXbF///5K9y6Li4+Ph4eHB+Li4kq9afu8efMQHx+PrVu3vvX6CCGE1DzVDV5SUlI0Lg/jGz2qkhBCCNFR/F8zoMNUMwzLmsjUqlUr9W1OCSGEkKpESboMdnZ26kkPpSl+f19CCCGkKunVOWlCCCFEn9A5aUIIIURHUZImhBBCdBQlaUIIIURHUZImhBBCdBQlaUIIIURHUZImhBBCdBQlaUIIIURHUZImhBBCdBQlaUIIIURHUZImhBBCdBQlaUIIIURHUZImhBBCdBQlaUIIIURHUZImhBBCdBQlaUIIIURHUZImhBBCdBQlaUIIIURHUZImhBBCdJQB3wEQQiomPVeGhPQ8JLzOR0J6HjLz5ZAXKiFXKGEnysUM7AFEkn//jK0Aaw/ApiFg7Q5ITPjeBEJIOQkYY4zvIAghmlKyC3D5cSqiEjLx7HUenqfn4Xl6PnIKCkt9j49FNg7KQsuoVQCYO/2btG3cATsvwN0fMLGp8m0ghLwd6kkToiOypHJce/Ialx6l4vLjVPydlFMNa2FA9suiv2eX/10sEAIu7YDGPQHPHkX/L6SzYYTwjXrShPDoeXoeDtx6jnMxKbibmAmF8u2+jm/uSZeTsQ3QqFtRwvbsAZjZv32dhJAKoyRNSA1TKBnORCdh9/VnOP93Ct4yL3NUWZIuTiACvEOA//sQcOtUtXUTQspEw92E1JAXGfnYcyMB+24k4FWWlO9wyo8pgOjfi/5c2gK+U4EWgwGRmO/ICNF71JMmpJrdfZ6JlWf+xtmYlLcezn6TaulJa2PmBHSYBLSfAJjaVv/6CKmjKEkTUk2epOTg+1MxOH7vFWrqW1ZjSVrFwAhoOwoI+oKSNSHVgIa7CaliGXky/HDqb/x6/RkKq7nnzLtCKXDjF+Du/qJE3WESIKLDCiFVhXrShFQRpZJh1/VnWH4qBul5cl5iqPGedEn2TYGQHwB3P/5iIESP0E9eQqpAXGouZu6JwJ3nmXyHwq+UaGBrCOAzDui5ADCy4DsiQmo1ulsBIW/pSGQi+q26QAlajQG3tgBrfYGYE3wHQ0itRkmakErKlykQdiAKM/dEIlem4Dsc3ZP9Avj1feCvhaixmXOE6Bka7iakEv5Oysa0XbcRm1wdt+7UM+eXAcnRwOCfAIkp39EQUqtQT5qQCtp74xn6r7lICboiHh4FNvUC0p/yHQkhtQolaUIqYNnJh/js4F1I5Uq+Q6l9ku4BP3cD4i/xHQkhtQYlaULKacEfD7D27GO+w6jd8lKB7QOAW1v5joSQWoGSNCFvwBjDF4fuYvOlOL5D0Q9KOfDHTODcEr4jIUTnUZImpAwKJcOn+6Ow+9ozvkPRP+cWA9c28h0FITqNkjQhpZArlPjo1wj8djuR71D01/HPgDv7+Y6CEJ1FSZoQLRhjmLknAn/efcl3KHqOAYenArGn+Q6EEJ1ESZoQLVaeicWxu6/4DqNuUMqBfWOAZ9f4joQQnUNJmpASTj9IwsozsXyHUbfI84DdQ4Gk+3xHQohOoSRNSDGPkrPxyd5IuoslH6QZwI7BQHYS35EQojMoSRPyjyypHJO330JOQSHfodRdOa+A36fzHQUhOoOSNCEoehb0R79GIC41l+9QSOwp4MYmvqMgRCdQkiYERRPFzsWk8B0GUTk1B0ir2N3dzp8/j3feeQcuLi4QCAQ4fPhw9cRGSA2iJE3qvOiXWVh37hHfYZDi5LnAoVBAWf5HgObm5qJ169ZYu3ZtNQZGSM2iR1WSOk2hZPj84B3IFTRTTOc8vwFc+AEIDCtX8eDgYAQHB1dzUITULOpJkzpty6U4RD3P5DsMUpr/fQck3uY7CkJ4Q0ma1FnJWVL8GE7XQ+s0ZWHRHckUNOOe1E2UpEmdteT4Q7rcqjZIeQhE7uQ7CkJ4QUma1Em3nqbjUCQ9OKPWOLcEkOfzHQUhNY6SNKmTvjvxkO4qVptkvwSuruc7CkJqHCVpUudEJWTgetxrvsMgFXVpJVCQXerLOTk5iIyMRGRkJAAgLi4OkZGRePaMngVOai9K0qTO+fnCE75DIJUhzSjzTmQ3b95E27Zt0bZtWwDArFmz0LZtW3z99dc1FCAhVY+ukyZ1yvP0PBy/R4+grLWurAV8PwDERhovBQUFgdE5DKJnqCdN6pTNF+OhUNKBvNbKTQYidvAdBSE1hpI0qTOypHLsu5nAdxjkbdHDN0gdQkma1Bm7rz2j66L1QUo0kPSA7ygIqRF0TprUGTuuPOU7BJ20/oYM62/KEJ+hBAA0dxDh6wAJghuLAQBBW3Pxv6fcB12E+oixoZ9xqXX+Fi3Hhpsy3HqpxOt8hohQU7RxEnHKzDopxdZIGUwlAizpboSRrcTq1/bfl2P7HTn+GG6ifQX3DgKOzSqzuYTUKpSkSZ1wLzETiRl0Mwxt6lsIsKSHIRrbCMEAbIuUY8CefESECtHcoSixTm4nxoKuhur3mIgFZdaZK2Po0sAAQ5sLMPkPqcbrf8TIsfuuHKdGmyI2TYkJv+ejt6cIdiZCZEoZvvyrAOFjSknQQFGS7j6nUttLSG1CSZrUCeHRSXyHoLPeaSLm/HtRdxHW35Th6nOFOkmbiAVwMiv/2bHRrSUAoO6dlxSdqkSQuwjtXYr+Pj4pRVw6g50JEHZaiqntxWhgWcb60uOAxFtAPZ9yx0RIbUTnpEmdQEm6fBRKhj335MiVA51c/x2e3nVXDrul2WixLgezw6XIk7/dDPnWjiLcfKFAej7DrRcK5MsZPG2EuPisELdfKfCRr+TNldz77a1iIKQ2oJ400XuvMqW4l5jFdxg67W6SAp025UJaCJhJgEPvG6OZfVGSHtFSDDdLIVzMBbiTpMRn4VLEpCnx2/tlDEe/QW9PA4xqJUaHn3NgLBZg20BjmEqAqX9KsXWAMdbflGP1dRnsTAT4qZ+RukfPcf8Q0GshICh76J2Q2oySNNF7p6kX/UZN7ISI/MAMmVKGAw/kGHtYiv+NE6KZvQhTfP7t1bZ0FMHZXIDu2/Pw+LUSjWwqPxg3L8gI84L+vSnJ/HMF6OFhALEIWHi+AHenmuLo34UYczgft6aYaVaQlQg8uwK4da50DIToOhruJnov/AEl6TeRiATwtBHCx0WExT2M0NpRiJVXZVrL+tYr6tU+eq39fHNlPExVYOddOb7pZohz8YUIcBPB3lSIoc3FuP1SieyCUobXH5+tshgI0UWUpIley5MV4sqTNL7DqHWUDChQaH8t8lXRC87mVTPMzBhD6FEplvcyhJlEAIUSkP+T/1X/VZR2CvxlVJXEQIiuouFuotcevMiCrLDqenz6aHa4FMGNDdDAUojsAobdd+U4F6/AyVGGePxaid135ejb2AC2JgLcSVLgk5NSBLiJ0Mrx3/PE3mtysLi7IQY1LZop/jqf4VmmEi+yi9o+JrXov05mmrPEf7kth72JQD3L3K+BAeb9rwBXnxfieGwhmtkLYWVUyg8CStJEz1GSJnotJqn0RxuSIsm5DGMO5eNlDoOloQCtHIU4OcoEPRsZICFTifC4Qvx4TYZcGYOrpRDvNhXjqwBDTh0xaUpkFhuS/j1GjvFH/r0+etjBomvU5wZKOOehk3KUWHShAJcnmqqXdawnwqedDBGyOx8OpkWTykqV8wrIfgWYO71tMxCikwSMHhtD9Ni83+9j6+V4vsOoMT4W2TgoC+U7jJo1Yh/g1ZvvKAipFnROmui1mFfUk9Z7NORN9BglaaLXYpMpSes9StJEj1GSJnorLacAqTnaLyMieoSSNNFjlKSJ3qJJY3VEZgIgy+U7CkKqBSVporcep9CBu86QZvIdASHVgpI00VvpuTTUXWcU0KgJ0U+UpIneysqX8x0CqSlSeoAK0U+UpIneypJSkq4zCihJE/1ESZrorZyCQr5DIDWFkjTRU5Skid6SFdLN9OoMOidN9BQlaaK3CpX0YI06g85JEz1FSZrorcJSn2+ov25nm+GM63QwoZjvUGqWLIfvCAipFpSkid5iqHtJmjEBJsZ2xn8tlqLQogHf4dQcUR37UULqDErSRG9ZmUj4DoE3B145okvmAjyv35fvUGqGoQXfERBSLShJE71lb2b45kJ67FWBBF0ejcJ+lzAwsQnf4VQvI0u+IyCkWlCSJnrL1rTu9qSL+++TNpgoWQapjTffoVQf6kkTPUVJmugt2zreky7urzRrdEj+AjGuQ/kOpXqY2vEdASHVgpI00Vu2ZtSTLi670AC9Ywdig+M8KI2s+A6napk78x0BIdWCkjTRW3bUk9ZqyVMvDGFLkePgw3coVUMgBMwc+Y6CkGpBSZroLTvqSZfqdqYZfJ5/ghuuE8AEtfwwYOoAiAz4joKQalHLv52ElM7RwggGQgHfYeisAqUQ78X2wCLbxVCY1uKeqI0H3xEQUm0oSRO9ZSQWwdvZnO8wdN4vz13RK/9bpDkH8h1K5dRvz3cEhFQbGiMieq2tqzXuJZZ+X+fC7FRknNuK/Ce3wAoLYGDlDNu+H8PQubFG2bSTa5ATeQLW3SbDosOAUutUFuQh48JO5MVegTIvExKHhrDuMQWGzl7qMpnXfkPW9YMAAEvfd2HRcbD6tYIXMXh9ah2cxiyHQCiqzGZX2OM8Y7SPn4KfGrVCjxcbIFDWosd81u/IdwSEVBvqSRO91raBVamvKaQ5eLUzDBAawOG9eXCeuA7W3SZCaGSmUTbv78soeBEDkZnNG9eZdmI1pPGRsOv3KZwnrIGRR1sk7fkKhdmpAABZchwyL+6CXf8w2L3zX2Rc2AlZSjwAgCkVSDu5Fja9p9VYglZhTIDJjzrhU/NlkFu61+i634orJWmivyhJE73WtoF1qa9lXT0AAws72IV8DEOXJhBbOcHYox3E1tzLeQqzU/H69EbY9fsPICx78EkpL0BezCVYdR0PI9cWEFu7wKrLSIitnZEdcRwAIE97DrG9O4zdWsPYvQ3E9u6Qpz0viunaQRi5Nuf0umvab0kO8MuYj+f1Q3iLodwsGwDmTnxHQUi1oSRN9JqHnSmsTbQ/fCH/0TVInBoj5fBiJKweiRdbPkJ25AlOGcaUSD26HBa+gyGxd3vzCpUKgCkhKPHAB4GBIQqe3wcASOzdUZieiMKsZBRmJqPwdSIkdm6Qp79Ezt1wWPmPrtzGVqHkAjG6PBqJvS6fg4lN+Q6ndNSLJnqOkjTRe61drbQul2e8QnbEMRhYu8Bx6AKYt+2L9DM/IefuGXWZrKsHIBCKYO7Tv1zrEhqawNDFG5mX96AwOw1MqUDO/bMoePEQitx0AIDYzhVWAWOQtHcOkvbNgVXgWIjtXPH65BpYB41HftxtvNj0IV5s+QjShHtvvf1v47MnrTBevBRS22a8xlEqStJEz9HEMaL32jWwxrmYFM0XGIOhkyesA8cCACSOjSBPfYrsyGMwa9kdBa8eIevW73AeuxICQfkv5bLt9ynSjq9E4rqxgEAIiVMjmDYNQMGrR+oy5m37wrztv0+oyrl7BgKJMQzreSPx5w/gPGY5FNlpSP19KeqFboLAgL9HMZ57bQ0fg9k46HEU3gl7eYtDq/od+I6AkGpFSZrovW7eDlh++m+N5SIza4jtuM9cFtu6Ii/mEgCgIOE+lLmZSFw//t8CTIn0s5uQdfMI6k/drHV9YmtnOI1YAqVMCqUsDwZmNkg58h3EVtrPnSryMpF5aTccR3yHghd/Q2zjArFNPYht6oEpCiFPT4TE3r1yG19FcgtF6BM7AGFuzfBB5o8QStN5jQcAIDEHnFryHQUh1YqSNNF7LepZwtPBDI+SczjLDes1g/z1c84y+etEGFg4AABMW3SFkXtrzuvJ+76GafNuMGvZ443rFUqMIJQYQSHNQX7cbVgHjddaLv2vX2DeYSAMLOwge/U3mELx74tKBaBUlmcza8TSp41xyuI77HD4CebJN/kNpvkAQMTfCAMhNYHOSZM6YWAbF41lFh0GoOBFDDKv7IM8/QVyH5xDTtQJmLUrmtUsMraAxN6d8wehAUSm1hDb1lfXk7TnC2Td+kP97/wnt5D/5BbkGa+QHxeBpF9nQ2xTX2tiz4+LgPx1Isz/WafEyQuFr58j//HNoklsQhEMbOpVcWu8ncgsM7R7/gmuuU7i95aibUbyt25Cagj1pEmdMKBNPXx/ijvkbejsBftBXyLjf9uQcelXGFg6wrrbZJg171qhuuXpr2CY/+8NU5QFecg4vw2F2akQGZnDpElnWAWMgaDE/aWV8gK8Dt8A+/6fQfBPsjOwsIN1j1CkHv8RApEYtiGfQCjWvQeFyJUCvB/bDRPqNcaX0hUQ5b6q2QCsPYAGnWp2nYTwQMAYY3wHQUhNeHf9Zdx6qgPnUvVMQxMp9jlth92LczW30qAvgKDPam59hPCEhrtJnTFAy5A3eXtP8ozQIW4yTtafCSaqiSePCYDWw2pgPYTwj5I0qTNCWjrTU7GqCWMChD7yxcdmSyG3rOanUrn5AdbluLEMIXqAkjSpM2zNDNGjaS1+JGMtcCTJAX4Z85BQv1/1raTNiOqrmxAdQ0ma6I21a9fC3d0dRkZG8PX1xfXr1zXKTOvqyUNkdUtygRj+j0bgV5fZVX9LUSMroFnpTyAjRN9QkiZ6Ye/evZg1axbmzp2L27dvo3Xr1ujduzeSk5M55VrWt0SAlz1PUdYts5+0xFjxMuTbNq+6Sv1nAYaaTykjRF/R7G6iF3x9fdGhQwesWbMGAKBUKuHq6ooZM2bg888/55S9Ef8a7224wkeYdZKpgQL7PY6hWcKvb1eRRX1gxi1AbFQ1gRFSC1BPmtR6MpkMt27dQo8e/94sRCgUokePHrhyRTMZd3C3gX9ju5oMsU7LLRShb+w7WO3wDZTGb34ed6m6zqYETeocStKk1ktNTYVCoYCjI3dSmKOjI1690n6Tjc/6eKMCz8wgVeCHZ40wULEEWY6VeHKVQzOgNU0YI3UPJWlSJ7WoZ4mQls58h1Hn3Mkyg0/CTFx1nVyxW4p2/xoQ0uGK1D2015Naz87ODiKRCElJSZzlSUlJcHLS/uQpoKg3bSIRVXd4pAS5UoBhsV0x33oJFGbl+KHUoDPQJLj6AyNEB1GSJrWeRCKBj48Pzpw5o16mVCpx5swZdOpU+v2dXW1M8Hmwd02ESLTY+qI+uucuQopLt7IL9pxfMwERooMoSRO9MGvWLPz888/Ytm0boqOjMXXqVOTm5mL8eO2Ph1QZ/X9u6OJJk8j4Ep9vhA5PJuF4/Y/BRFoeJNJ+AuBaiXPYhOgJugSL6I01a9Zg2bJlePXqFdq0aYNVq1bB19f3je97kZGP3ivOI7ugsAaiJKV5xyEFPwhXQpLxpGiBrScQegGQmPAbGCE8oiRNCIB9NxMQduAO32HUefYSOQ40OAi3F8eACaeA+j58h0QIryhJE/KPSdtuIDw6+c0FSbXb1d8cfp0D+A6DEN7ROWlC/vHt4JawMa2JRy2SsgR62aNzJ3++wyBEJ1CSJuQfDuZG+Gm0DwwN6GvBl3pWxvjx/TYQ0J1mCAFASZoQjvbuNlg5rA3osdM1z1gswtqR7WBNoxmEqFGSJqSEPi2cMadfM77DqFMkBkJsHO2DNq5WfIdCiE6hJE2IFuP9PDDZ34PvMOoEA6EAq4e3pUeIEqIFJWlCSvFF36bo14ru712dhALg+/dao3fz0m/fSkhdRkmakFIIBAL8MLQ1Ojey5TsUvbVoUEsMbFuP7zAI0VmUpAkpg6GBCFvGd6AedTX4KqQphndswHcYhOg0upkJIeXAGMOS4w+x8fwTvkOp9URCAb4KaYrxfnTOn5A3oSRNSAXsuBKPeX88gEJJX5vKsDIRY+2IdvCjh5oQUi6UpAmpoPAHSZjxawTy5Qq+Q6lVmjia4+cx7dHAlh6YQUh5UZImpBKiEjIwcdtNpOYU8B1KrdCrmSNWvN8GpoYGfIdCSK1CSZqQSkrJLkDYgSicjUnhOxSdJRAAM7p64pOeXnSrT0IqgZI0IW9px5V4LDoWDalcyXcoOsXVxhjfDGiBoCYOfIdCSK1FSZqQKvAkJQef/3YX1+Ne8x0K78QiASb5N8TM7o1hJBbxHQ4htRolaUKqCGMMu68/w5LjD5EtLeQ7HF60d7PGokEt0cTJnO9QCNELlKQJqWJJWVKsOhOL/TefQ6aoG0PglsZizA72xvsdXOncMyFViJI0IdXkRUY+1p59pNfJ2kgsxLAODTC9myfszAz5DocQvUNJmpBqpo/J2szQAKP+zw2T/D0oORNSjShJE1JDXmTkY925Rzh0OxG5stp5IxRXG2OM+T93DO3gCktjMd/hEKL3KEkTUsPyZQqcjk7C75EvcP7vFJ3vXRsaCOHf2A5D27uiR1NHCIV0zpmQmkJJmhAeZebJcezeS/we+QLX4tKgK7cEtzYRo5u3I3o2c0SAlx1MJHSnMEL4QEmaEB2RlCXF6QdJiEzIQFRCBh6n5NRo0nazNUF3b0f0au6IDu42EFGPmRDeUZImREdlS+W4+zwTkc8zEPksA1HPM5CU9fb3Cjc3MoC3kzm8HM3h7WSOJk4WaOJoDksTOsdMiK6hJE1ILZJbUIikLCmSsgqQlCVFep4MWfmFyJbKkS0thFAogKlEBBNDg6L/SkQwkRjA1FAEM0MxGtqbwsXKmO/NIISUEyVpQgghREcJ+Q6AEEIIIdpRkiaEEEJ0FCVpQgghREdRkiaEEEJ0FCVpQgghREdRkiaEEEJ0FCVpQgghREdRkiaEEEJ0FCVpQgghREdRkiaEEEJ0FCVpQgghREdRkiaEEEJ0FCVpQgghREdRkiaEEEJ0FCVpQgghREdRkiaEEEJ0FCVpQgghREdRkiaEEEJ0FCVpQgghREdRkiaEEEJ0FCVpQgghREdRkiaEEEJ0FCVpQgghREdRkiaEEEJ01P8D70SlxuBsGM0AAAAASUVORK5CYII=",
|
||
"text/plain": [
|
||
"<Figure size 200x200 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Вывод распределения количества наблюдений по меткам (классам)\n",
|
||
"print(df.Outcome.value_counts())\n",
|
||
"print()\n",
|
||
"\n",
|
||
"data = df.copy()\n",
|
||
"\n",
|
||
"df_train, df_val, df_test = split_stratified_into_train_val_test(\n",
|
||
" data, stratify_colname=\"Outcome\", frac_train=0.60, frac_val=0.20, frac_test=0.20\n",
|
||
")\n",
|
||
"\n",
|
||
"print(\"Обучающая выборка: \", df_train.shape)\n",
|
||
"print(df_train.Outcome.value_counts())\n",
|
||
"counts = df_train['Outcome'].value_counts()\n",
|
||
"plt.figure(figsize=(2, 2))# Установка размера графика\n",
|
||
"plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)# Построение круговой диаграммы\n",
|
||
"plt.title('Распределение классов Outcome в обучающей выборке')# Добавление заголовка\n",
|
||
"plt.show()# Отображение графика\n",
|
||
"\n",
|
||
"print(\"Контрольная выборка: \", df_val.shape)\n",
|
||
"print(df_val.Outcome.value_counts())\n",
|
||
"counts = df_val['Outcome'].value_counts()\n",
|
||
"plt.figure(figsize=(2, 2))\n",
|
||
"plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
|
||
"plt.title('Распределение классов Outcome в контрольной выборке')\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"print(\"Тестовая выборка: \", df_test.shape)\n",
|
||
"print(df_test.Outcome.value_counts())\n",
|
||
"counts = df_test['Outcome'].value_counts()\n",
|
||
"plt.figure(figsize=(2, 2))\n",
|
||
"plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
|
||
"plt.title('Распределение классов Outcome в тестовой выборке')\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"#### Сбалансируем распределение:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"1. Балансировка данных оверсемплингом. Это метод, увеличивающий число наблюдений в меньшинственном классе для достижения более равномерного распределения классов."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 353,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обучающая выборка: (460, 9)\n",
|
||
"Outcome\n",
|
||
"0 299\n",
|
||
"1 161\n",
|
||
"Name: count, dtype: int64\n",
|
||
"Обучающая выборка после oversampling: (587, 9)\n",
|
||
"Outcome\n",
|
||
"0 299\n",
|
||
"1 288\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 200x200 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"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>Pregnancies</th>\n",
|
||
" <th>Glucose</th>\n",
|
||
" <th>BloodPressure</th>\n",
|
||
" <th>SkinThickness</th>\n",
|
||
" <th>Insulin</th>\n",
|
||
" <th>BMI</th>\n",
|
||
" <th>DiabetesPedigreeFunction</th>\n",
|
||
" <th>Age</th>\n",
|
||
" <th>Outcome</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>1.000000</td>\n",
|
||
" <td>73.000000</td>\n",
|
||
" <td>50.000000</td>\n",
|
||
" <td>10.000000</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>23.000000</td>\n",
|
||
" <td>0.248000</td>\n",
|
||
" <td>21.000000</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>1.000000</td>\n",
|
||
" <td>84.000000</td>\n",
|
||
" <td>64.000000</td>\n",
|
||
" <td>23.000000</td>\n",
|
||
" <td>115.000000</td>\n",
|
||
" <td>36.900000</td>\n",
|
||
" <td>0.471000</td>\n",
|
||
" <td>28.000000</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>8.000000</td>\n",
|
||
" <td>133.000000</td>\n",
|
||
" <td>72.000000</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>32.900000</td>\n",
|
||
" <td>0.270000</td>\n",
|
||
" <td>39.000000</td>\n",
|
||
" <td>1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>3.000000</td>\n",
|
||
" <td>106.000000</td>\n",
|
||
" <td>72.000000</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>25.800000</td>\n",
|
||
" <td>0.207000</td>\n",
|
||
" <td>27.000000</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>5.000000</td>\n",
|
||
" <td>88.000000</td>\n",
|
||
" <td>78.000000</td>\n",
|
||
" <td>30.000000</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>27.600000</td>\n",
|
||
" <td>0.258000</td>\n",
|
||
" <td>37.000000</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>...</th>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>582</th>\n",
|
||
" <td>2.629250</td>\n",
|
||
" <td>113.651700</td>\n",
|
||
" <td>62.696600</td>\n",
|
||
" <td>36.303400</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>33.632585</td>\n",
|
||
" <td>0.445897</td>\n",
|
||
" <td>27.191151</td>\n",
|
||
" <td>1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>583</th>\n",
|
||
" <td>6.450045</td>\n",
|
||
" <td>106.641614</td>\n",
|
||
" <td>60.366637</td>\n",
|
||
" <td>25.008251</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>27.150780</td>\n",
|
||
" <td>0.318640</td>\n",
|
||
" <td>28.266727</td>\n",
|
||
" <td>1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>584</th>\n",
|
||
" <td>8.753291</td>\n",
|
||
" <td>118.116773</td>\n",
|
||
" <td>35.000000</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>23.728855</td>\n",
|
||
" <td>0.212378</td>\n",
|
||
" <td>34.986837</td>\n",
|
||
" <td>1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>585</th>\n",
|
||
" <td>8.411659</td>\n",
|
||
" <td>160.786384</td>\n",
|
||
" <td>72.609702</td>\n",
|
||
" <td>40.652426</td>\n",
|
||
" <td>278.176681</td>\n",
|
||
" <td>41.212817</td>\n",
|
||
" <td>0.891405</td>\n",
|
||
" <td>32.780595</td>\n",
|
||
" <td>1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>586</th>\n",
|
||
" <td>4.948382</td>\n",
|
||
" <td>130.526964</td>\n",
|
||
" <td>82.314330</td>\n",
|
||
" <td>36.788906</td>\n",
|
||
" <td>110.000000</td>\n",
|
||
" <td>36.689522</td>\n",
|
||
" <td>0.771453</td>\n",
|
||
" <td>38.895223</td>\n",
|
||
" <td>1</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>587 rows × 9 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" Pregnancies Glucose BloodPressure SkinThickness Insulin \\\n",
|
||
"0 1.000000 73.000000 50.000000 10.000000 0.000000 \n",
|
||
"1 1.000000 84.000000 64.000000 23.000000 115.000000 \n",
|
||
"2 8.000000 133.000000 72.000000 0.000000 0.000000 \n",
|
||
"3 3.000000 106.000000 72.000000 0.000000 0.000000 \n",
|
||
"4 5.000000 88.000000 78.000000 30.000000 0.000000 \n",
|
||
".. ... ... ... ... ... \n",
|
||
"582 2.629250 113.651700 62.696600 36.303400 0.000000 \n",
|
||
"583 6.450045 106.641614 60.366637 25.008251 0.000000 \n",
|
||
"584 8.753291 118.116773 35.000000 0.000000 0.000000 \n",
|
||
"585 8.411659 160.786384 72.609702 40.652426 278.176681 \n",
|
||
"586 4.948382 130.526964 82.314330 36.788906 110.000000 \n",
|
||
"\n",
|
||
" BMI DiabetesPedigreeFunction Age Outcome \n",
|
||
"0 23.000000 0.248000 21.000000 0 \n",
|
||
"1 36.900000 0.471000 28.000000 0 \n",
|
||
"2 32.900000 0.270000 39.000000 1 \n",
|
||
"3 25.800000 0.207000 27.000000 0 \n",
|
||
"4 27.600000 0.258000 37.000000 0 \n",
|
||
".. ... ... ... ... \n",
|
||
"582 33.632585 0.445897 27.191151 1 \n",
|
||
"583 27.150780 0.318640 28.266727 1 \n",
|
||
"584 23.728855 0.212378 34.986837 1 \n",
|
||
"585 41.212817 0.891405 32.780595 1 \n",
|
||
"586 36.689522 0.771453 38.895223 1 \n",
|
||
"\n",
|
||
"[587 rows x 9 columns]"
|
||
]
|
||
},
|
||
"execution_count": 353,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"from imblearn.over_sampling import ADASYN\n",
|
||
"\n",
|
||
"ada = ADASYN()\n",
|
||
"\n",
|
||
"print(\"Обучающая выборка: \", df_train.shape)\n",
|
||
"print(df_train.Outcome.value_counts())\n",
|
||
"\n",
|
||
"X_resampled, y_resampled = ada.fit_resample(df_train, df_train[\"Outcome\"])\n",
|
||
"df_train_adasyn = pd.DataFrame(X_resampled)\n",
|
||
"\n",
|
||
"print(\"Обучающая выборка после oversampling: \", df_train_adasyn.shape)\n",
|
||
"print(df_train_adasyn.Outcome.value_counts())\n",
|
||
"\n",
|
||
"counts = df_train_adasyn['Outcome'].value_counts()\n",
|
||
"plt.figure(figsize=(2, 2))\n",
|
||
"plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
|
||
"plt.title('Распределение классов Outcome в тренировочной выборке после ADASYN')\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"df_train_adasyn"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"2. Балансировка данных андерсемплингом. Этот метод помогает сбалансировать выборку, уменьшая количество экземпляров класса большинства, чтобы привести его в соответствие с классом меньшинства."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 354,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обучающая выборка после undersampling: (322, 9)\n",
|
||
"Outcome\n",
|
||
"0 161\n",
|
||
"1 161\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 200x200 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"from imblearn.under_sampling import RandomUnderSampler\n",
|
||
"\n",
|
||
"rus = RandomUnderSampler()# Создание экземпляра RandomUnderSampler\n",
|
||
"\n",
|
||
"# Применение RandomUnderSampler\n",
|
||
"X_resampled, y_resampled = rus.fit_resample(df_train.drop(columns=['Outcome']), df_train['Outcome'])\n",
|
||
"\n",
|
||
"# Создание нового DataFrame\n",
|
||
"df_train_undersampled = pd.DataFrame(X_resampled)\n",
|
||
"df_train_undersampled['Outcome'] = y_resampled # Добавление целевой переменной\n",
|
||
"\n",
|
||
"# Вывод информации о новой выборке\n",
|
||
"print(\"Обучающая выборка после undersampling: \", df_train_undersampled.shape)\n",
|
||
"print(df_train_undersampled['Outcome'].value_counts())\n",
|
||
"\n",
|
||
"# Визуализация распределения классов\n",
|
||
"counts = df_train_undersampled['Outcome'].value_counts()\n",
|
||
"plt.figure(figsize=(2, 2))\n",
|
||
"plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
|
||
"plt.title('Распределение классов Outcome в тренировочной выборке после Undersampling')\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 2. Датасет: Данные по инсультам\n",
|
||
"https://www.kaggle.com/datasets/fedesoriano/stroke-prediction-dataset\n",
|
||
"##### О наборе данных: \n",
|
||
"По данным Всемирной организации здравоохранения (ВОЗ), инсульт является второй по значимости причиной смертности во всем мире, на его долю приходится примерно 11% от общего числа смертей.\n",
|
||
"Этот набор данных используется для прогнозирования вероятности инсульта у пациента на основе входных параметров, таких как пол, возраст, различные заболевания и статус курильщика. Каждая строка в данных содержит соответствующую информацию о пациенте.\n",
|
||
"\n",
|
||
"Атрибуты:\n",
|
||
"1) id: уникальный идентификатор\n",
|
||
"2) gender: \"Male\", \"Female\" или \"Other\"\n",
|
||
"3) age: возраст пациента\n",
|
||
"4) hypertension: 0, если у пациента нет артериальной гипертензии, 1, если у пациента есть артериальная гипертензия\n",
|
||
"5) heart_disease: 0, если у пациента нет сердечных заболеваний, 1, если у пациента есть сердечные заболевания\n",
|
||
"6) ever_married: \"No\" или \"Yes\"\n",
|
||
"7) work_type: \"children\", \"Govt_jov\", \"Never_worked\", \"Private\" or \"Self-employed\"\n",
|
||
"8) Residence_type: \"Rural\" or \"Urban\"\n",
|
||
"9) avg_glucose_level: средний уровень глюкозы в крови\n",
|
||
"10) bmi: индекс массы тела\n",
|
||
"11) smoking_status: \"formerly smoked\", \"never smoked\", \"smokes\" или \"Unknown\"*\n",
|
||
"12) stroke: 1, если у пациента был инсульт, или 0, если нет.\n",
|
||
"##### Таким образом:\n",
|
||
"* Объект наблюдения - Реальные пациенты.\n",
|
||
"* Атрибуты: id, gender, age, hypertension, heart_disease, ever_married, work_type, Residence_type, avg_glucose_level, bmi, smoking_status, stroke.\n",
|
||
"* Проблемная область: Прогнозирование вероятности инсульта у пациента."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 355,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Количество колонок: 12\n",
|
||
"Колонки: id, gender, age, hypertension, heart_disease, ever_married, work_type, Residence_type, avg_glucose_level, bmi, smoking_status, stroke\n",
|
||
"\n",
|
||
"<class 'pandas.core.frame.DataFrame'>\n",
|
||
"RangeIndex: 5110 entries, 0 to 5109\n",
|
||
"Data columns (total 12 columns):\n",
|
||
" # Column Non-Null Count Dtype \n",
|
||
"--- ------ -------------- ----- \n",
|
||
" 0 id 5110 non-null int64 \n",
|
||
" 1 gender 5110 non-null object \n",
|
||
" 2 age 5110 non-null float64\n",
|
||
" 3 hypertension 5110 non-null int64 \n",
|
||
" 4 heart_disease 5110 non-null int64 \n",
|
||
" 5 ever_married 5110 non-null object \n",
|
||
" 6 work_type 5110 non-null object \n",
|
||
" 7 Residence_type 5110 non-null object \n",
|
||
" 8 avg_glucose_level 5110 non-null float64\n",
|
||
" 9 bmi 4909 non-null float64\n",
|
||
" 10 smoking_status 5110 non-null object \n",
|
||
" 11 stroke 5110 non-null int64 \n",
|
||
"dtypes: float64(3), int64(4), object(5)\n",
|
||
"memory usage: 479.2+ KB\n"
|
||
]
|
||
},
|
||
{
|
||
"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>id</th>\n",
|
||
" <th>gender</th>\n",
|
||
" <th>age</th>\n",
|
||
" <th>hypertension</th>\n",
|
||
" <th>heart_disease</th>\n",
|
||
" <th>ever_married</th>\n",
|
||
" <th>work_type</th>\n",
|
||
" <th>Residence_type</th>\n",
|
||
" <th>avg_glucose_level</th>\n",
|
||
" <th>bmi</th>\n",
|
||
" <th>smoking_status</th>\n",
|
||
" <th>stroke</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>9046</td>\n",
|
||
" <td>Male</td>\n",
|
||
" <td>67.0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Private</td>\n",
|
||
" <td>Urban</td>\n",
|
||
" <td>228.69</td>\n",
|
||
" <td>36.6</td>\n",
|
||
" <td>formerly smoked</td>\n",
|
||
" <td>1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>51676</td>\n",
|
||
" <td>Female</td>\n",
|
||
" <td>61.0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Self-employed</td>\n",
|
||
" <td>Rural</td>\n",
|
||
" <td>202.21</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>never smoked</td>\n",
|
||
" <td>1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>31112</td>\n",
|
||
" <td>Male</td>\n",
|
||
" <td>80.0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Private</td>\n",
|
||
" <td>Rural</td>\n",
|
||
" <td>105.92</td>\n",
|
||
" <td>32.5</td>\n",
|
||
" <td>never smoked</td>\n",
|
||
" <td>1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>60182</td>\n",
|
||
" <td>Female</td>\n",
|
||
" <td>49.0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Private</td>\n",
|
||
" <td>Urban</td>\n",
|
||
" <td>171.23</td>\n",
|
||
" <td>34.4</td>\n",
|
||
" <td>smokes</td>\n",
|
||
" <td>1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>1665</td>\n",
|
||
" <td>Female</td>\n",
|
||
" <td>79.0</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Self-employed</td>\n",
|
||
" <td>Rural</td>\n",
|
||
" <td>174.12</td>\n",
|
||
" <td>24.0</td>\n",
|
||
" <td>never smoked</td>\n",
|
||
" <td>1</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" id gender age hypertension heart_disease ever_married \\\n",
|
||
"0 9046 Male 67.0 0 1 Yes \n",
|
||
"1 51676 Female 61.0 0 0 Yes \n",
|
||
"2 31112 Male 80.0 0 1 Yes \n",
|
||
"3 60182 Female 49.0 0 0 Yes \n",
|
||
"4 1665 Female 79.0 1 0 Yes \n",
|
||
"\n",
|
||
" work_type Residence_type avg_glucose_level bmi smoking_status \\\n",
|
||
"0 Private Urban 228.69 36.6 formerly smoked \n",
|
||
"1 Self-employed Rural 202.21 NaN never smoked \n",
|
||
"2 Private Rural 105.92 32.5 never smoked \n",
|
||
"3 Private Urban 171.23 34.4 smokes \n",
|
||
"4 Self-employed Rural 174.12 24.0 never smoked \n",
|
||
"\n",
|
||
" stroke \n",
|
||
"0 1 \n",
|
||
"1 1 \n",
|
||
"2 1 \n",
|
||
"3 1 \n",
|
||
"4 1 "
|
||
]
|
||
},
|
||
"execution_count": 355,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"import pandas as pd\n",
|
||
"df = pd.read_csv(\".//static//csv//stroke.csv\", sep=\",\")\n",
|
||
"print('Количество колонок: ' + str(df.columns.size)) \n",
|
||
"print('Колонки: ' + ', '.join(df.columns)+'\\n')\n",
|
||
"\n",
|
||
"df.info()\n",
|
||
"df.head()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"#### Получение сведений о пропущенных данных\n",
|
||
"Типы пропущенных данных:\n",
|
||
"\n",
|
||
"- None - представление пустых данных в Python\n",
|
||
"- NaN - представление пустых данных в Pandas\n",
|
||
"- '' - пустая строка"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 356,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"id 0\n",
|
||
"gender 0\n",
|
||
"age 0\n",
|
||
"hypertension 0\n",
|
||
"heart_disease 0\n",
|
||
"ever_married 0\n",
|
||
"work_type 0\n",
|
||
"Residence_type 0\n",
|
||
"avg_glucose_level 0\n",
|
||
"bmi 201\n",
|
||
"smoking_status 0\n",
|
||
"stroke 0\n",
|
||
"dtype: int64\n",
|
||
"\n",
|
||
"id False\n",
|
||
"gender False\n",
|
||
"age False\n",
|
||
"hypertension False\n",
|
||
"heart_disease False\n",
|
||
"ever_married False\n",
|
||
"work_type False\n",
|
||
"Residence_type False\n",
|
||
"avg_glucose_level False\n",
|
||
"bmi True\n",
|
||
"smoking_status False\n",
|
||
"stroke False\n",
|
||
"dtype: bool\n",
|
||
"\n",
|
||
"id процент пустых значений: %0.00\n",
|
||
"gender процент пустых значений: %0.00\n",
|
||
"age процент пустых значений: %0.00\n",
|
||
"hypertension процент пустых значений: %0.00\n",
|
||
"heart_disease процент пустых значений: %0.00\n",
|
||
"ever_married процент пустых значений: %0.00\n",
|
||
"work_type процент пустых значений: %0.00\n",
|
||
"Residence_type процент пустых значений: %0.00\n",
|
||
"avg_glucose_level процент пустых значений: %0.00\n",
|
||
"bmi процент пустых значений: %3.93\n",
|
||
"smoking_status процент пустых значений: %0.00\n",
|
||
"stroke процент пустых значений: %0.00\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Количество пустых значений признаков\n",
|
||
"print(df.isnull().sum())\n",
|
||
"print()\n",
|
||
"\n",
|
||
"# Есть ли пустые значения признаков\n",
|
||
"print(df.isnull().any())\n",
|
||
"print()\n",
|
||
"\n",
|
||
"# Процент пустых значений признаков\n",
|
||
"for i in df.columns:\n",
|
||
" null_rate = df[i].isnull().sum() / len(df) * 100\n",
|
||
" print(f\"{i} процент пустых значений: %{null_rate:.2f}\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"##### Пропущенные данные существуют. Необходимо заполнить пропуски медианными значениями.\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Заполнение пропущенных данных:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 357,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"(5110, 12)\n",
|
||
"id False\n",
|
||
"gender False\n",
|
||
"age False\n",
|
||
"hypertension False\n",
|
||
"heart_disease False\n",
|
||
"ever_married False\n",
|
||
"work_type False\n",
|
||
"Residence_type False\n",
|
||
"avg_glucose_level False\n",
|
||
"bmi False\n",
|
||
"smoking_status False\n",
|
||
"stroke False\n",
|
||
"dtype: bool\n"
|
||
]
|
||
},
|
||
{
|
||
"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>id</th>\n",
|
||
" <th>gender</th>\n",
|
||
" <th>age</th>\n",
|
||
" <th>hypertension</th>\n",
|
||
" <th>heart_disease</th>\n",
|
||
" <th>ever_married</th>\n",
|
||
" <th>work_type</th>\n",
|
||
" <th>Residence_type</th>\n",
|
||
" <th>avg_glucose_level</th>\n",
|
||
" <th>bmi</th>\n",
|
||
" <th>smoking_status</th>\n",
|
||
" <th>stroke</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>5105</th>\n",
|
||
" <td>18234</td>\n",
|
||
" <td>Female</td>\n",
|
||
" <td>80.0</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Private</td>\n",
|
||
" <td>Urban</td>\n",
|
||
" <td>83.75</td>\n",
|
||
" <td>27.7</td>\n",
|
||
" <td>never smoked</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>5106</th>\n",
|
||
" <td>44873</td>\n",
|
||
" <td>Female</td>\n",
|
||
" <td>81.0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Self-employed</td>\n",
|
||
" <td>Urban</td>\n",
|
||
" <td>125.20</td>\n",
|
||
" <td>40.0</td>\n",
|
||
" <td>never smoked</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>5107</th>\n",
|
||
" <td>19723</td>\n",
|
||
" <td>Female</td>\n",
|
||
" <td>35.0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Self-employed</td>\n",
|
||
" <td>Rural</td>\n",
|
||
" <td>82.99</td>\n",
|
||
" <td>30.6</td>\n",
|
||
" <td>never smoked</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>5108</th>\n",
|
||
" <td>37544</td>\n",
|
||
" <td>Male</td>\n",
|
||
" <td>51.0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Private</td>\n",
|
||
" <td>Rural</td>\n",
|
||
" <td>166.29</td>\n",
|
||
" <td>25.6</td>\n",
|
||
" <td>formerly smoked</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>5109</th>\n",
|
||
" <td>44679</td>\n",
|
||
" <td>Female</td>\n",
|
||
" <td>44.0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Govt_job</td>\n",
|
||
" <td>Urban</td>\n",
|
||
" <td>85.28</td>\n",
|
||
" <td>26.2</td>\n",
|
||
" <td>Unknown</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" id gender age hypertension heart_disease ever_married \\\n",
|
||
"5105 18234 Female 80.0 1 0 Yes \n",
|
||
"5106 44873 Female 81.0 0 0 Yes \n",
|
||
"5107 19723 Female 35.0 0 0 Yes \n",
|
||
"5108 37544 Male 51.0 0 0 Yes \n",
|
||
"5109 44679 Female 44.0 0 0 Yes \n",
|
||
"\n",
|
||
" work_type Residence_type avg_glucose_level bmi smoking_status \\\n",
|
||
"5105 Private Urban 83.75 27.7 never smoked \n",
|
||
"5106 Self-employed Urban 125.20 40.0 never smoked \n",
|
||
"5107 Self-employed Rural 82.99 30.6 never smoked \n",
|
||
"5108 Private Rural 166.29 25.6 formerly smoked \n",
|
||
"5109 Govt_job Urban 85.28 26.2 Unknown \n",
|
||
"\n",
|
||
" stroke \n",
|
||
"5105 0 \n",
|
||
"5106 0 \n",
|
||
"5107 0 \n",
|
||
"5108 0 \n",
|
||
"5109 0 "
|
||
]
|
||
},
|
||
"execution_count": 357,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"fillna_df = df.fillna(0)\n",
|
||
"\n",
|
||
"print(fillna_df.shape)\n",
|
||
"\n",
|
||
"print(fillna_df.isnull().any())\n",
|
||
"\n",
|
||
"# Замена пустых данных на 0\n",
|
||
"df[\"bmi\"] = df[\"bmi\"].fillna(0)\n",
|
||
"\n",
|
||
"# Вычисляем медиану для колонки \"bmi\"\n",
|
||
"median_bmi = df[\"bmi\"].median()\n",
|
||
"\n",
|
||
"# Заменяем значения 0 на медиану\n",
|
||
"df.loc[df[\"bmi\"] == 0, \"bmi\"] = median_bmi\n",
|
||
"\n",
|
||
"df.tail()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Удалим наблюдения с пропусками:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 358,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"(5110, 12)\n",
|
||
"id False\n",
|
||
"gender False\n",
|
||
"age False\n",
|
||
"hypertension False\n",
|
||
"heart_disease False\n",
|
||
"ever_married False\n",
|
||
"work_type False\n",
|
||
"Residence_type False\n",
|
||
"avg_glucose_level False\n",
|
||
"bmi False\n",
|
||
"smoking_status False\n",
|
||
"stroke False\n",
|
||
"dtype: bool\n"
|
||
]
|
||
},
|
||
{
|
||
"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>id</th>\n",
|
||
" <th>gender</th>\n",
|
||
" <th>age</th>\n",
|
||
" <th>hypertension</th>\n",
|
||
" <th>heart_disease</th>\n",
|
||
" <th>ever_married</th>\n",
|
||
" <th>work_type</th>\n",
|
||
" <th>Residence_type</th>\n",
|
||
" <th>avg_glucose_level</th>\n",
|
||
" <th>bmi</th>\n",
|
||
" <th>smoking_status</th>\n",
|
||
" <th>stroke</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>5105</th>\n",
|
||
" <td>18234</td>\n",
|
||
" <td>Female</td>\n",
|
||
" <td>80.0</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Private</td>\n",
|
||
" <td>Urban</td>\n",
|
||
" <td>83.75</td>\n",
|
||
" <td>27.7</td>\n",
|
||
" <td>never smoked</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>5106</th>\n",
|
||
" <td>44873</td>\n",
|
||
" <td>Female</td>\n",
|
||
" <td>81.0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Self-employed</td>\n",
|
||
" <td>Urban</td>\n",
|
||
" <td>125.20</td>\n",
|
||
" <td>40.0</td>\n",
|
||
" <td>never smoked</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>5107</th>\n",
|
||
" <td>19723</td>\n",
|
||
" <td>Female</td>\n",
|
||
" <td>35.0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Self-employed</td>\n",
|
||
" <td>Rural</td>\n",
|
||
" <td>82.99</td>\n",
|
||
" <td>30.6</td>\n",
|
||
" <td>never smoked</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>5108</th>\n",
|
||
" <td>37544</td>\n",
|
||
" <td>Male</td>\n",
|
||
" <td>51.0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Private</td>\n",
|
||
" <td>Rural</td>\n",
|
||
" <td>166.29</td>\n",
|
||
" <td>25.6</td>\n",
|
||
" <td>formerly smoked</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>5109</th>\n",
|
||
" <td>44679</td>\n",
|
||
" <td>Female</td>\n",
|
||
" <td>44.0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Govt_job</td>\n",
|
||
" <td>Urban</td>\n",
|
||
" <td>85.28</td>\n",
|
||
" <td>26.2</td>\n",
|
||
" <td>Unknown</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" id gender age hypertension heart_disease ever_married \\\n",
|
||
"5105 18234 Female 80.0 1 0 Yes \n",
|
||
"5106 44873 Female 81.0 0 0 Yes \n",
|
||
"5107 19723 Female 35.0 0 0 Yes \n",
|
||
"5108 37544 Male 51.0 0 0 Yes \n",
|
||
"5109 44679 Female 44.0 0 0 Yes \n",
|
||
"\n",
|
||
" work_type Residence_type avg_glucose_level bmi smoking_status \\\n",
|
||
"5105 Private Urban 83.75 27.7 never smoked \n",
|
||
"5106 Self-employed Urban 125.20 40.0 never smoked \n",
|
||
"5107 Self-employed Rural 82.99 30.6 never smoked \n",
|
||
"5108 Private Rural 166.29 25.6 formerly smoked \n",
|
||
"5109 Govt_job Urban 85.28 26.2 Unknown \n",
|
||
"\n",
|
||
" stroke \n",
|
||
"5105 0 \n",
|
||
"5106 0 \n",
|
||
"5107 0 \n",
|
||
"5108 0 \n",
|
||
"5109 0 "
|
||
]
|
||
},
|
||
"execution_count": 358,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"dropna_df = df.dropna()\n",
|
||
"\n",
|
||
"print(dropna_df.shape)\n",
|
||
"\n",
|
||
"print(fillna_df.isnull().any())\n",
|
||
"df.tail()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"##### Проверим выбросы и усредним их:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 359,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Колонка age:\n",
|
||
" Есть выбросы: Нет\n",
|
||
" Количество выбросов: 0\n",
|
||
" Минимальное значение: 0.08\n",
|
||
" Максимальное значение: 82.0\n",
|
||
" 1-й квартиль (Q1): 25.0\n",
|
||
" 3-й квартиль (Q3): 61.0\n",
|
||
"\n",
|
||
"Колонка avg_glucose_level:\n",
|
||
" Есть выбросы: Да\n",
|
||
" Количество выбросов: 627\n",
|
||
" Минимальное значение: 55.12\n",
|
||
" Максимальное значение: 271.74\n",
|
||
" 1-й квартиль (Q1): 77.245\n",
|
||
" 3-й квартиль (Q3): 114.09\n",
|
||
"\n",
|
||
"Колонка bmi:\n",
|
||
" Есть выбросы: Да\n",
|
||
" Количество выбросов: 126\n",
|
||
" Минимальное значение: 10.3\n",
|
||
" Максимальное значение: 97.6\n",
|
||
" 1-й квартиль (Q1): 23.8\n",
|
||
" 3-й квартиль (Q3): 32.8\n",
|
||
"\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"numeric_columns = ['age', 'avg_glucose_level', 'bmi']\n",
|
||
"for column in numeric_columns:\n",
|
||
" if pd.api.types.is_numeric_dtype(df[column]): # Проверяем, является ли колонка числовой\n",
|
||
" q1 = df[column].quantile(0.25) # Находим 1-й квартиль (Q1)\n",
|
||
" q3 = df[column].quantile(0.75) # Находим 3-й квартиль (Q3)\n",
|
||
" iqr = q3 - q1 # Вычисляем межквартильный размах (IQR)\n",
|
||
"\n",
|
||
" # Определяем границы для выбросов\n",
|
||
" lower_bound = q1 - 1.5 * iqr # Нижняя граница\n",
|
||
" upper_bound = q3 + 1.5 * iqr # Верхняя граница\n",
|
||
"\n",
|
||
" # Подсчитываем количество выбросов\n",
|
||
" outliers = df[(df[column] < lower_bound) | (df[column] > upper_bound)]\n",
|
||
" outlier_count = outliers.shape[0]\n",
|
||
"\n",
|
||
" print(f\"Колонка {column}:\")\n",
|
||
" print(f\" Есть выбросы: {'Да' if outlier_count > 0 else 'Нет'}\")\n",
|
||
" print(f\" Количество выбросов: {outlier_count}\")\n",
|
||
" print(f\" Минимальное значение: {df[column].min()}\")\n",
|
||
" print(f\" Максимальное значение: {df[column].max()}\")\n",
|
||
" print(f\" 1-й квартиль (Q1): {q1}\")\n",
|
||
" print(f\" 3-й квартиль (Q3): {q3}\\n\")\n",
|
||
"\n",
|
||
" # Устраняем выбросы: заменяем значения ниже нижней границы на саму нижнюю границу, а выше верхней — на верхнюю\n",
|
||
" df[column] = df[column].apply(lambda x: lower_bound if x < lower_bound else upper_bound if x > upper_bound else x)\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"#### Постараемся выявить зависимости Stroke от остальных колонок:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"#### Разобьем наш набор на выборки относительно параметра Stroke:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 360,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 400x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 400x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 400x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import matplotlib.pyplot as plt\n",
|
||
"# Создание диаграмм зависимости\n",
|
||
"for column in numeric_columns:\n",
|
||
" plt.figure(figsize=(4, 6)) # Установка размера графика\n",
|
||
" if pd.api.types.is_numeric_dtype(df[column]): # Проверяем, является ли колонка числовой\n",
|
||
" # Проверяем, содержит ли колонка только два уникальных значения (0 и 1)\n",
|
||
" if df[column].nunique() == 2 and set(df[column].unique()).issubset({0, 1}):\n",
|
||
" counts = df[column].value_counts() \n",
|
||
" counts.plot(kind='bar', width=0.4) # Создаем столбчатую диаграмму\n",
|
||
" plt.title(f'Количество значений для {column}')\n",
|
||
" plt.xlabel(column)\n",
|
||
" plt.ylabel('Количество повторений')\n",
|
||
" else:\n",
|
||
" grouped_data = df.groupby('stroke')[column].mean()\n",
|
||
"\n",
|
||
" # Создаем столбчатую диаграмму\n",
|
||
" plt.bar(grouped_data.index, grouped_data.values, alpha=0.5, width=0.4)\n",
|
||
" plt.title(f'Среднее значение {column} по Stroke')\n",
|
||
" plt.xlabel('stroke (0 = нет, 1 = да)')\n",
|
||
" plt.ylabel(f'Среднее значение {column}')\n",
|
||
" plt.xticks([0, 1]) # Установка меток по оси X\n",
|
||
" plt.grid(axis='y')\n",
|
||
" else:\n",
|
||
" # Если колонка не числовая, строим столбчатую диаграмму\n",
|
||
" counts = df[column].value_counts() # Считаем количество повторений каждого значения\n",
|
||
" counts.plot(kind='bar', width=0.4) # Создаем столбчатую диаграмму\n",
|
||
" plt.title(f'Количество значений для {column}')\n",
|
||
" plt.xlabel(column)\n",
|
||
" plt.ylabel('Количество повторений')\n",
|
||
"\n",
|
||
" plt.show() "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 361,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Функция для создания выборок\n",
|
||
"from sklearn.model_selection import train_test_split\n",
|
||
"\n",
|
||
"def split_stratified_into_train_val_test(\n",
|
||
" df_input,\n",
|
||
" stratify_colname=\"y\",\n",
|
||
" frac_train=0.6,\n",
|
||
" frac_val=0.15,\n",
|
||
" frac_test=0.25,\n",
|
||
" random_state=None,\n",
|
||
"):\n",
|
||
"\n",
|
||
" if frac_train + frac_val + frac_test != 1.0:\n",
|
||
" raise ValueError(\n",
|
||
" \"fractions %f, %f, %f do not add up to 1.0\"\n",
|
||
" % (frac_train, frac_val, frac_test)\n",
|
||
" )\n",
|
||
"\n",
|
||
" if stratify_colname not in df_input.columns:\n",
|
||
" raise ValueError(\"%s is not a column in the dataframe\" % (stratify_colname))\n",
|
||
"\n",
|
||
" X = df_input # Contains all columns.\n",
|
||
" y = df_input[\n",
|
||
" [stratify_colname]\n",
|
||
" ] # Dataframe of just the column on which to stratify.\n",
|
||
"\n",
|
||
" # Split original dataframe into train and temp dataframes.\n",
|
||
" df_train, df_temp, y_train, y_temp = train_test_split(\n",
|
||
" X, y, stratify=y, test_size=(1.0 - frac_train), random_state=random_state\n",
|
||
" )\n",
|
||
"\n",
|
||
" # Split the temp dataframe into val and test dataframes.\n",
|
||
" relative_frac_test = frac_test / (frac_val + frac_test)\n",
|
||
" df_val, df_test, y_val, y_test = train_test_split(\n",
|
||
" df_temp,\n",
|
||
" y_temp,\n",
|
||
" stratify=y_temp,\n",
|
||
" test_size=relative_frac_test,\n",
|
||
" random_state=random_state,\n",
|
||
" )\n",
|
||
"\n",
|
||
" assert len(df_input) == len(df_train) + len(df_val) + len(df_test)\n",
|
||
"\n",
|
||
" return df_train, df_val, df_test"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 362,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"stroke\n",
|
||
"0 4861\n",
|
||
"1 249\n",
|
||
"Name: count, dtype: int64\n",
|
||
"\n",
|
||
"Обучающая выборка: (3066, 12)\n",
|
||
"stroke\n",
|
||
"0 2917\n",
|
||
"1 149\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 200x200 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Контрольная выборка: (1022, 12)\n",
|
||
"stroke\n",
|
||
"0 972\n",
|
||
"1 50\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 200x200 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Тестовая выборка: (1022, 12)\n",
|
||
"stroke\n",
|
||
"0 972\n",
|
||
"1 50\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAdEAAADECAYAAADArxsHAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAA200lEQVR4nO3dd1gU1/oH8O82dpfeqwgIIopYgqJiwa6gIUYNMWpi18R2jSa5amIs0WuMxhJbNLFF/RkLscQbG3YJscTeEBAsSG/CUpbdPb8/uLthWUBAlnHh/TwPj+7smXPemZ2dd+fMnBkeY4yBEEIIIdXG5zoAQgghxFBREiWEEEJqiJIoIYQQUkOURAkhhJAaoiRKCCGE1BAlUUIIIaSGKIkSQgghNURJlBBCCKkhIdcBEEIIqd8KCwuRmZkJoVAIe3t7rsOpVXQkSghB9+7d0bJlS67DINW0bt06ZGdna16vXr0aMpmMu4BKiYiIQGhoKCwtLSGVSuHi4oJ//etfXIdV66qVRLdv3w4ej6f5k0gk8Pb2xtSpU5GSkqKvGAkhADZs2IDt27dzHQZ5g/z+++9YsGABnj17ht27d2PevHmQSqVch4UNGzagX79+yMnJwZo1a3Dq1CmcOnUKixYt4jq0Wlej7txFixbBw8MDhYWFuHTpEjZu3Ig//vgDd+/ehbGxcW3HSAhByY7J1tYWo0eP5joU8oaYO3cuQkNDsWbNGvD5fHz//ffg87ntYIyJicHMmTMxceJEbNiwATwej9N49K1GSTQ4OBjt2rUDAIwfPx42NjZYuXIlDh8+jA8++KBWAySEVJ9MJoOJiQnXYRA9CwoKwpMnT/DgwQO4urqiUaNGXIeEH374AY6Ojvjhhx/qfQIFaumcaM+ePQEA8fHxAIDMzEx89tln8PPzg6mpKczNzREcHIxbt27pzFtYWIgFCxbA29sbEokETk5OGDx4MOLi4gAACQkJWl3IZf+6d++uqevcuXPg8XjYu3cv5s6dC0dHR5iYmCA0NBTPnj3Tafvy5cvo378/LCwsYGxsjKCgIERGRpa7jN27dy+3/QULFuiU3bVrF/z9/SGVSmFtbY1hw4aV235ly1aaSqXC6tWr4evrC4lEAgcHB0yaNAlZWVla5dzd3TFw4ECddqZOnapTZ3mxL1++XGedAkBRURHmz58PLy8viMViuLq64osvvkBRUVG566q07t2769S3ZMkS8Pl8/N///V+N1seKFSsQGBgIGxsbSKVS+Pv748CBA+W2v2vXLgQEBMDY2BhWVlbo1q0bTp48qVXm2LFjCAoKgpmZGczNzdG+fXud2Pbv36/5TG1tbTFy5EgkJiZqlRk9erRWzFZWVujevTsuXrz4yvWUnJyMMWPGoFGjRhCLxXBycsI777yDhIQEACWf7b1793D+/HmdbV99muX8+fOYPHky7O3ttXamGzZsgK+vL8RiMZydnTFlyhSt82gVOXnyJIyNjfHBBx9AoVAAAB4+fIihQ4fC2toaEokE7dq1w5EjR15ZV9nPViQSwd3dHZ9//jnkcnmV5yvvr/SReXZ2NmbMmAFXV1eIxWJ4eXlh2bJlUKlUWvWqVCqsWbMGfn5+kEgksLOzQ//+/XHt2jUAeGWbpbfp1NRUjBs3Dg4ODpBIJGjdujV27NhR4+V//Pgx3nvvPVhbW8PY2BgdO3bEf//7X60y6n3duXPnYGlpiU6dOqFRo0YYMGBAhful8uZX/4nFYnh7e2Pp0qUo/WCvBQsWgMfjIT09vcK63N3dtT6Dv/76C/7+/pg8eTIcHBwgFovRsmVL/PTTTzrzymQyzJo1S/N5NWvWDCtWrEDZh4vxeDxMnToVu3fvRrNmzSCRSODv748LFy5olVPHW9rZs2chFovx8ccfa01PTEzE2LFjNTH6+vpi69atla638tTK1bnqhGdjYwOgZCM4dOgQ3nvvPXh4eCAlJQWbNm1CUFAQ7t+/D2dnZwCAUqnEwIEDcfr0aQwbNgz/+te/kJubi1OnTuHu3bvw9PTUtPHBBx8gJCREq905c+aUG8+SJUvA4/Hw73//G6mpqVi9ejV69+6Nmzdvas4XnDlzBsHBwfD398f8+fPB5/Oxbds29OzZExcvXkRAQIBOvY0aNcLSpUsBAHl5efjkk0/KbXvevHkICwvD+PHjkZaWhrVr16Jbt264ceMGLC0tdeaZOHEiunbtCgD47bffcPDgQa33J02ahO3bt2PMmDGYPn064uPjsW7dOty4cQORkZEQiUTlrofqyM7O1ixbaSqVCqGhobh06RImTpyI5s2b486dO1i1ahUePXqEQ4cOVaudbdu24auvvsL333+P4cOHl1vmVetjzZo1CA0NxYgRIyCXy/Hrr7/ivffew9GjRzFgwABNuYULF2LBggUIDAzEokWLYGRkhMuXL+PMmTPo27cvgJIENHbsWPj6+mLOnDmwtLTEjRs3cPz4cU186nXfvn17LF26FCkpKVizZg0iIyN1PlNbW1usWrUKAPD8+XOsWbMGISEhePbsWbmfvdqQIUNw7949TJs2De7u7khNTcWpU6fw9OlTuLu7Y/Xq1Zg2bRpMTU3x5ZdfAgAcHBy06pg8eTLs7Ozw9ddfay4uWbBgARYuXIjevXvjk08+QXR0NDZu3IirV69Wuu0cPXoUQ4cOxfvvv4+tW7dCIBDg3r176Ny5M1xcXDB79myYmJhg3759GDRoEMLDw/Huu+9WuHxq6s+2qKgIJ06cwIoVKyCRSPDNN9+UW97Ozg47d+7UvFZvD6WnqfcT+fn5CAoKQmJiIiZNmoTGjRvjzz//xJw5c5CUlITVq1dr5hk3bhy2b9+O4OBgjB8/HgqFAhcvXsRff/2Fdu3aadV/8eJFbN68GatWrYKtra3Wui8oKED37t0RGxuLqVOnwsPDA/v378fo0aORnZ2tcyHNq5Y/JSUFgYGByM/Px/Tp02FjY4MdO3YgNDQUBw4cqHQdX7hwAX/88ccrP4PS5s6di+bNm6OgoEBz8GFvb49x48ZVq57SMjIycO3aNQiFQkyZMgWenp44dOgQJk6ciIyMDMyePRsAwBhDaGgozp49i3HjxqFNmzY4ceIEPv/8cyQmJmq+R2rnz5/H3r17MX36dIjFYmzYsAH9+/fHlStXKrwo7tatWxg0aBBCQkKwfv16zfSUlBR07NhRk5zt7Oxw7NgxjBs3Di9fvsSMGTOqvsCsGrZt28YAsIiICJaWlsaePXvGfv31V2ZjY8OkUil7/vw5Y4yxwsJCplQqteaNj49nYrGYLVq0SDNt69atDABbuXKlTlsqlUozHwC2fPlynTK+vr4sKChI8/rs2bMMAHNxcWEvX77UTN+3bx8DwNasWaOpu2nTpqxfv36adhhjLD8/n3l4eLA+ffrotBUYGMhatmypeZ2WlsYAsPnz52umJSQkMIFAwJYsWaI17507d5hQKNSZHhMTwwCwHTt2aKbNnz+flf5YLl68yACw3bt3a817/Phxnelubm5swIABOrFPmTKFlf2oy8b+xRdfMHt7e+bv76+1Tnfu3Mn4fD67ePGi1vw//vgjA8AiIyN12istKChIU99///tfJhQK2axZs8otW5X1wVjJ51SaXC5nLVu2ZD179tSqi8/ns3fffVdnW1R/5tnZ2czMzIx16NCBFRQUlFtGLpcze3t71rJlS60yR48eZQDY119/rZk2atQo5ubmplXP5s2bGQB25cqVcpeZMcaysrIq3MZLK7u9q6m/l126dGEKhUIzPTU1lRkZGbG+fftqrYN169YxAGzr1q2aaUFBQczX15cxxlh4eDgTiURswoQJWvP16tWL+fn5scLCQs00lUrFAgMDWdOmTSuNXf093rZtm9Z0Z2dnFhISUum8pZW3Pah98803zMTEhD169Ehr+uzZs5lAIGBPnz5ljDF25swZBoBNnz5dp47S+wM19fqNj4/XeW/16tUMANu1a5dmmlwuZ506dWKmpqaa/VBVl3/GjBkMgNb3LTc3l3l4eDB3d3fN56He1509e1ZTrkOHDiw4OFjnu12e8uYvLCxkfD6fTZ48WTNNvb7T0tIqrMvNzY2NGjVK6zUAtn37ds00hULBevXqxcRiMUtPT2eMMXbo0CEGgC1evFirvqFDhzIej8diY2M10wAwAOzatWuaaU+ePGESiYS9++67OvEyVrI/dnJyYl26dNH5fo8bN445OTlpYlEbNmwYs7Cw0NnHVKZG3bm9e/eGnZ0dXF1dMWzYMJiamuLgwYNwcXEBAIjFYs3JbaVSiYyMDJiamqJZs2a4fv26pp7w8HDY2tpi2rRpOm28Tl/6Rx99BDMzM83roUOHwsnJSfMr7ebNm4iJicHw4cORkZGB9PR0pKenQyaToVevXrhw4YJO909hYSEkEkml7f72229QqVQICwvT1Jmeng5HR0c0bdoUZ8+e1Sqv7sYRi8UV1rl//35YWFigT58+WnX6+/vD1NRUp87i4mKtcunp6SgsLKw07sTERKxduxbz5s2DqampTvvNmzeHj4+PVp3qLvyy7VfkypUrCAsLw5AhQ7B8+fJyy1RlfQDQuvowKysLOTk56Nq1q9a2dejQIahUKnz99dc6F1qot61Tp04hNzcXs2fP1vls1WWuXbuG1NRUTJ48WavMgAED4OPjo9PNplKpNOvo5s2b+OWXX+Dk5ITmzZtXujxGRkY4d+6cThd9dUyYMAECgUDzOiIiAnK5HDNmzNBaBxMmTIC5ublO7ACwZ88evP/++5g0aRI2bdqkmS8zMxNnzpxBWFgYcnNzNcuYkZGBfv36ISYmRqd7uzx5eXlIT09HYmIiNm/ejOTkZPTq1avGy1za/v370bVrV1hZWWltq71794ZSqdR0/YWHh4PH42H+/Pk6dVR3v/PHH3/A0dFR61oQkUiE6dOnIy8vD+fPn9cq/6rl/+OPPxAQEIAuXbpoppmammLixIlISEjA/fv3y43jt99+w9WrV/Htt99WK/6cnBykp6fj6dOn+O6776BSqTTf7dIyMzM1+8iqcHBwwIcffqh5LRAIMGPGDBQVFSEiIgJAybIKBAJMnz5da95Zs2aBMYZjx45pTe/UqRP8/f01rxs3box33nkHJ06cgFKp1Cqr3i7NzMxw5MgRre8uYwzh4eF4++23wRjT2lbUVxSX3pe8So26c9evXw9vb28IhUI4ODigWbNmWl9S9fmGDRs2ID4+XmsB1V2+QEk3cLNmzSAU1u49H5o2bar1msfjwcvLS3N+KSYmBgAwatSoCuvIycmBlZWV5nV6erpOvWXFxMSAMVZhubJdZ+rzUmUTV9k6c3JyKhygnJqaqvX65MmTsLOzqzTOsubPnw9nZ2dMmjRJ59xiTEwMHjx4UGGdZdsvT2JiIgYMGACZTIaMjIwKd1RVWR9ASVfj4sWLcfPmTa3zsqXrjYuLA5/PR4sWLSqsR30aorLxkU+ePAEANGvWTOc9Hx8fXLp0SWvas2fPtNaVk5MTwsPDK10msViMZcuWYdasWXBwcEDHjh0xcOBAfPTRR3B0dKxwvrI8PDyqFLuRkRGaNGmieV8tPj4eI0eOxHvvvYe1a9dqvRcbGwvGGObNm4d58+aV235qaqrmh3RFpk2bpvWjecyYMfj0008rX7AqiomJwe3bt1+5rcbFxcHZ2RnW1tav3eaTJ0/QtGlTnR9q6h9NZdfxq5b/yZMn6NChg047pesru70qlUrMnTsXI0aMQKtWraoV/6BBgzT/5/P5+OqrrzBkyBCdcqW3IXt7e0yYMAELFy7U+tGmxuPx4O3tXeE6Ue+Hnzx5AmdnZ60DntLlyq678var3t7eyM/PR1pamtZ3ZeDAgYiOjoa9vb3O+dW0tDRkZ2dj8+bN2Lx5s06dQNX2a2o1yl4BAQGaq3PL85///Afz5s3D2LFj8c0338Da2hp8Ph8zZszQOcLjgjqG5cuXo02bNuWWKb3Tk8vlSEpKQp8+fV5ZL4/Hw7Fjx8rduMruSJOTkwGg0h2lSqWCvb09du/eXe77ZXcYHTp0wOLFi7WmrVu3DocPHy53/gcPHmD79u3YtWtXuefHVCoV/Pz8sHLlynLnd3V1rTB2tdjYWLz11ltYtWoVPvzwQ+zYsaPcHzBVWR8XL15EaGgounXrhg0bNsDJyQkikQjbtm3TuRiICw4ODti1axeAkh9iW7duRf/+/XHp0iX4+flVON+MGTPw9ttv49ChQzhx4gTmzZuHpUuX4syZM2jbtm2V2n7d8YFOTk6aHptr165pfcfV35nPPvsM/fr1K3d+Ly+vV7bx+eefo2/fvlAqlbh37x4WLVoExhi2bdv2WrGrY+zTpw+++OKLct/39vZ+7TZelz6Wf8uWLUhISMCJEyeqPe+KFSvQunVrFBcX4+rVq1i8eDGEQqHOUXp4eDjMzc2Rn5+PgwcPYsmSJTA3Ny93Xb8J41QfPnyIY8eOISwsDLNmzdJav+pteeTIkRUeSFXnx4hebvt34MAB9OjRA1u2bNGanp2drTkxD5RcEHD58mUUFxfXysUxauojTTXGGGJjYzUrRn0hgrm5OXr37v3K+m7duoXi4uJKfzio62WMwcPDo0pf2Pv374PH45V7lFO6zoiICHTu3LlKG6etra3OMlV28c+cOXPQpk0bvP/++xW2f+vWLfTq1avGXezqHbODgwMOHz6MWbNmISQkROcHQFXWR3h4OCQSCU6cOKHV7Vt2J+Tp6QmVSoX79+9X+ENJvR3cvXu3wgTg5uYGAIiOjtbp5oqOjta8ryaRSLTWf2hoKKytrbFu3Tps2rSpwuVSxzNr1izMmjULMTExaNOmDb7//ntNUq7u+i8de5MmTTTT5XI54uPjdbYTiUSCo0ePomfPnujfvz/Onz8PX19fANDMLxKJqvSdqUiLFi008/fr1w9FRUWYO3culixZorngsKY8PT2Rl5f3yvg8PT1x4sQJZGZmvvbRqJubG27fvg2VSqV15PXw4UPN+6W9avnd3NwQHR2t005F9eXn52PhwoWYPHmyzntV4e/vr7nSODg4GImJiVi2bBnmzZuntTzdunXT7LtDQ0MRGRmJ48ePl5tEPTw8cP369QrXibu7u2ZZIiIikJubq3U0WtGylt2vA8CjR49gbGyssy85cuQIunbtiqVLl2Lq1KkYOXKkptvczs4OZmZmUCqVr7Utq+llVK5AINA5hN6/f7/OOZMhQ4YgPT0d69at06mj7PzV8csvvyA3N1fz+sCBA0hKSkJwcDCAkg3H09MTK1asQF5ens78aWlpOrELBIJyh4+UNnjwYAgEAixcuFAnfsYYMjIyNK8VCgXCw8MREBBQaVdfWFgYlEpluVcvKhSKKg1VqEhUVBQOHz6Mb7/9tsIddFhYGBITE8u9PL2goKBK50i8vb01VzOuXbsWKpVK56rFqq4PgUAAHo+ndYogISFB54fCoEGDwOfzsWjRIp3eD/Vn07dvX5iZmWHp0qU6543VZdq1awd7e3v8+OOPWl3Hx44dw4MHD7SuBi6PXC6HQqGodDhQfn6+Tvuenp4wMzPTms/ExKRan3fv3r1hZGSEH374QWt73LJlC3JycsqN3cLCAidOnIC9vT369Omj6fK2t7dH9+7dsWnTJiQlJenMV/Y7U1UFBQUAUOkwl6oKCwtDVFRUuUdk2dnZmmE6Q4YMAWMMCxcu1ClX3f1OSEgIkpOTsXfvXs00hUKBtWvXwtTUFEFBQZXOX3b5Q0JCcOXKFURFRWnKyGQybN68Ge7u7jqnJ9asWQOZTKa5Yvt1FRQUQKFQaNZVeRhjYIyV29umXoay60R9ik8sFmsSV0hICJRKpc7+f9WqVeDxeJr9tVpUVJTWucpnz57h8OHD6Nu3r04s6qv7J0+ejMDAQEyaNEmzrgUCAYYMGYLw8HDcvXtXJ/7qbst6ORIdOHAgFi1ahDFjxiAwMBB37tzB7t27tX4NAyUXAP3yyy+YOXMmrly5gq5du0ImkyEiIgKTJ0/GO++8U6P2ra2t0aVLF4wZMwYpKSlYvXo1vLy8MGHCBAAlff8///wzgoOD4evrizFjxsDFxQWJiYk4e/YszM3N8fvvv0Mmk2H9+vX44Ycf4O3tjXPnzmnaUCff27dvIyoqCp06dYKnpycWL16MOXPmICEhAYMGDYKZmRni4+Nx8OBBTJw4EZ999hkiIiIwb9483L59G7///nulyxIUFIRJkyZh6dKluHnzJvr27QuRSISYmBjs378fa9aswdChQ2u0nk6ePIk+ffpU+mvsww8/xL59+/Dxxx/j7Nmz6Ny5M5RKJR4+fIh9+/bhxIkTrzxCL83R0RHLly/H+PHjMXLkSISEhFRrfQwYMAArV65E//79MXz4cKSmpmL9+vXw8vLC7du3NeW8vLzw5Zdf4ptvvkHXrl0xePBgiMViXL16Fc7Ozli6dCnMzc2xatUqjB8/Hu3bt8fw4cNhZWWFW7duIT8/Hzt27IBIJMKyZcswZswYBAUF4YMPPtAMcXF3d9c5nyeTybS6c3fu3InCwsJKhyY8evQIvXr1QlhYGFq0aAGhUIiDBw8iJSUFw4YN05Tz9/fHxo0bsXjxYnh5ecHe3r7ci0DU7OzsMGfOHCxcuBD9+/dHaGgooqOjsWHDBrRv3x4jR44sdz5bW1ucOnUKXbp0Qe/evXHp0iW4uLhg/fr16NKlC/z8/DBhwgQ0adIEKSkpiIqKwvPnz8sdB15WVFQUhEKhpjtz7dq1aNu2rebo5HV8/vnnOHLkCAYOHIjRo0fD398fMpkMd+7cwYEDB5CQkABbW1v06NEDH374IX744QfExMSgf//+UKlUuHjxInr06IGpU6dWuc2JEydi06ZNGD16NP7++2+4u7vjwIEDiIyMxOrVq3XO971q+WfPno09e/YgODgY06dPh7W1NXbs2IH4+HiEh4frnGc8efIklixZonWtSXWcOnUKz58/13Tn7t69G6GhoTAyMtIqd+bMGa3u3NjY2AqHgYwbNw4bN27E6NGjce3aNXh4eODQoUM4ffo0vv32W02sb7/9Nnr06IEvv/wSCQkJaN26NU6ePInDhw9jxowZWkMcgZJrF/r166c1xAVAuT+G1Hg8Hn7++We0adMG8+fPx3fffQcA+Pbbb3H27Fl06NABEyZMQIsWLZCZmYnr168jIiICmZmZVV+JVb6Ol/1zqffVq1crLVdYWMhmzZrFnJycmFQqZZ07d2ZRUVFawx3U8vPz2Zdffsk8PDyYSCRijo6ObOjQoSwuLo4xVrMhLnv27GFz5sxh9vb2TCqVsgEDBrAnT57ozH/jxg02ePBgZmNjw8RiMXNzc2NhYWHs9OnTWm2/6q/05d2MlQwR6NKlCzMxMWEmJibMx8eHTZkyhUVHRzPGGJs2bRrr1q0bO378uE5MFV3Cv3nzZubv78+kUikzMzNjfn5+7IsvvmAvXrzQlKnuEBcej8f+/vtvrenlfUZyuZwtW7aM+fr6MrFYzKysrJi/vz9buHAhy8nJ0WnvVfUxxljPnj1Z48aNWW5ubrXXx5YtW1jTpk2ZWCxmPj4+bNu2bRWut61bt7K2bdtq4g4KCmKnTp3SKnPkyBEWGBjIpFIpMzc3ZwEBAWzPnj1aZfbu3aupx9ramo0YMUIzpEtt1KhRWtuFqakpe+utt9jOnTsrXUfp6elsypQpzMfHh5mYmDALCwvWoUMHtm/fPq1yycnJbMCAAczMzIwB0KzXV30v161bx3x8fJhIJGIODg7sk08+YVlZWVplSg9xUYuNjWVOTk6sefPmmiEOcXFx7KOPPmKOjo5MJBIxFxcXNnDgQHbgwIFKl7Hsd4nP57NGjRqxUaNG6azHylQ2xIWxkuEgc+bMYV5eXszIyIjZ2tqywMBAtmLFCiaXyzXlFAoFW758OfPx8WFGRkbMzs6OBQcH63wfGKt8iAtjjKWkpLAxY8YwW1tbZmRkxPz8/HSGslRn+ePi4tjQoUOZpaUlk0gkLCAggB09elSrjHpf5+TkxGQymdZ7qMYQF/WfUChkbm5ubPr06Vrbhnp9q/+kUilr0aIFW7VqlaZM2SEujJUMrxo7dqxmnbRs2ZL99NNPOnHk5uayTz/9lDk7OzORSMSaNm3Kli9frjPUCACbMmUK27Vrl+a737ZtW60hOqXjLWvhwoVMKBSy69eva6alpKSwKVOmMFdXV03u6dWrF9u8eXOl664s3v8CrBfOnTuHHj16YP/+/TU+OistISEBHh4eiI+Pr/CX8oIFC5CQkEA3BieEED3h8XiYMmVKuaf+uEaPQiOEEEJqiB7KXQlTU1OMGDGi0gtdWrVq9dpXFRJCCDFMlEQrYWtrq7lIpCKDBw+uo2gIIYS8aerVOVFCCCGkLtE5UUIIIaSGKIkSQgghNURJlBBCCKkhSqKEEEJIDVESJYQQQmqIkighhBBSQ5RECSGEkBqiJEoIIYTUECVRQuqZCxcu4O2334azszN4PF6lD2UnhLweSqKE1DMymQytW7fG+vXruQ6FkHqP7p1LSD0THByM4OBgrsMgpEGgI1FCCCGkhiiJEkIIITVESZQQQgipIUqihBBCSA1REiWEEEJqiK7OJaSeycvLQ2xsrOZ1fHw8bt68CWtrazRu3JjDyAipf3iMMcZ1EISQ2nPu3Dn06NFDZ/qoUaOwffv2ug+IkHqMkighHMopKEZabiFSc4uQ9r+/DJkcBXIlFCoVepo8QU/5OUBgBAiNSv41MgUsXQFLN8DKHTC25noxCGmwqDuXkDqgVDHEpeXh/ouXuPciB/eTXuJBUi4yZfJK52vZ5C7w4qfKKzcyA2y9AAdfwMGv5F/HloDUqhaXgBBSHkqihOjJs8x8nItOxdnoNPz1OAP5cqV+GpLnAi9ulPxp8ACnVkDTviV/Lu0APl1HSEhtoyRKSC26lpCJ43eTcTY6FXFpMg4jYUDSrZK/C8sBqTU2t9gOTy8fdG1qByMhJVRCagMlUUJeU8rLQuy/9gwH/n6OhIx8rsMpl0JojP9E5gGR12AuESK0jTNGdXJHUwczrkMjxKBREiWkhv6MTceOqAScfpAKherNvj7voWUQkFby/5eFCuz66yl2/fUUnb1s8FEnd/Ru7gABn8dtkIQYIEqihFTTpZh0rI54hGtPsrgOpcr2y9qUOz0yNgORsRlwsZRiXBcPjOzoRl29hFQDJVFCqujPuHSsPhWDKwmZXIdSLSqpLXYlOVVaJjG7AIuO3sfWyHjM7OONQW1cwKcjU0JeiZIoIa8Qk5KLrw/fQ9TjDK5DqZF4m25QZlXt6PJ5VgFm7ruFny7G44v+zdCjmb2eoyPEsFESJaQChcVKrDsTi00X4lCsfLPPeVbmiPytas/zIOklxmy7im7edvh2sB+cLaV6iIwQw0cnPwgpR2RsOoLXXMS6s7EGnUCZkSl+fuFW4/kvPEpDv1UXsOfK01qMipD6g5IoIaUUyJX44sAtjPj5MuLTuRznWTte2HWFTCF4rTpyixSY89sdfLjlMhKzC2opMkLqB0qihPxPXFoeBq2PxL5rz7kOpdYcV7WvtbouxqSj36oLOHQjsdbqJMTQURIlBMDvt14gdO0lRKfkch1KrWECMTa98KzVOvOKFJix9yYWHLmHYqWqVusmxBBREiUNWrFShfmH72LanhuQ6evethzJcOiE1CKRXure/mcCRvx8+ZU30CekvqMkShqsvCIFxm6/ih1RT7gORS/OIkCv9V+Jz8Q76y8hph4dvRNSXZRESYOUnleEYZujcDEmnetQ9ILxBNiY7KP3dp5lFmDoj1G4/Txb720R8iaiJEoanKScAoT9GIW7iS+5DkVvcu3b4XG+pE7ayikoxoifL+P6U8O5DSIhtYWSKGlQnmXm470fo/C4Hgxfqcyfoo512l5uoQIfbbmCqwZ2S0RCXhclUdJgpOcVYeSWy3ieVf/HOm5O863zNvOKFBi19Qqi4gzz9oiE1AQlUdIgyP53EdGTN/B5nzl/7ceTZQORGbG5wjLFSoZF54vg+UMuJItfovWPeTgeq9Aqs/t2MVxX5cLqOxkiftuj9Z4iJwWJmydCVaTf5c+XKzFux1Xce5Gj13YIeVNQEiX1XrFShU92X8ft52/ejr0o6RFybx6HyM690nJfnSnCpr/lWBsswf0ppvjY3wjv7s3HjaSSYTnp+SqM/70AK/pIsGzmcMjun0N+7BXN/BknN8AqaDT4YmN9Lg6AkkQ6fsc1pLws1HtbhHCNkiip9/4dfhsXHqVxHYYOlbwA6b+vgE3/aeBLTCstu/N2MeZ2ESOkqQhNrPj4pL0RQpoK8X1UyTjNx1kMFmIe3m8pwl8WfSBp3ArFGc8AALL758HjC2HcLFDvy6SWlFOI8TuuoaCejb0lpCxKoqRe+/F8HH67/mbepi7z1EZIPdtD6t7mlWWLlICkzDOXpEIeLj0t6dJtas1HfjHDlTwnnHougjzpEYzs3KEszEP2xV2w7vOxHpagcncSczBj7w0wZrg38CfkVSiJknrr7ydZWHEimuswyiW7fx7y5DhYBY2qUvl+ngKs/EuOmAwlVIzhVJwCvz0oRlJeSYKykvKwY5AUw39NR/IvM2HSsiekTfyRdWYLzN4aCEVOCl5sm44XWyZD9vCSPhdNy4l7KVgVEVNn7RFS1+h5oqReyskvxvQ9N6BQvXlHQYqXacg8/RMc3v8GPKFRleZZ01+CCb8Xwme9DDwAntZ8jGkjwtabxZoy7zYXIbLTdziQ7AAAKHx6B8VpCbDuMwkvNk+E7dufQ2BihaRfZkLi2hICE0s9LJ2u9WdjEeRtB383qzppj5C6REmU1EtfhN96Yx/bJU+OhSo/G0nb//XPRKZC0bN7yL1+FI0/OwgeX/vxZXYmfBwaZoxCBUNGPoOzGQ+zI4rQxOqfziSlqTPCU+xLqlMUI/PkRtgMnAlFVhKYSglJYz8AgMjaBUVJ0TD26qD/hQWgVDF8uvcmjv2rK0zEtMsh9Qtt0aTe2RmVgBP3UrgOo0ISt9ZwGrtOa1rGH2sgsmkE8w5DdBKo1rxCHlzMeShWMoQ/KEaY7z83mH9k1Q0snQcAyPnzV0iavAWxoxfkKXGA6p8LfJhKAajq9gksTzPzsej3+1g2tFWdtkuIvlESJfVKystCLDv+Zp4HVeOLjWFUZkgLTyQGX2KmmZ5+9HsIzGyAJv4AgMvPFUjMZWjjKEDiSxUWnC+CigFfdBZr6ggvaAsAkKc/hezhRTiN/gEAILRuBPD4yL11EgJTKxRnPIeRU1P9L2gZe689Q6/m9ujr61jnbROiL5RESb3yzdH7yCtSvLrgG07xMg3g/dNVW6goGSv6OEsFUyMeQpoKsfNdKSwlJUeeKqk1dr5wAWMMmcfXwarnePCNSu6dyxeJYRMyA5mnNoIpi2Hd52MIzWw5Wa65B++ik6cNzCT6eUQbIXWNx+j6c1JPRMamY8TPl7kOo1Z92+QOhr1Y+spy8Y0GoUdsWB1E9PrGd/HAVwNbcB0GIbWChriQekGuUGHe4btch8GZo3J/rkOosh1RCYhNzeM6DEJqBSVRUi9sjYzH47T6/WSWijCRCTa/cOM6jCorVjJ8e+wh12EQUisoiRKDl1tYjI3n4rgOgzPJ9p2RqzCsyxsiHqTgSjw9No0YPkqixOBti0xATkHxqwvWU6dUAVyHUCMrT73ZV1ETUhWURIlBkxUpsDUynuswOMP4ImxM8uI6jBr563Em7ia+eU/WIaQ6KIkSg7bnylNk5zfco9As+45IKqzarQPfRJsvPOY6BEJeCyVRYrAUShW2Xmq4R6EAcE7QkesQXssfd5Lw4g29PSMhVUFJlBisMw9T8SKn4T74mfH4+DHZh+swXotCxbCtAXfHE8NHSZQYrPDrz7kOgVN5dm/hkUzKdRiv7dcrz1BYTA/vJoaJkigxSJkyOc48TOU6DE79ZdSJ6xBqRW6RosF/lsRwURIlBunIzUQUKxv2HSt/SvflOoRac/T2C65DIKRGKIkSg3SggXflFtq0wJVsc67DqDVnHqZCVg8eHEAaHkqixOA8yZDhbuJLrsPg1A3jLlyHUKsKi1WIePDmPgOWkIpQEiUG50JMOtchcO6X7JZch1Drfr+VxHUIhFQbJVFicC7FpHEdAqeKLdxxLI2b54HqU1RcOpSqhn2emxgeSqLEoChVDH/GZXAdBqfuW3TlOgS9kMmVdBtAYnAoiRKDcut5NnILG/YFKL/mtuY6BL25mkBPdiGGhZIoMSiRDfx8qNLEAb8mO3Edht5cpsejEQNDSZQYlDsNvLsvzrobGONxHYbeXEvIBGN0XpQYDkqixKA8SsnlOgROHSxsy3UIepWVX4zH6TKuwyCkyiiJEoNRIFfiaWY+12FwhoktsP2FK9dh6F1MSh7XIRBSZZREicGISc1FQx4B8cyuGwqUAq7D0Lu4NEqixHBQEiUGIzq5YXfl/lHsz3UIdYKSKDEklESJwYhLa7jnyphQik0vmnAdRp14nkkP6SaGg5IoMRipuQ33Adyp9p2RVSzkOow68Tyr4Z73JoaHkigxGGm5RVyHwJnTaM91CHUmLa/hfs7E8FASJQYjUybnOgROML4QG154cx1GnSlWMhQplFyHQUiVUBIlBiOnoJjrEDiRYx+A54VirsOoU7IiSqLEMFASJQajod4z96KwE9ch1Dl6QDcxFJREicFoiF18KgA/pvhwHUadk8kpiRLDQEmUGAwBr/7eM7YiJ7Mb4V6uCddh1Dk6EiWGgpIoMRgCfsNLoucyrbgOgRP8BviDiRgmSqLEYIgEtLk2FCbihjEmlhg+2isRg9EQj0QbKqmo/t8jmNQPlESJwaAj0YbD2IiSKDEMtFciBsNCKuI6BFJHjI2oO5cYBkqixGA4WUi4DoHUAQGfB4mIdk3EMNCWSgyGkyUl0YbAxVIKHl2dSwwEJVFiMJwspFyHQOqAm40x1yEQUmWURInBcDSnI9GGoLE1JVFiOCiJEoPhYkVHog2Bu03Du0MTMVyURInBaO5kDjpVVv81pu5cYkAoiRKDYSEVwY26+uo9L3tTrkMgpMooiRKD0qqRJdchED2ykIrQxJa6c4nhoCRKDEqrRhZch0D0qLWrJQ1vIQaFkigxKHQkWr+1d2uYT60hhouSKDEofi4WMBLSZltfdfS04ToEQqqF9kbEoEiNBOjgYc11GEQPpCIBWlNPAzEwlESJwenRzJ7rEIgedPO2pV4GYnBoiyUGp08LB65DIHowoJUz1yEQUm2URInBcbU2hq+zOddhkFokEfHRuzn1MBDDQ0mUGKQQPyeuQyC1qEcze3qGKDFIlESJQRryViMI+TSesL4Y0Ip+FBHDREmUGCRHCwl6UfdfvWAuEaKXD53nJoaJkigxWB92dOc6BFILPujQGFIjAddhEFIjlESJwersZQMPus+qQRPyeRgd6M51GITUGCVRYrB4PB5GdGjMdRjkNQT7OcHJgp4TSwwXJVFi0N5v7wpLYxHXYZAaGt/Fg+sQCHktlESJQTOTiPBxkCfXYZAaCPCwRmtXS67DIOS1UBIlBm90oDvszcRch0GqgccD5gT7cB0GIa+NkigxeBKRANN6NeU6DFINA1s5o21jeuwZMXyUREm9MKy9KxpbG3MdBqkCsZCPf/dvxnUYhNQKus8WqRdEAj6+HNAck3b+XWdtqorykX1xF/JjoqDKz4GRfRNY9Z4IsZM3ACD9v6sgu3taax6Jx1twCFtUYZ2Fz+7i5eVwyFPioMzLhN27X8LYu5NWmZzLv+HllXAAgEWHITAPGKx5r+hFNDJPboDjRyvB47+ZYy/HdPZAIyv6wUPqB0qipN7o5+uIED9H/HEnuU7ayzi+FsVpT2A7cBYEptaQ3TuLlF+/gvP4DRCa2QIAJB7+sA2Z8c9MwsqvJGbyQojsm8C0VR+kHfyPzvvy1HjkXNoNu6FfA4whLXwRJB5vwcjOHUylRMaJ9bDpP/WNTaC2pmJM6UEXgpH6g7pzSb2yMLRlnQx5URUXIT86EpY9xkDi2hIiK2dYdhkBkZUTcm8c05TjCUUQmFr98ycxrbReqWc7WHX7EMbegeW+X5zxHCI7d0jdWkPq3gYiO3cUZzwHALy8HA6Jq6/mSPhNtOTdljCT0JAkUn9QEiX1ip2ZGPMGtNB/QyolwFTgCbQTAk8oRtHze5rXhU/v4NnaEUj8aRIyTqyHsuDlazVrZOcORVYiFC9TochJhSIzEUa2bijOSkLenQhYdv3wterXp3faOKOfryPXYRBSq6g7l9Q7Q/wb4citFzj/KE1vbfDFxhA7+yDnz18hsnGFwMQSsgcXUPTiIYRWJU8kkXq8BWPvQAgtHaDISkL2hV+Qun8+HEeuqHF3q8jWFZbdPkLK3nkAAMugURDZuiLl1y9h1X0MCuKvIyfy/wC+ENa9J0Li2rLWlvl1OFlIsCj0zYiFkNpESZTUS8uHtsKAtZeQlluktzZsBs5CxrE1SNwwCuDxYeToCZPm3VCUHAsAMGkRpClrZOcOkb0HXmwaj8KndyB1b1Pjds3ahsCsbYjmdd6d0+AZSSF28UHiTx/D6aOVUOZmIP3Id3CZtAW8V5yH1Tc+D1gZ1gYWdGcpUg9REiX1kr25BGs/aIsRP1+GUsX00obIygmOw7+FSl4IlTwfQlNrpB1eBpFl+V2WIktH8KXmUGQnAWhTKzEo83OQE/l/cBi+DEUvHkFk7QyRtQtE1i5gSgWKsxJhZOdeK23V1LSeTdHJ04bTGAjRFzonSuqtjk1s6mQ8It9IAqGpNZSFeSiIvw5p047lllO8TIeqIBcCE+taazvrzM8waz8IQnNbgCnBlMp/3lQpAZWq1tqqiQF+TpjRm26EQeovOhIl9drEbp54mJSL324k1nrdBY9LxqQKrV2gyEpC1rmtEFk3gqlfb6jkBciJ3ANj70AITK1QnJWE7HPbILRygtTjLU0dKb/OhbRpJ5j7vw0AUMkLoMhK0ryvyEmBPOUx+FJTCM21H0JeEH8DxZmJsBnwKQDAyNEbisznKIi7BkVuOsAXQGjtUuvLXVWtGlng+7DW4PF4nMVAiL5REiX13n8G++FpZj6uPcmq1XpVRfnIvrADitx0CCRmMG4WCMtuH4EnEIKplJCnxiPv7mmoCmUQmFpD6tEWll1Hap2jLM5KhrjUFbvy5Bik7JmreZ115mcAgEnLXrD9X7IESobYZEb8CLvQf4PHK+lQEprbwqr3JKQfWw2eQASbAZ+CL+LmnsKO5hL89FE7SERv5nhVQmoLjzGmnxNGhLxBXhYWY8RPl3EnMYfrUOo9EyMB9k7qhJYuFlyHQoje0TlR0iCYS0T4ZWwAmjmYcR1KvWYqFmL72ABKoKTBoCRKGgwrEyPsHB8AD1sTrkOpl0zFQuwY2x7t3WvvwilC3nSUREmDYm8mwe7xHeBmQzdAr01mYiF2jA2AvxslUNKw0DlR0iBl5BVh/C/XcONpNtehGDxzSUkCpeeDkoaIkihpsAqLlfh0700cu1s3T32pj5rYmeDnj9qhiV3lN9YnpL6iJEoaNMYYlh57iM0XHnMdisEJ8rbD2uFtYU5PZSENGCVRQgD8euUpFvx+D4XF3N7hx1BM7NYEs/v7gM+nGymQho2SKCH/E5OSi+m/3sSDpNd7XFl9ZiYW4ptBLTGoLXd3QiLkTUJJlJBSihRKfHc8Glsj40HfDG0B7tb4Pqw1XK3pymZC1CiJElKO84/S8MWBW0h5qb9HqRkKqUiAz/o1w5hAd+q+JaQMSqKEVCCvSIHVpx5h+58JUOjpcWpvum7edlj8Tks0pnG1hJSLkighr/AoJRffHL2PizHpXIdSZ1o4mWNOiA+6NrXjOhRC3miURAmponPRqVh+Ihr3XtTfC49cLKWY1dcb77Z1oUeYEVIFlEQJqaYLj9Kw6UIcImMzuA6l1jS2NsboQHeM6NgYYiE9voyQqqIkSkgN3Xmegx8vxOH43WQoDfScaaCnDcZ09kAvH3u6aIiQGqAkSshrepFdgCO3XuDQjUQ8TM7lOpxXsjQWIcTPCaMD3eFNj4Yj5LVQEiWkFkUn5+LwzUQcvvkCidkFXIejYWcmRj9fBwS3dEIHD2sIBfQAJ0JqAyVRQvQkNjUXUXEZ+OtxJv56nIEMmbzO2jYS8NGqkQXae1ijp489/BtbUXctIXpASZSQOsAYQ0xqHq7EZyI6ORfRKbmIS82rlcRqbWKERlZSeNiaoFUjS7RuZIGWLhaQiOgCIUL0jZIoIRzKK1IgIV2G1NxCvCxQILewGC8LFXhZWIzcQgV4AMRCASQivuZfYyMBnCykcLU2RiMrKUzEQq4Xg5AGi5IoIXq0fv16LF++HMnJyWjdujXWrl2LgIAArsMihNQSurqAED3Zu3cvZs6cifnz5+P69eto3bo1+vXrh9TUVK5DI4TUEjoSJURPOnTogPbt22PdunUAAJVKBVdXV0ybNg2zZ8/mODpCSG2gI1FC9EAul+Pvv/9G7969NdP4fD569+6NqKgoDiMjhNQmSqKE6EF6ejqUSiUcHBy0pjs4OCA5OZmjqAghtY2SKCGEEFJDlEQJ0QNbW1sIBAKkpKRoTU9JSYGjoyNHURFCahslUUL0wMjICP7+/jh9+rRmmkqlwunTp9GpUycOIyOE1CYapU2InsycOROjRo1Cu3btEBAQgNWrV0Mmk2HMmDFch0YIqSWURAnRk/fffx9paWn4+uuvkZycjDZt2uD48eM6FxsRQgwXjRMlhBBCaojOiRJCCCE1REmUEEIIqSFKooQQQkgNURIlhBBCaoiSKCGEEFJDlEQJIYSQGqIkSgghhNQQJVFCCCGkhiiJEkIIITVESZQQQgipIUqihBBCSA1REiWEEEJqiJIoIYQQUkOURAkhhJAa+n+UZ21TL3/Z0AAAAABJRU5ErkJggg==",
|
||
"text/plain": [
|
||
"<Figure size 200x200 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Вывод распределения количества наблюдений по меткам (классам)\n",
|
||
"print(df.stroke.value_counts())\n",
|
||
"print()\n",
|
||
"\n",
|
||
"data = df.copy()\n",
|
||
"\n",
|
||
"df_train, df_val, df_test = split_stratified_into_train_val_test(\n",
|
||
" data, stratify_colname=\"stroke\", frac_train=0.60, frac_val=0.20, frac_test=0.20\n",
|
||
")\n",
|
||
"\n",
|
||
"print(\"Обучающая выборка: \", df_train.shape)\n",
|
||
"print(df_train.stroke.value_counts())\n",
|
||
"counts = df_train['stroke'].value_counts()\n",
|
||
"plt.figure(figsize=(2, 2))# Установка размера графика\n",
|
||
"plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)# Построение круговой диаграммы\n",
|
||
"plt.title('Распределение классов stroke в обучающей выборке')# Добавление заголовка\n",
|
||
"plt.show()# Отображение графика\n",
|
||
"\n",
|
||
"print(\"Контрольная выборка: \", df_val.shape)\n",
|
||
"print(df_val.stroke.value_counts())\n",
|
||
"counts = df_val['stroke'].value_counts()\n",
|
||
"plt.figure(figsize=(2, 2))\n",
|
||
"plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
|
||
"plt.title('Распределение классов stroke в контрольной выборке')\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"print(\"Тестовая выборка: \", df_test.shape)\n",
|
||
"print(df_test.stroke.value_counts())\n",
|
||
"counts = df_test['stroke'].value_counts()\n",
|
||
"plt.figure(figsize=(2, 2))\n",
|
||
"plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
|
||
"plt.title('Распределение классов stroke в тестовой выборке')\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"#### Сбалансируем распределение:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"1. Балансировка данных оверсемплингом. Это метод, увеличивающий число наблюдений в меньшинственном классе для достижения более равномерного распределения классов."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 363,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обучающая выборка после oversampling: (5865, 17)\n",
|
||
"stroke\n",
|
||
"1 2948\n",
|
||
"0 2917\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 600x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"from imblearn.over_sampling import ADASYN\n",
|
||
"from sklearn.compose import ColumnTransformer\n",
|
||
"from sklearn.preprocessing import OneHotEncoder\n",
|
||
"\n",
|
||
"categorical_features = ['gender', 'ever_married', 'work_type', 'Residence_type'] # Ваши категориальные признаки\n",
|
||
"numeric_features = ['age', 'hypertension', 'heart_disease', 'avg_glucose_level', 'bmi'] # Ваши числовые признаки\n",
|
||
"\n",
|
||
"# Создание пайплайна для обработки категориальных данных\n",
|
||
"preprocessor = ColumnTransformer(\n",
|
||
" transformers=[\n",
|
||
" ('cat', OneHotEncoder(), categorical_features), # OneHotEncoder для категориальных данных\n",
|
||
" ('num', 'passthrough', numeric_features) # Оставляем числовые колонки без изменений\n",
|
||
" ]\n",
|
||
")\n",
|
||
"\n",
|
||
"# Создание экземпляра ADASYN\n",
|
||
"ada = ADASYN()\n",
|
||
"\n",
|
||
"# Преобразование данных с помощью пайплайна\n",
|
||
"X = preprocessor.fit_transform(df_train.drop(columns=['stroke']))\n",
|
||
"y = df_train['stroke']\n",
|
||
"\n",
|
||
"# Применение ADASYN\n",
|
||
"X_resampled, y_resampled = ada.fit_resample(X, y)\n",
|
||
"\n",
|
||
"# Создание нового DataFrame\n",
|
||
"df_train_adasyn = pd.DataFrame(X_resampled)\n",
|
||
"# Восстанавливаем названия столбцов для DataFrame\n",
|
||
"ohe_columns = preprocessor.named_transformers_['cat'].get_feature_names_out(categorical_features)\n",
|
||
"new_column_names = list(ohe_columns) + numeric_features\n",
|
||
"df_train_adasyn.columns = new_column_names\n",
|
||
"\n",
|
||
"# Добавление целевой переменной\n",
|
||
"df_train_adasyn['stroke'] = y_resampled\n",
|
||
"\n",
|
||
"# Вывод информации о новой выборке\n",
|
||
"print(\"Обучающая выборка после oversampling: \", df_train_adasyn.shape)\n",
|
||
"print(df_train_adasyn['stroke'].value_counts())\n",
|
||
"\n",
|
||
"# Визуализация\n",
|
||
"counts = df_train_adasyn['stroke'].value_counts()\n",
|
||
"plt.figure(figsize=(6, 6))\n",
|
||
"plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
|
||
"plt.title('Распределение классов Stroke в тренировочной выборке после ADASYN')\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"2. Балансировка данных андерсемплингом. Этот метод помогает сбалансировать выборку, уменьшая количество экземпляров класса большинства, чтобы привести его в соответствие с классом меньшинства."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 364,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обучающая выборка после undersampling: (298, 12)\n",
|
||
"stroke\n",
|
||
"0 149\n",
|
||
"1 149\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 200x200 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"from imblearn.under_sampling import RandomUnderSampler\n",
|
||
"\n",
|
||
"rus = RandomUnderSampler()# Создание экземпляра RandomUnderSampler\n",
|
||
"\n",
|
||
"# Применение RandomUnderSampler\n",
|
||
"X_resampled, y_resampled = rus.fit_resample(df_train.drop(columns=['stroke']), df_train['stroke'])\n",
|
||
"\n",
|
||
"# Создание нового DataFrame\n",
|
||
"df_train_undersampled = pd.DataFrame(X_resampled)\n",
|
||
"df_train_undersampled['stroke'] = y_resampled # Добавление целевой переменной\n",
|
||
"\n",
|
||
"# Вывод информации о новой выборке\n",
|
||
"print(\"Обучающая выборка после undersampling: \", df_train_undersampled.shape)\n",
|
||
"print(df_train_undersampled['stroke'].value_counts())\n",
|
||
"\n",
|
||
"# Визуализация распределения классов\n",
|
||
"counts = df_train_undersampled['stroke'].value_counts()\n",
|
||
"plt.figure(figsize=(2, 2))\n",
|
||
"plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
|
||
"plt.title('Распределение классов stroke в тренировочной выборке после Undersampling')\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 3. Датасет: Набор данных для анализа и прогнозирования сердечного приступа\n",
|
||
"https://www.kaggle.com/datasets/kamilpytlak/personal-key-indicators-of-heart-disease\n",
|
||
"##### О наборе данных: \n",
|
||
"По данным CDC, болезни сердца являются основной причиной смерти представителей большинства рас в США (афроамериканцев, американских индейцев и коренных жителей Аляски, а также белых). Около половины всех американцев (47%) имеют по крайней мере 1 из 3 основных факторов риска сердечно-сосудистых заболеваний: высокое кровяное давление, высокий уровень холестерина и курение. Другие ключевые показатели включают сахарный диабет, ожирение (высокий ИМТ), недостаточную физическую активность или чрезмерное употребление алкоголя. Выявление и профилактика факторов, оказывающих наибольшее влияние на сердечно-сосудистые заболевания, очень важны в здравоохранении. В свою очередь, достижения в области вычислительной техники позволяют применять методы машинного обучения для выявления \"закономерностей\" в данных, которые позволяют предсказать состояние пациента.\n",
|
||
"\n",
|
||
"##### Таким образом:\n",
|
||
"* Объект наблюдения - представители большинства рас в США\n",
|
||
"* Атрибуты: HeartDisease, BMI, Smoking, AlcoholDrinking, Stroke, PhysicalHealth(как много дней за месяц вы чувствовали себя плохо), MentalHealth(как много дней за месяц вы чувствовали себя ментально плохо), DiffWalking, Sex, AgeCategory, Race, Diabetic, PhysicalActivity, GenHealth, SleepTime, Asthma, KidneyDisease, SkinCancer.\n",
|
||
"* Проблемная область: прогнозирование сердечного приступа у человека."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 365,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Количество колонок: 18\n",
|
||
"Колонки: HeartDisease, BMI, Smoking, AlcoholDrinking, Stroke, PhysicalHealth, MentalHealth, DiffWalking, Sex, AgeCategory, Race, Diabetic, PhysicalActivity, GenHealth, SleepTime, Asthma, KidneyDisease, SkinCancer\n",
|
||
"\n",
|
||
"<class 'pandas.core.frame.DataFrame'>\n",
|
||
"RangeIndex: 319795 entries, 0 to 319794\n",
|
||
"Data columns (total 18 columns):\n",
|
||
" # Column Non-Null Count Dtype \n",
|
||
"--- ------ -------------- ----- \n",
|
||
" 0 HeartDisease 319795 non-null object \n",
|
||
" 1 BMI 319795 non-null float64\n",
|
||
" 2 Smoking 319795 non-null object \n",
|
||
" 3 AlcoholDrinking 319795 non-null object \n",
|
||
" 4 Stroke 319795 non-null object \n",
|
||
" 5 PhysicalHealth 319795 non-null float64\n",
|
||
" 6 MentalHealth 319795 non-null float64\n",
|
||
" 7 DiffWalking 319795 non-null object \n",
|
||
" 8 Sex 319795 non-null object \n",
|
||
" 9 AgeCategory 319795 non-null object \n",
|
||
" 10 Race 319795 non-null object \n",
|
||
" 11 Diabetic 319795 non-null object \n",
|
||
" 12 PhysicalActivity 319795 non-null object \n",
|
||
" 13 GenHealth 319795 non-null object \n",
|
||
" 14 SleepTime 319795 non-null float64\n",
|
||
" 15 Asthma 319795 non-null object \n",
|
||
" 16 KidneyDisease 319795 non-null object \n",
|
||
" 17 SkinCancer 319795 non-null object \n",
|
||
"dtypes: float64(4), object(14)\n",
|
||
"memory usage: 43.9+ MB\n"
|
||
]
|
||
},
|
||
{
|
||
"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>HeartDisease</th>\n",
|
||
" <th>BMI</th>\n",
|
||
" <th>Smoking</th>\n",
|
||
" <th>AlcoholDrinking</th>\n",
|
||
" <th>Stroke</th>\n",
|
||
" <th>PhysicalHealth</th>\n",
|
||
" <th>MentalHealth</th>\n",
|
||
" <th>DiffWalking</th>\n",
|
||
" <th>Sex</th>\n",
|
||
" <th>AgeCategory</th>\n",
|
||
" <th>Race</th>\n",
|
||
" <th>Diabetic</th>\n",
|
||
" <th>PhysicalActivity</th>\n",
|
||
" <th>GenHealth</th>\n",
|
||
" <th>SleepTime</th>\n",
|
||
" <th>Asthma</th>\n",
|
||
" <th>KidneyDisease</th>\n",
|
||
" <th>SkinCancer</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>No</td>\n",
|
||
" <td>16.60</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>3.0</td>\n",
|
||
" <td>30.0</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>Female</td>\n",
|
||
" <td>55-59</td>\n",
|
||
" <td>White</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Very good</td>\n",
|
||
" <td>5.0</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>No</td>\n",
|
||
" <td>20.34</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>Female</td>\n",
|
||
" <td>80 or older</td>\n",
|
||
" <td>White</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Very good</td>\n",
|
||
" <td>7.0</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>No</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>No</td>\n",
|
||
" <td>26.58</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>20.0</td>\n",
|
||
" <td>30.0</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>Male</td>\n",
|
||
" <td>65-69</td>\n",
|
||
" <td>White</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Fair</td>\n",
|
||
" <td>8.0</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>No</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>No</td>\n",
|
||
" <td>24.21</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>Female</td>\n",
|
||
" <td>75-79</td>\n",
|
||
" <td>White</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>Good</td>\n",
|
||
" <td>6.0</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>No</td>\n",
|
||
" <td>23.71</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>28.0</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Female</td>\n",
|
||
" <td>40-44</td>\n",
|
||
" <td>White</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>Yes</td>\n",
|
||
" <td>Very good</td>\n",
|
||
" <td>8.0</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>No</td>\n",
|
||
" <td>No</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" HeartDisease BMI Smoking AlcoholDrinking Stroke PhysicalHealth \\\n",
|
||
"0 No 16.60 Yes No No 3.0 \n",
|
||
"1 No 20.34 No No Yes 0.0 \n",
|
||
"2 No 26.58 Yes No No 20.0 \n",
|
||
"3 No 24.21 No No No 0.0 \n",
|
||
"4 No 23.71 No No No 28.0 \n",
|
||
"\n",
|
||
" MentalHealth DiffWalking Sex AgeCategory Race Diabetic \\\n",
|
||
"0 30.0 No Female 55-59 White Yes \n",
|
||
"1 0.0 No Female 80 or older White No \n",
|
||
"2 30.0 No Male 65-69 White Yes \n",
|
||
"3 0.0 No Female 75-79 White No \n",
|
||
"4 0.0 Yes Female 40-44 White No \n",
|
||
"\n",
|
||
" PhysicalActivity GenHealth SleepTime Asthma KidneyDisease SkinCancer \n",
|
||
"0 Yes Very good 5.0 Yes No Yes \n",
|
||
"1 Yes Very good 7.0 No No No \n",
|
||
"2 Yes Fair 8.0 Yes No No \n",
|
||
"3 No Good 6.0 No No Yes \n",
|
||
"4 Yes Very good 8.0 No No No "
|
||
]
|
||
},
|
||
"execution_count": 365,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"import pandas as pd\n",
|
||
"df = pd.read_csv(\".//static//csv//heart.csv\", sep=\",\")\n",
|
||
"print('Количество колонок: ' + str(df.columns.size)) \n",
|
||
"print('Колонки: ' + ', '.join(df.columns)+'\\n')\n",
|
||
"\n",
|
||
"df.info()\n",
|
||
"df.head()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"#### Получение сведений о пропущенных данных\n",
|
||
"Типы пропущенных данных:\n",
|
||
"\n",
|
||
"- None - представление пустых данных в Python\n",
|
||
"- NaN - представление пустых данных в Pandas\n",
|
||
"- '' - пустая строка"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 366,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"HeartDisease 0\n",
|
||
"BMI 0\n",
|
||
"Smoking 0\n",
|
||
"AlcoholDrinking 0\n",
|
||
"Stroke 0\n",
|
||
"PhysicalHealth 0\n",
|
||
"MentalHealth 0\n",
|
||
"DiffWalking 0\n",
|
||
"Sex 0\n",
|
||
"AgeCategory 0\n",
|
||
"Race 0\n",
|
||
"Diabetic 0\n",
|
||
"PhysicalActivity 0\n",
|
||
"GenHealth 0\n",
|
||
"SleepTime 0\n",
|
||
"Asthma 0\n",
|
||
"KidneyDisease 0\n",
|
||
"SkinCancer 0\n",
|
||
"dtype: int64\n",
|
||
"\n",
|
||
"HeartDisease False\n",
|
||
"BMI False\n",
|
||
"Smoking False\n",
|
||
"AlcoholDrinking False\n",
|
||
"Stroke False\n",
|
||
"PhysicalHealth False\n",
|
||
"MentalHealth False\n",
|
||
"DiffWalking False\n",
|
||
"Sex False\n",
|
||
"AgeCategory False\n",
|
||
"Race False\n",
|
||
"Diabetic False\n",
|
||
"PhysicalActivity False\n",
|
||
"GenHealth False\n",
|
||
"SleepTime False\n",
|
||
"Asthma False\n",
|
||
"KidneyDisease False\n",
|
||
"SkinCancer False\n",
|
||
"dtype: bool\n",
|
||
"\n",
|
||
"HeartDisease процент пустых значений: %0.00\n",
|
||
"BMI процент пустых значений: %0.00\n",
|
||
"Smoking процент пустых значений: %0.00\n",
|
||
"AlcoholDrinking процент пустых значений: %0.00\n",
|
||
"Stroke процент пустых значений: %0.00\n",
|
||
"PhysicalHealth процент пустых значений: %0.00\n",
|
||
"MentalHealth процент пустых значений: %0.00\n",
|
||
"DiffWalking процент пустых значений: %0.00\n",
|
||
"Sex процент пустых значений: %0.00\n",
|
||
"AgeCategory процент пустых значений: %0.00\n",
|
||
"Race процент пустых значений: %0.00\n",
|
||
"Diabetic процент пустых значений: %0.00\n",
|
||
"PhysicalActivity процент пустых значений: %0.00\n",
|
||
"GenHealth процент пустых значений: %0.00\n",
|
||
"SleepTime процент пустых значений: %0.00\n",
|
||
"Asthma процент пустых значений: %0.00\n",
|
||
"KidneyDisease процент пустых значений: %0.00\n",
|
||
"SkinCancer процент пустых значений: %0.00\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Количество пустых значений признаков\n",
|
||
"print(df.isnull().sum())\n",
|
||
"print()\n",
|
||
"\n",
|
||
"# Есть ли пустые значения признаков\n",
|
||
"print(df.isnull().any())\n",
|
||
"print()\n",
|
||
"\n",
|
||
"# Процент пустых значений признаков\n",
|
||
"for i in df.columns:\n",
|
||
" null_rate = df[i].isnull().sum() / len(df) * 100\n",
|
||
" print(f\"{i} процент пустых значений: %{null_rate:.2f}\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"##### Пропущенные данные отсутствуют.\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"##### Проверим выбросы и усредним их:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 367,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Колонка BMI:\n",
|
||
" Есть выбросы: Да\n",
|
||
" Количество выбросов: 10396\n",
|
||
" Минимальное значение: 12.02\n",
|
||
" Максимальное значение: 94.85\n",
|
||
" 1-й квартиль (Q1): 24.03\n",
|
||
" 3-й квартиль (Q3): 31.42\n",
|
||
"\n",
|
||
"Колонка PhysicalHealth:\n",
|
||
" Есть выбросы: Да\n",
|
||
" Количество выбросов: 47146\n",
|
||
" Минимальное значение: 0.0\n",
|
||
" Максимальное значение: 30.0\n",
|
||
" 1-й квартиль (Q1): 0.0\n",
|
||
" 3-й квартиль (Q3): 2.0\n",
|
||
"\n",
|
||
"Колонка MentalHealth:\n",
|
||
" Есть выбросы: Да\n",
|
||
" Количество выбросов: 51576\n",
|
||
" Минимальное значение: 0.0\n",
|
||
" Максимальное значение: 30.0\n",
|
||
" 1-й квартиль (Q1): 0.0\n",
|
||
" 3-й квартиль (Q3): 3.0\n",
|
||
"\n",
|
||
"Колонка SleepTime:\n",
|
||
" Есть выбросы: Да\n",
|
||
" Количество выбросов: 4543\n",
|
||
" Минимальное значение: 1.0\n",
|
||
" Максимальное значение: 24.0\n",
|
||
" 1-й квартиль (Q1): 6.0\n",
|
||
" 3-й квартиль (Q3): 8.0\n",
|
||
"\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"numeric_columns = ['BMI', 'PhysicalHealth', 'MentalHealth', 'AgeCategory', 'SleepTime']\n",
|
||
"for column in numeric_columns:\n",
|
||
" if pd.api.types.is_numeric_dtype(df[column]): # Проверяем, является ли колонка числовой\n",
|
||
" q1 = df[column].quantile(0.25) # Находим 1-й квартиль (Q1)\n",
|
||
" q3 = df[column].quantile(0.75) # Находим 3-й квартиль (Q3)\n",
|
||
" iqr = q3 - q1 # Вычисляем межквартильный размах (IQR)\n",
|
||
"\n",
|
||
" # Определяем границы для выбросов\n",
|
||
" lower_bound = q1 - 1.5 * iqr # Нижняя граница\n",
|
||
" upper_bound = q3 + 1.5 * iqr # Верхняя граница\n",
|
||
"\n",
|
||
" # Подсчитываем количество выбросов\n",
|
||
" outliers = df[(df[column] < lower_bound) | (df[column] > upper_bound)]\n",
|
||
" outlier_count = outliers.shape[0]\n",
|
||
"\n",
|
||
" print(f\"Колонка {column}:\")\n",
|
||
" print(f\" Есть выбросы: {'Да' if outlier_count > 0 else 'Нет'}\")\n",
|
||
" print(f\" Количество выбросов: {outlier_count}\")\n",
|
||
" print(f\" Минимальное значение: {df[column].min()}\")\n",
|
||
" print(f\" Максимальное значение: {df[column].max()}\")\n",
|
||
" print(f\" 1-й квартиль (Q1): {q1}\")\n",
|
||
" print(f\" 3-й квартиль (Q3): {q3}\\n\")\n",
|
||
"\n",
|
||
" # Устраняем выбросы: заменяем значения ниже нижней границы на саму нижнюю границу, а выше верхней — на верхнюю\n",
|
||
" df[column] = df[column].apply(lambda x: lower_bound if x < lower_bound else upper_bound if x > upper_bound else x)\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"#### Постараемся выявить зависимости HeartDisease от остальных колонок:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"#### Разобьем наш набор на выборки относительно параметра HeartDisease:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 368,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 400x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 400x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 400x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 400x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 400x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import matplotlib.pyplot as plt\n",
|
||
"# Создание диаграмм зависимости\n",
|
||
"for column in numeric_columns:\n",
|
||
" plt.figure(figsize=(4, 6)) # Установка размера графика\n",
|
||
" if pd.api.types.is_numeric_dtype(df[column]): # Проверяем, является ли колонка числовой\n",
|
||
" # Проверяем, содержит ли колонка только два уникальных значения (0 и 1)\n",
|
||
" if df[column].nunique() == 2 and set(df[column].unique()).issubset({0, 1}):\n",
|
||
" counts = df[column].value_counts() \n",
|
||
" counts.plot(kind='bar', width=0.4) # Создаем столбчатую диаграмму\n",
|
||
" plt.title(f'Количество значений для {column}')\n",
|
||
" plt.xlabel(column)\n",
|
||
" plt.ylabel('Количество повторений')\n",
|
||
" else:\n",
|
||
" grouped_data = df.groupby('HeartDisease')[column].mean()\n",
|
||
"\n",
|
||
" # Создаем столбчатую диаграмму\n",
|
||
" plt.bar(grouped_data.index, grouped_data.values, alpha=0.5, width=0.4)\n",
|
||
" plt.title(f'Среднее значение {column} по HeartDisease')\n",
|
||
" plt.xlabel('HeartDisease (0 = нет, 1 = да)')\n",
|
||
" plt.ylabel(f'Среднее значение {column}')\n",
|
||
" plt.xticks([0, 1]) # Установка меток по оси X\n",
|
||
" plt.grid(axis='y')\n",
|
||
" else:\n",
|
||
" # Если колонка не числовая, строим столбчатую диаграмму\n",
|
||
" counts = df[column].value_counts() # Считаем количество повторений каждого значения\n",
|
||
" counts.plot(kind='bar', width=0.4) # Создаем столбчатую диаграмму\n",
|
||
" plt.title(f'Количество значений для {column}')\n",
|
||
" plt.xlabel(column)\n",
|
||
" plt.ylabel('Количество повторений')\n",
|
||
"\n",
|
||
" plt.show() "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 369,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Функция для создания выборок\n",
|
||
"from sklearn.model_selection import train_test_split\n",
|
||
"\n",
|
||
"def split_stratified_into_train_val_test(\n",
|
||
" df_input,\n",
|
||
" stratify_colname=\"y\",\n",
|
||
" frac_train=0.6,\n",
|
||
" frac_val=0.15,\n",
|
||
" frac_test=0.25,\n",
|
||
" random_state=None,\n",
|
||
"):\n",
|
||
"\n",
|
||
" if frac_train + frac_val + frac_test != 1.0:\n",
|
||
" raise ValueError(\n",
|
||
" \"fractions %f, %f, %f do not add up to 1.0\"\n",
|
||
" % (frac_train, frac_val, frac_test)\n",
|
||
" )\n",
|
||
"\n",
|
||
" if stratify_colname not in df_input.columns:\n",
|
||
" raise ValueError(\"%s is not a column in the dataframe\" % (stratify_colname))\n",
|
||
"\n",
|
||
" X = df_input # Contains all columns.\n",
|
||
" y = df_input[\n",
|
||
" [stratify_colname]\n",
|
||
" ] # Dataframe of just the column on which to stratify.\n",
|
||
"\n",
|
||
" # Split original dataframe into train and temp dataframes.\n",
|
||
" df_train, df_temp, y_train, y_temp = train_test_split(\n",
|
||
" X, y, stratify=y, test_size=(1.0 - frac_train), random_state=random_state\n",
|
||
" )\n",
|
||
"\n",
|
||
" # Split the temp dataframe into val and test dataframes.\n",
|
||
" relative_frac_test = frac_test / (frac_val + frac_test)\n",
|
||
" df_val, df_test, y_val, y_test = train_test_split(\n",
|
||
" df_temp,\n",
|
||
" y_temp,\n",
|
||
" stratify=y_temp,\n",
|
||
" test_size=relative_frac_test,\n",
|
||
" random_state=random_state,\n",
|
||
" )\n",
|
||
"\n",
|
||
" assert len(df_input) == len(df_train) + len(df_val) + len(df_test)\n",
|
||
"\n",
|
||
" return df_train, df_val, df_test"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 370,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"HeartDisease\n",
|
||
"No 292422\n",
|
||
"Yes 27373\n",
|
||
"Name: count, dtype: int64\n",
|
||
"\n",
|
||
"Обучающая выборка: (191877, 18)\n",
|
||
"HeartDisease\n",
|
||
"No 175453\n",
|
||
"Yes 16424\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 200x200 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Контрольная выборка: (63959, 18)\n",
|
||
"HeartDisease\n",
|
||
"No 58485\n",
|
||
"Yes 5474\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 200x200 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Тестовая выборка: (63959, 18)\n",
|
||
"HeartDisease\n",
|
||
"No 58484\n",
|
||
"Yes 5475\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 200x200 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Вывод распределения количества наблюдений по меткам (классам)\n",
|
||
"print(df.HeartDisease.value_counts())\n",
|
||
"print()\n",
|
||
"\n",
|
||
"data = df.copy()\n",
|
||
"\n",
|
||
"df_train, df_val, df_test = split_stratified_into_train_val_test(\n",
|
||
" data, stratify_colname=\"HeartDisease\", frac_train=0.60, frac_val=0.20, frac_test=0.20\n",
|
||
")\n",
|
||
"\n",
|
||
"print(\"Обучающая выборка: \", df_train.shape)\n",
|
||
"print(df_train.HeartDisease.value_counts())\n",
|
||
"counts = df_train['HeartDisease'].value_counts()\n",
|
||
"plt.figure(figsize=(2, 2))# Установка размера графика\n",
|
||
"plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)# Построение круговой диаграммы\n",
|
||
"plt.title('Распределение классов HeartDisease в обучающей выборке')# Добавление заголовка\n",
|
||
"plt.show()# Отображение графика\n",
|
||
"\n",
|
||
"print(\"Контрольная выборка: \", df_val.shape)\n",
|
||
"print(df_val.HeartDisease.value_counts())\n",
|
||
"counts = df_val['HeartDisease'].value_counts()\n",
|
||
"plt.figure(figsize=(2, 2))\n",
|
||
"plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
|
||
"plt.title('Распределение классов HeartDisease в контрольной выборке')\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"print(\"Тестовая выборка: \", df_test.shape)\n",
|
||
"print(df_test.HeartDisease.value_counts())\n",
|
||
"counts = df_test['HeartDisease'].value_counts()\n",
|
||
"plt.figure(figsize=(2, 2))\n",
|
||
"plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
|
||
"plt.title('Распределение классов HeartDisease в тестовой выборке')\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"#### Сбалансируем распределение:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"1. Балансировка данных оверсемплингом. Это метод, увеличивающий число наблюдений в меньшинственном классе для достижения более равномерного распределения классов."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 371,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обучающая выборка после oversampling: (352020, 51)\n",
|
||
"HeartDisease\n",
|
||
"Yes 176567\n",
|
||
"No 175453\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAsYAAAH4CAYAAABJ8Cv1AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAABgyUlEQVR4nO3dd3hT5cPG8TvppotZNqVsZItsGSqiDFEQcLMcOBBxvCouloqIqCgi4E8QEUUQBcXBEFBAhmwZskE2FCjdKznvH7WR0BY6OT3p93NdvZQ0PbmTJk/uPnnOOTbDMAwBAAAARZzd7AAAAABAYUAxBgAAAEQxBgAAACRRjAEAAABJFGMAAABAEsUYAAAAkEQxBgAAACRRjAEAAABJFGMAAJBNqampOn36tP755x+zowAFgmIM4Kr67LPPZLPZdOjQIbOjAIXGwoULtWXLFte/58+frx07dpgX6CJ79+7Vww8/rPLly8vX11dly5ZVq1atxIlz4YlyVIzT39DSv/z9/VWrVi0NHjxYp06dKqiMgMcbMWKEbDabIiMjM/1+1apV1a1bt6uc6j+TJk3SZ599luHyFStWuI0Jfn5+Klu2rDp06KA333xTZ86cufphAQv666+/9NRTT2nv3r1au3atHn30UcXExJgdS2vXrlXz5s21bNkyvfjii1q0aJGWLFmi+fPny2azmR0POTBp0iTZbDa1aNEiy+tcPJ57e3urZMmSatq0qZ566int3Lkzz9uPjY3V8OHDVb9+fQUGBqpUqVJq3LixnnrqKR0/flwpKSlq0KCBqlevroSEhAw/f+jQIRUrVky9e/eW9F8v9ff317FjxzJcv0OHDqpfv/5lc1/KO0fX/teoUaMUERGhxMRErVq1Sh9//LF++uknbd++XcWKFcvNJgEUYpMmTVLp0qXVv3//TL8/ZMgQNWvWTA6HQ2fOnNEff/yh4cOH691339WcOXN04403uq77wAMP6O6775afn99VSg8Ufg899JCmTZumWrVqSZJ69uypli1bmpopOTlZAwYMUK1atbR48WKFhoaamgd5M2vWLFWtWlXr16/Xvn37VKNGjUyvd/PNN6tv374yDEMXLlzQ1q1bNWPGDE2aNEljx47VM888k6vtp6SkqF27dvr777/Vr18/Pfnkk4qNjdWOHTv05ZdfqkePHqpQoYKmTp2qNm3aaPTo0XrzzTfdtjF48GD5+vrqgw8+cLs8KSlJb731lj788MM8PEL/MnJg+vTphiTjzz//dLv8mWeeMSQZX375ZU42B+Bfw4cPNyQZZ86cyfT74eHhRteuXa9yKsOIi4szDMMw6tWrZ7Rv3z7D95cvX25IMubOnZvhe1u2bDHCwsKM4sWLG8ePHy/oqIDlJSYmGhs2bDB27txpdhTDMAzjm2++MWw2m7F7926zoyCPDhw4YEgyvv32W6NMmTLGiBEjMr2eJOOJJ57IcHlkZKTRqlUrQ5Lx448/5mr7c+bMMSQZs2bNyvC9hIQE48KFC65/P/bYY4aPj4+xfft212XffPONIcmYNGmS67L0Xtq4cWPDz8/POHbsmNt227dvb9SrVy/T+5qVfFljnD4bdPDgQUnSuXPn9Nxzz6lBgwYKCgpSSEiIOnfurK1bt2b42cTERI0YMUK1atWSv7+/ypcvr549e2r//v2S0qbNL57av/SrQ4cOrm2lf6z79ddf66WXXlK5cuUUGBio7t2768iRIxlue926dbr11lsVGhqqYsWKqX379lq9enWm97FDhw6Z3v6IESMyXPeLL75Q06ZNFRAQoJIlS+ruu+/O9PYvd98u5nQ69f7776tevXry9/dX2bJlNWjQIJ0/f97tell93D548OAM28ws+7hx4zI8plLaX2LDhw9XjRo15Ofnp8qVK+v5559XUlJSpo/VxTp06JBhe2+88Ybsdru+/PLLXD0e77zzjlq3bq1SpUopICBATZs21TfffJPp7X/xxRdq3ry5ihUrphIlSqhdu3ZavHix23V+/vlntW/fXsHBwQoJCVGzZs0yZJs7d67rd1q6dGndf//9GT626d+/v1vmEiVKqEOHDlq5cuUVH6fcyO7zYsGCBeratasqVKggPz8/Va9eXaNHj5bD4XC7XvpHThs3blS7du1UrFgxvfTSS6patap27Nih3377LdPXXVYaNWqk999/X1FRUZo4caLr8szWGG/YsEG33HKLSpcurYCAAEVERGjgwIEFen/37t2rO++8U+XKlZO/v78qVaqku+++WxcuXHC7XnZfz5dKXx6T/hUcHKzmzZtr/vz5Ofq5zL5WrFghyf131rp1a9djN3ny5Azbze7r2GazafDgwRl+vlu3bqpatarr3+mv10uX2DzxxBOy2Wxuny6k/85///13DRo0SKVKlVJISIj69u2b4fcnpX1CUa9ePfn5+alChQp64oknFBUV5XadS8fk0qVLq2vXrtq+fbvb9VJTUzV69GhVr15dfn5+qlq1ql566SW3+53VfUn/XeTm8ZGkuLg4Pfvss6pcubL8/PxUu3ZtvfPOOxnW5qaPx35+fmratKnq1q2b5XicmYsfBy8vL1WsWFGPPPKI22OW/v6Y1VgppY1hF9+HtWvXKiIiQvPmzVP16tXl6+urKlWq6Pnnn8/0Y+7s/t6y85xNz5v+XJek48ePq2rVqrruuusUGxvrujyv71GXe61dui9Edu6jlNYvunTpohIlSigwMFANGzbUhAkTMlwvu7eb23Eo3axZs1SiRAl17dpVvXr10qxZs7L9s5JUqlQpzZ49W97e3nrjjTdytf30XtemTZsM3/P391dISIjr32PGjFHp0qX16KOPyjAMxcbGaujQoWrVqpUeffTRDD//0ksvyeFw6K233srR/cpMrpZSXCr9zpYqVUqSdODAAc2fP1+9e/dWRESETp06pSlTpqh9+/bauXOnKlSoIElyOBzq1q2bfv31V91999166qmnFBMToyVLlmj79u2qXr266zbuuecedenSxe12hw0blmmeN954QzabTS+88IJOnz6t999/Xx07dtSWLVsUEBAgSVq2bJk6d+6spk2bavjw4bLb7Zo+fbpuvPFGrVy5Us2bN8+w3UqVKmnMmDGS0tbJPPbYY5ne9quvvqo+ffrooYce0pkzZ/Thhx+qXbt22rx5s4oXL57hZx555BG1bdtWkvTtt9/qu+++c/v+oEGD9Nlnn2nAgAEaMmSIDh48qIkTJ2rz5s1avXq1fHx8Mn0cciIqKsp13y7mdDrVvXt3rVq1So888ojq1q2rv/76S++995727NlzxTf5S02fPl2vvPKKxo8fr3vvvTfT61zp8ZgwYYK6d++u++67T8nJyZo9e7Z69+6thQsXqmvXrq7rjRw5UiNGjFDr1q01atQo+fr6at26dVq2bJk6deokKe0Ne+DAgapXr56GDRum4sWLa/Pmzfrll19c+dIf+2bNmmnMmDE6deqUJkyYoNWrV2f4nZYuXVrvvfeeJOno0aOaMGGCunTpoiNHjmT6u7/UuXPnMr3c6XRmuCy7z4vPPvtMQUFBeuaZZxQUFKRly5bptddeU3R0tMaNG+e2zbNnz6pz5866++67df/997vWCz/55JMKCgrSyy+/LEkqW7bsFe+LJPXq1UsPPvigFi9enOlgKkmnT59Wp06dVKZMGb344osqXry4Dh06pG+//bbA7m9ycrJuueUWJSUl6cknn1S5cuV07NgxLVy4UFFRUa6PjHPzer7UzJkzJUmRkZGaNGmSevfure3bt6t27dqZXr9nz55uH0E+/fTTqlu3rh555BHXZXXr1nX9//nz59WlSxf16dNH99xzj+bMmaPHHntMvr6+rj8u8vt1nJV9+/bpk08+yfL7gwcPVvHixTVixAjt3r1bH3/8sQ4fPuwqQVJaGR05cqQ6duyoxx57zHW9P//8M8N4V6dOHb388ssyDEP79+/Xu+++qy5durgdMeGhhx7SjBkz1KtXLz377LNat26dxowZo127dmUYW/KTYRjq3r27li9frgcffFCNGzfWokWL9H//9386duyYa5zITFbj8eX06NFDPXv2VGpqqtasWaOpU6cqISHB9fzLjbNnz+rAgQN66aWX1LNnTz377LPasGGDxo0bp+3bt+vHH3/M1e8tO8/ZS124cEGdO3eWj4+PfvrpJwUFBUnKn+f2xe/t6X766Sd99dVXbpdl9z4uWbJE3bp1U/ny5fXUU0+pXLly2rVrlxYuXKinnnoqw+2n/+4kaeXKlZo6darb9/NjHJo1a5Z69uwpX19f3XPPPa7czZo1u+LPpqtSpYrat2+v5cuXKzo62q3IZmf74eHhkqTPP/9cr7zyymXXqIeGhuqDDz5Q79699b///U87d+7UqVOn9PPPP2f6cxEREerbt68++eQTvfjii66emSs5mV5On7JeunSpcebMGePIkSPG7NmzjVKlShkBAQHG0aNHDcNI+zjI4XC4/ezBgwcNPz8/Y9SoUa7Lpk2bZkgy3n333Qy35XQ6XT8nyRg3blyG61z68W76x7oVK1Y0oqOjXZenT99PmDDBte2aNWsat9xyi+t2DMMw4uPjjYiICOPmm2/OcFutW7c26tev7/r3mTNnDEnG8OHDXZcdOnTI8PLyMt544w23n/3rr78Mb2/vDJfv3bvXkGTMmDHDdVn6R+rpVq5cmelHD7/88kuGy7P6uP2JJ54wLv1VX5r9+eefN8LCwoymTZu6PaYzZ8407Ha7sXLlSrefnzx5siHJWL16dYbbu1j79u1d2/vxxx8Nb29v49lnn830utl5PAwj7fd0seTkZKN+/frGjTfe6LYtu91u9OjRI8NzMf13HhUVZQQHBxstWrQwEhISMr1OcnKyERYWZtSvX9/tOgsXLjQkGa+99prrsn79+hnh4eFu25k6daohyVi/fn2m9/nS+3m5r4t/tzl5Xlz6eBmGYQwaNMgoVqyYkZiY6Lqsffv2hiRj8uTJGa6fm6UU6Ro1amSUKFHC9e/0ceTgwYOGYRjGd999l+kSrYvl9/3dvHnzFXPn9PV8qcyeu4sXLzYkGXPmzLnsz14sPDzc6NevX6bfS/+djR8/3nVZUlKS0bhxYyMsLMxITk42DCNnr2Nl8VFq165d3Z7f6WPz9OnTXZf16dPHqF+/vlG5cmW3zOm/86ZNm7oyGYZhvP3224YkY8GCBYZhGMbp06cNX19fo1OnTm6v24kTJxqSjGnTprnd90ufky+99JIhyTh9+rRhGGnLeSQZDz30kNv1nnvuOUOSsWzZMsMwDOPw4cMZtm8Ymf8Os/v4zJ8/35BkvP76627X69Wrl2Gz2Yx9+/a5bTM743FWLv15w0h7z7rmmmtc/87Oa/XSMaxfv36GJKN///5u10t/XH744QfDMHL+e8vOczY97/Lly43ExESjQ4cORlhYmNvjZhj58x6V2Uft48aNcxunsnsfU1NTjYiICCM8PNw4f/682zYv7huGYRgpKSmGJGPkyJGuyy4dH/M6DhmGYWzYsMGQZCxZssSVo1KlSsZTTz2V4bpZPb/TPfXUU4YkY+vWrTnefnx8vFG7dm1DkhEeHm7079/f+PTTT41Tp05leXvdunUzQkNDDS8vL2PYsGEZvn/xEt/9+/cb3t7expAhQ1zfv2pLKTp27KgyZcqocuXKuvvuuxUUFKTvvvtOFStWlCT5+fnJbk/btMPh0NmzZxUUFKTatWtr06ZNru3MmzdPpUuX1pNPPpnhNvKyt2vfvn0VHBzs+nevXr1Uvnx5/fTTT5KkLVu2aO/evbr33nt19uxZRUZGKjIyUnFxcbrpppv0+++/Z5ihS0xMlL+//2Vv99tvv5XT6VSfPn1c24yMjFS5cuVUs2ZNLV++3O36ycnJknTZnZDmzp2r0NBQ3XzzzW7bbNq0qYKCgjJsMyUlxe16kZGRSkxMvGzuY8eO6cMPP9Srr77q+iv84tuvW7eu6tSp47bN9OUzl95+VtavX68+ffrozjvvzDBLmS47j4ck16y/lDbzcOHCBbVt29btuTV//nw5nU699tprrudiuvTn1pIlSxQTE6MXX3wxw+82/TobNmzQ6dOn9fjjj7tdp2vXrqpTp45+/PFHt59zOp2ux2jLli36/PPPVb58ebcZvsuZN2+elixZkuHr0hnanDwvLn68YmJiFBkZqbZt2yo+Pl5///2323b9/Pw0YMCAbGXNrqCgoMvuXZ8+27Fw4UKlpKRkep38vr/pM8KLFi1SfHx8preZ09dzVtJ/bteuXZo8ebICAwPzdacqb29vDRo0yPVvX19fDRo0SKdPn9bGjRsl5fx1nJiYmGEcyep3k27jxo2aO3euxowZk+E1l+6RRx5xmzl87LHH5O3t7Rqbly5dquTkZA0dOtRtGw8//LBCQkIyvN7Sx7szZ85ozZo1+u6779SwYUOVLl1aklzbvXRnoWeffVaSXNsrU6aMpLRPebIjO4/PTz/9JC8vLw0ZMiTDbRuGoZ9//jnTbV9uPL6c+Ph4RUZG6uTJk5o3b562bt2qm266KcP10l8TmX38n5X/+7//c/v3008/LS8vL9fjl9PfW3aes+mcTqf69u2rtWvX6qeffnL7JFnKv/eoK8nufdy8ebMOHjyooUOHZpjJvbTXZOc9Lz/GoVmzZqls2bK64YYbXDnuuusuzZ49O8MSsytJf05ePKZnd/sBAQFat26d6/n02Wef6cEHH1T58uX15JNPZrr05aOPPlJycrIqV66sV1999bLZqlWrpgceeEBTp07ViRMncnS/LparpRQfffSRatWqJW9vb5UtW1a1a9d2e6I4nU5NmDBBkyZN0sGDB90emPTlFlLaEozatWvL2ztfVnS41KxZ0+3fNptNNWrUcK3Z2bt3rySpX79+WW7jwoULKlGihOvfkZGRGbZ7qb1798owjCyvd+mSh/SB6XKD3969e3XhwgWFhYVl+v3Tp0+7/Xvx4sWuQT67hg8frgoVKmjQoEEZ1p/t3btXu3btynKbl95+Zo4dO6auXbsqLi5OZ8+ezfKPnuw8HlJagXr99de1ZcsWtxfSxdvdv3+/7Ha7rrnmmiy3k74E6HKHcjl8+LAkZfqxd506dbRq1Sq3y44cOeL2WJUvX17z5s3L9htcu3btXG/qF7u0uOfkebFjxw698sorWrZsmaKjo92ud+l62ooVK8rX1zdbWbMrNjbW7Q/VS7Vv31533nmnRo4cqffee08dOnTQHXfcoXvvvdf1hpHf9zciIkLPPPOM3n33Xc2aNUtt27ZV9+7ddf/997tKc05fz1m5+PkQEhKiWbNmqXLlytn62eyoUKGCAgMD3S5LP7LBoUOH1LJlyxy/jj/99FN9+umnGa6X/lFoZl588UW1bdtW3bp1y3QNrpRxbA4KClL58uVdY3NWrzdfX19Vq1bN9f10f/zxh9t9qlmzptthxA4fPiy73Z5h7/hy5cqpePHiru0FBASoSZMmmjp1qjp27OjKmdUfTdl5fA4fPqwKFSpkeO6n/5F86X1Jd7nx+HLGjRvnNulw6623auzYsRmud/FShaCgIN1222167733Ml0eZbPZZLfbM/zeQkND8/R7y85zNt3LL7+stWvXymazZfr7yI/3qOzI7n3MzvtKuux2gLyMQw6HQ7Nnz9YNN9zg2g9Mklq0aKHx48fr119/dS0tzI70td3pz+ucbj80NFRvv/223n77bR0+fFi//vqr3nnnHU2cOFGhoaF6/fXX3W6vSpUqCgsLU7169dwmPbLyyiuvaObMmXrrrbcyXdOdHblqpM2bN9d1112X5ffffPNNvfrqqxo4cKBGjx6tkiVLym63a+jQoZmulbza0jOMGzdOjRs3zvQ6Fz9Rk5OTdeLECd18881X3K7NZtPPP/8sLy+vy25Tkk6ePCkpbZC+3DbDwsKyXCh/6WDQokWLDE+siRMnasGCBZn+/K5du/TZZ5/piy++yPQF5nQ61aBBA7377ruZ/nx23uD37duna6+9Vu+9954eeOABzZgxI9M/SrLzeKxcuVLdu3dXu3btNGnSJJUvX14+Pj6aPn16hh3mzFC2bFl98cUXktJK2LRp03Trrbdq1apVatCgQb7dTnafF1FRUWrfvr1CQkI0atQoVa9eXf7+/tq0aZNeeOGFDK/H7Aw8OZGSkqI9e/Zc9k0ifYegtWvX6ocfftCiRYs0cOBAjR8/XmvXrlVQUFCB3N/x48erf//+WrBggRYvXqwhQ4ZozJgxWrt2rSpVqpTj13NWlixZIiltR6x58+apT58+Wrhw4RXHk/yU09fx7bffnqHcvvLKK67X6KUWL16spUuXas2aNfkTOJsaNmyo8ePHS5LOnDmjDz74QB06dNCmTZvcxpHsfAI5efJk3X777WrduvUVr5vTxye7rjQeX84DDzygvn37yul06sCBAxo9erS6deumpUuXut3/1157TW3btlVKSoo2btyoUaNGKSoqyjW7frH08cDM4xWvW7dOn332mSZOnKhHHnlEW7ZscZthzY/3KLNktwPkZRxatmyZTpw4odmzZ2v27NkZvj9r1qwcFePt27fLy8tLERERed5+eHi4Bg4cqB49eqhatWqaNWtWhv6SU9WqVdP999+vqVOn6sUXX8zVNvJ3qvZf33zzjW644YYMf1FHRUW5zYZVr15d69atU0pKSr7sQJYufUY4nWEY2rdvnxo2bOi6XSlt9qZjx45X3N7WrVuVkpJy2T8G0rdrGIYiIiJcf/1ezs6dO2Wz2bLcCSd9m0uXLlWbNm2yVVpKly6d4T5dbueDYcOGqXHjxrrrrruyvP30j+RyOzimL2MpW7asFixYoGeffVZdunTJUOqz83jMmzdP/v7+WrRokdvgOH369Ay5nU6ndu7cmeUfP+nPg+3bt2d5PMf0GaDdu3e7HYs3/bJLZ9D8/f3dHv/u3burZMmSmjhxoqZMmZLl/cqp7D4vVqxYobNnz+rbb79Vu3btXJdf/Jd9duT2d//NN98oISFBt9xyyxWv27JlS7Vs2VJvvPGGvvzyS913332aPXu2HnrooQK7vw0aNFCDBg30yiuv6I8//lCbNm00efJkvf766zl+PWfl4ufD7bffrnXr1umdd97Jt2J8/PhxxcXFuc3A7dmzR5JcRxjI6eu4UqVKGcaR999/P9PiZxiGXnzxRfXo0eOKS0T27t3r+rhVSpt9OnHihGvH6otfb9WqVXNdLzk5WQcPHsyQqUSJEm6XdejQQRUqVND06dM1bNgwhYeHy+l0au/evW7LmU6dOqWoqCi312/z5s114MABbdu2zfUx8eeff57pzmvZeXzCw8O1dOlSxcTEuM0apy/nyWz2/Urj8eVUq1bNLVNoaKjuvfderV27Vq1atXJd3qBBA9f1OnfurH/++UczZsxQampqhm1GRERk+vhFR0frxIkTrqMg5fT3lp3nbLqRI0eqX79+aty4sa677jq9/vrrGj16tOv7+fEelR3ZvY8Xv69cqV+knzDjckvt8joOzZo1S2FhYfroo48yfC995/bJkydnq1/8888/+u2339SqVSvXczo/tl+iRAlVr149wxFlcuuVV17RF198keknJtlRIKeE9vLyynA4mrlz52Y4vNWdd96pyMhIt0M5pbv053Pi888/d1v/8s033+jEiRPq3LmzJKlp06aqXr263nnnHbdDvqS79Gxdc+fOlZeX1xXPPNazZ095eXlp5MiRGfIbhqGzZ8+6/p2amqp58+apefPml/2Lr0+fPnI4HG4DwcXbyMk6sUutWbNGCxYs0FtvvZXlgNKnTx8dO3Ys0z3NExISFBcXd8XbqVWrlutjug8//FBOpzPDnrnZfTy8vLxks9ncluccOnQoQ/m/4447ZLfbNWrUqAyzoum/m06dOik4OFhjxozJsA47/TrXXXedwsLCNHnyZLdlGz///LN27drldhSMzCQnJys1NTVbhw3Kiew+L9JnGC5+PiYnJ2vSpEk5ur3AwMAcP9e2bt2qoUOHqkSJEnriiSeyvN758+czvF7S/5hJf9zy+/5GR0dnKAINGjSQ3W533WZOXs/Z5XA4lJycnK/Ph9TUVLc/upKTkzVlyhSVKVNGTZs2lZQ/r+OszJ49W9u2bcvWURSmTp3qthb3448/Vmpqqmts7tixo+vg/Rc/5p9++qkuXLhwxddb+iHE0h/f9ML9/vvvu10vfXbx0u0FBASoRYsW6tixozp27OhWgHKqS5cucjgcGd7f3nvvPdlsNtd9Tped8TgnLn0ssuJ0OmW32zO9zawevwkTJriOKiXl/PeWnedsuvQjFDVq1EjPPfecxo4d61agCvK5fbHs3sdrr71WERERrkNVXuzSceTrr7++4j4oeRmHEhIS9O2336pbt27q1atXhq/BgwcrJiZG33///RXv/7lz53TPPffI4XC4jk6U0+1v3bo107O7Hj58WDt37rzspFhOVK9eXffff7+mTJmSq09xCmTGuFu3bho1apQGDBig1q1b66+//tKsWbMyDDJ9+/bV559/rmeeeUbr169X27ZtFRcXp6VLl+rxxx/X7bffnqvbL1mypK6//noNGDBAp06d0vvvv68aNWro4YcfliTZ7Xb973//U+fOnVWvXj0NGDBAFStW1LFjx7R8+XKFhITohx9+UFxcnD766CN98MEHqlWrltvxFNML9bZt27RmzRq1atVK1atX1+uvv65hw4bp0KFDuuOOOxQcHKyDBw/qu+++0yOPPKLnnntOS5cu1auvvqpt27bphx9+uOx9ad++vQYNGqQxY8Zoy5Yt6tSpk3x8fLR3717NnTtXEyZMUK9evXL1OC1evFg333zzZf+qfeCBBzRnzhw9+uijWr58udq0aSOHw6G///5bc+bM0aJFi644k36xcuXKady4cXrooYd0//33q0uXLjl6PLp27ap3331Xt956q+69916dPn1aH330kWrUqKFt27a5rlejRg29/PLLGj16tNq2bauePXvKz89Pf/75pypUqKAxY8YoJCRE7733nh566CE1a9ZM9957r0qUKKGtW7cqPj5eM2bMkI+Pj8aOHasBAwaoffv2uueee1yHa6tataqefvppt3xxcXFuSylmzpypxMRE9ejRI9uPUXZk93nRunVrlShRQv369dOQIUNks9k0c+bMHP/h2bRpU3388cd6/fXXVaNGDYWFhbnNoK9cuVKJiYmunW1Xr16t77//XqGhofruu+8u+1Fh+hmVevTooerVqysmJkaffPKJQkJCXG/M+X1/ly1bpsGDB6t3796qVauWUlNTNXPmTHl5eenOO++UpGy/nq8k/fkQFxen+fPn69ChQxo6dGiOHv/LqVChgsaOHatDhw6pVq1a+vrrr7VlyxZNnTrV9Ulcfr+OL7Z48WI9/PDD2XpTS05O1k033aQ+ffpo9+7dmjRpkq6//np1795dUtqSmGHDhmnkyJG69dZb1b17d9f1mjVrpvvvv99te6dOnXI9vpGRkZoyZYq8vb1dha1Ro0bq16+fpk6d6lpms379es2YMUN33HGH2+x1frvtttt0ww036OWXX9ahQ4fUqFEjLV68WAsWLNDQoUMz7ESWnfH4crZt26YvvvjCdei6Dz74QJUqVcrwe92yZYuCgoKUmpqqjRs36vPPP9ftt9+e6cf09erV04MPPqipU6fq/PnzrmUq06ZNU+fOnV2vz5z+3rLznM3M8OHDNW/ePD388MNavXq17HZ7gT63L5bd+2i32/Xxxx/rtttuU+PGjTVgwACVL19ef//9t3bs2KFFixZpw4YNevXVV/XLL79o8uTJl/1DKC/j0Pfff6+YmBjX6+tSLVu2VJkyZTRr1iy3Tyn27Nnjei5FR0dr69atmjt3rmJjY13vv7nZ/pIlSzR8+HB1795dLVu2VFBQkA4cOKBp06YpKSkp0/NC5NbLL7+smTNnavfu3apXr17Ofjgnh7DI6sx3l0pMTDSeffZZo3z58kZAQIDRpk0bY82aNZkeXic+Pt54+eWXjYiICMPHx8coV66c0atXL2P//v2GYeTucG1fffWVMWzYMCMsLMwICAgwunbtahw+fDjDz2/evNno2bOnUapUKcPPz88IDw83+vTpY/z6669ut32lr0sPpTRv3jzj+uuvNwIDA43AwECjTp06xhNPPOE6e9CTTz5ptGvXzvjll18yZMrs8ECGkXbYr6ZNmxoBAQFGcHCw0aBBA+P55593O6NYTg/XZrPZjI0bN7pdntnvKDk52Rg7dqxRr149w8/PzyhRooTRtGlTY+TIkW5nqslMZtszDMO48cYbjSpVqhgxMTE5fjw+/fRTo2bNmoafn59Rp04dY/r06Vk+btOmTTOaNGniyt2+fXvXIWXSff/990br1q2NgIAAIyQkxGjevLnx1VdfuV3n66+/dm2nZMmSxn333ec6PGG69EMbpX8FBQUZ1157rTFz5szLPkYX38+cnvkuO8+L1atXGy1btjQCAgKMChUqGM8//7yxaNEi16GQ0l3usDYnT540unbtagQHBxuSXL/T9Ndc+pePj49RpkwZo127dsYbb7zhOmzWxS49HNGmTZuMe+65x6hSpYrh5+dnhIWFGd26dTM2bNhQYPf3wIEDxsCBA43q1asb/v7+RsmSJY0bbrjBWLp0aYbbvNLrOSuXHoIvICDAuOaaa4z33nsvw2GbLudKh2urV6+esWHDBqNVq1aGv7+/ER4ebkycODHDdbP7OlYOD9cWEBCQ4WxTl2ZO/53/9ttvxiOPPGKUKFHCCAoKMu677z7j7NmzGW5r4sSJRp06dQwfHx+jbNmyxmOPPZbh0Ffph/1K/ypevLjRpk0b46effnK7XkpKijFy5EjXe0zlypWNYcOGuR2qMCt5OVybYRhGTEyM8fTTTxsVKlQwfHx8jJo1axrjxo3L8PvPyXicmYsfB5vNZpQrV87o2bOnsWvXLtd1Ln2tent7G+Hh4caQIUNcj21mh5xMSUkxRo0a5fb4Pf/885keFjG7v7fsPGcvPlzbxVasWGHYbDbX4VcNI+/vUdk5XFtO7qNhGMaqVauMm2++2QgODjYCAwONhg0bGh9++KFhGIYxduxYo1mzZpmeAe7S8TFdbsah2267zfD393edwTQz/fv3N3x8fIzIyEjDMNyfS3a73ShevLjRpEkT46mnnjJ27NiRp+0fOHDAeO2114yWLVsaYWFhhre3t1GmTBmja9eurkMnZuZyZ369XC9Nf0/O6eHabIaRhzULhcyKFSt0ww03aO7cubmeRb3YoUOHFBERoYMHD2ZY95RuxIgROnToUIYzJgFAQevQoYMiIyPzbW1eQUk/Mcuff/6ZL7N3sC6rPGdRdBXIGmMAAADAagpkjbGnCAoK0n333XfZncEaNmyYt1MPAgAAoFCgGF9G6dKlXTt2ZCX9/OYAAACwNo9aYwwAAADkFmuMAQAAAFGMAQAAAEkUYwAAAEASxRgAAACQRDEGAAAAJFGMAQAAAEkUYwAAAEASxRgAAACQRDEGAAAAJFGMAQAAAEkUYwAAAEASxRgAAACQRDEGAAAAJFGMAQAAAEkUYwAAAEASxRgAAACQRDEGAAAAJFGMAQAAAEkUYwAAAEASxRgAAACQRDEGAAAAJFGMAQAAAEkUYwAAAEASxRgAAACQRDEGAAAAJFGMAQAAAEkUYwAAAEASxRgAAACQRDEGAAAAJFGMAQAAAEkUYwAAAEASxRgAAACQRDEGAAAAJFGMAQAAAEkUYwAAAEASxRgAAACQRDEGAAAAJFGMAQAAAEkUYwAAAEASxRgAAACQRDEGAAAAJFGMAQAAAEkUYwAAAEASxRgAAACQRDEGAAAAJFGMAQAAAEkUYwAAAEASxRgAAACQRDEGAAAAJEneZgcAAKtLdTgVGZusU9GJOhOTpJikFMUlORSXlJr2lZz2/7FJqYr/9/9TnYachiGn05DTkD4rM0ulondJNi/JZpfsXpK3n+QbJPkFS76Baf/vGyT5XfTfgJJScHkpuKzkH2r2QwEAlkYxBoDLMAxDxy8k6uCZOB06G6eTFxJ1OiZRp2OSdDo6SadjEnUuLllOI2+34+29Xzq1OW8b8SkmBZWVgsv9+99/C3PxKlKpGmlfvoF5uw0A8GAUYwCQdCE+RfvOxOpgZJwORqb998C/ZTgxxWl2vOxJiZfOH0z7ypQtrSyXqv5fUS5dM+2/JSIkO6vrABRtFGMARU5UfLL+OnZB245e0PZjF/TXsQs6ej7B7FhXgSHFHE/7OrTS/Vs+gVK5BlKFxlL5xmn/LV0rbUkHABQRFGMAHi0h2aFN/5zXliNRRawE51BKnHRkbdpXOp9iUtn6aSW5QhOpSkupZDXTIgJAQaMYA/AoiSkObTx8Xmv2n9XaA2e17egFJTssshSisEmJl46uT/tKF1JJqtpGqnp92hdFGYAHsRmGkcddRgDAPIkpDm06fF5rD5zV2gPntOVIlCWL8NbwCQo9tc7sGDkXWlkK/7coR7STSoSbnQgAco1iDMByImOTtGzXaS3ddUqr9kUqPtlhdqQ8s2wxvlSZulLtzmlfFa9jhz4AlkIxBmAJe0/FaMmuU1q685S2HInK8+HRChuPKcYXCywj1bwlrSRXv4FDxQEo9CjGAAqtzf+c14/bTmjprlM6dDbe7DgFyiOL8cW8/dOWWtTtLl3TnZORACiUKMYACpVDkXH6bvMxLdhyzOPL8MU8vhhfzNtfqtlJanhX2n+9fc1OBACSOCoFgELgbGySfth6XPO3HNeWI1Fmx0FBS02Udn2f9uVfXKp3h9SgjxTeWrLZzE4HoAhjxhiAKZJTnVq046S+3XRUK/dGKtXTFg3nUJGaMc5KaBWpYW/p2n4c3QKAKSjGAK6qf87Ga9b6w/pmw1GdjUs2O06hQTG+iM0u1egoNXtIqnEzR7YAcNWwlAJAgXM6DS37+7Q+X3tYK/eeEX+O47IMp7R3cdpX8SpS0wHStX2lwNJmJwPg4ZgxBlBgLiSkaM6fRzRz7WH9c67o7EiXG8wYX4GXr3TN7VKzh6UqLcxOA8BDMWMMIN8dj0rQ1N8P6Os/jyghxfon30Ah4EiW/pqb9lXxOun6p6U6XdlZD0C+ohgDyDf7z8Rq8or9mr/lmFIcfBiFAnJsg/T1fVKZOlKbp9KOaOHF2xmAvGMpBYA8237sgiat2Kdftp/0uDPSXS0spciD0MpSq8Fp65B9i5mdBoCFUYwB5NraA2c1acV+/b7njNlRLI9inA+KlZJaPCq1GMSZ9QDkCsUYQI5tORKlsT//rTUHzpodxWNQjPNRQIm0NcjNB0k+/manAWAhFGMA2bb/TKzeWbRbP28/aXYUj0MxLgAhFaX2z0tNHpDsXmanAWABFGMAV3Q6OlHvLd2ruRuOFPkz1BUUinEBKlVTuvGVtFNPA8BlsBsvgCxFJ6Zo8or9mr76EIddg3Wd3SvN7SetbiJ1HCFV62B2IgCFFMUYQAYOp6Ev1h7We0v3KCo+xew4QP44vln6/Hap1q3SrW9JJSPMTgSgkKEYA3Cz8fA5vTp/h3aeiDY7ClAw9vwiHVghtR4itX1G8gkwOxGAQoJiDECSdDY2SWN+/lvzNh0Vex7A46UmSr+/LW2dLd36plT3NrMTASgEKMZAEedwGpq17rDeWbRb0YmpZscBrq4L/0hf3y9Vv0nq/LZUuobZiQCYiGIMFGEbD5/Xawu2a8dxlk2giNv/q/RxK6nVE1L7Fzn+MVBEUYyBIigh2aG3ft6lz9ceZtkEkM6RLK16T9q1ULr9I6lKC7MTAbjK7GYHAHB1rT94TrdO+F0z1lCKgUyd3StNv1Va9LKUkmB2GgBXETPGQBGRmOLQ2F/+1ow/DolzdABXYDilNRPTjmBx+0dSlZZmJwJwFTBjDBQBGw+fU5cJKzV9NaUYyJGz+6TpnaVfhjF7DBQBzBgDHiwxxaHxi3fr01UHKcRAbhlOae2ktNnjHlOkys3NTgSggDBjDHioPadi1H3iKn2yklIM5ItzB9Jmj1eOFwv0Ac9EMQY80Jw/j+j2iau151Ss2VEAz+JMlX4dJc3sIcWeNjsNgHxGMQY8SFxSqp7+eouen7dNCSkOs+MAnuvAcunjNtL+ZWYnAZCPKMaAh9h1Ilq3TVyl7zYfMzsKUDTEnZZm9pSWjpAcnDUS8AQUY8ADzFp3WHd8tFoHzsSZHQUoYoy0k4JM7yxF/WN2GAB5RDEGLCwh2aEnv9qsl7/brqRUp9lxgKLr6HppSnvpwG9mJwGQBxRjwKKORSXozo//0A9bj5sdBYAkJZyTvugprZtidhIAuUQxBixow6Fzun3iKu08EW12FAAXc6ZKPz8vff+klJpsdhoAOUQxBixmzp9HdO8n6xQZy5suUGht+lyacRuHdAMshmIMWITDaWjUDzv1/LxtSnawnhgo9I6slabeIB3fbHYSANlEMQYsIDoxRQM++1PTVh80OwqAnIg+Kk3rLP31jdlJAGSDt9kBAFze0fPx6jdtvfZzKDbAmlITpHkPSTEnpNZPmp0GwGUwYwwUYn+fjNadH/9BKQYsz5AWvyItelkyDLPDAMgCxRgopP48dE59Jq/Rqegks6MAyC9rJkrfPiI5UsxOAiATFGOgEFqy85Qe+HSdohM5zSzgcf6aI33ZR0qKNTsJgEtQjIFCZs6fR/ToFxuVmMKRJwCPtX+ZNKObFHvG7CQALkIxBgqRSSv26fl52+RwsgYR8HjHN0vTOknnONoMUFhQjIFC4o0fd+rtX3abHQPA1XTugDS9ixS5z+wkAEQxBgqFEd/v0CcrmTUCiqSY49JnXaUz/GEMmI1iDJjIMAy9tmC7PvvjkNlRAJgp9mRaOT69y+wkQJFGMQZMYhiGXl2wXZ+vOWx2FACFQdwZ6bNulGPARBRjwCQjvt+hL9b+Y3YMAIVJfKQ04zbp9N9mJwGKJIoxYILRC3dqBjPFADITdyatHJ/ZY3YSoMihGANX2Zifd+nTVexoB+Ay4k6nlePzh8xOAhQpFGPgKpq0Yp+m/HbA7BgArCD2pDSzBycBAa4iijFwlczdcITjFAPImXMHpFl3SkkxZicBigSKMXAVLPv7lIZ9+5fZMQBY0Ymt0uz7pNRks5MAHo9iDBSwzf+c1xOzNiuV0zwDyK2Dv0nfPiw5nWYnATwaxRgoQPvPxGrgZ38qIcVhdhQAVrdzvvTz/5mdAvBoFGOggJyKTlTfT9frfHyK2VEAeIo//yetGGt2CsBjUYyBAhCTmKJ+09brWFSC2VEAeJoVb0pbZ5udAvBIFGMgnzmdhobO3qK/T7IXOYAC8v0Q6egGs1MAHodiDOSzdxbv1q9/nzY7BgBP5kiSZt8rRR83OwngUSjGQD76futxTVqx3+wYAIqC2FPSV/dIKSzZAvILxRjIJ9uPXdDz32w1OwaAouTEFmnBE2anADwGxRjIB2dikvTI5xuUmMIxRgFcZdvnSb+PMzsF4BEoxkAeJac69dgXG3X8QqLZUQAUVcvekHYtNDsFYHkUYyCPhn+/XRsOnzc7BoAizZC+e1Q6yz4OQF5QjIE8+G7zUX21/ojZMQBASo6R5vaXUpPMTgJYFsUYyKWDkXF65bvtZscAgP+c3CYtetnsFIBlUYyBXEhKdWjwl5sUl+wwOwoAuPvzE2nnArNTAJZEMQZyYcxPf2vH8WizYwBA5hY8KZ0/ZHYKwHIoxkAOLd5xUp/9ccjsGACQtaQL0twBUmqy2UkAS6EYAzlwPCpBz8/bZnYMALiy45ukpcPNTgFYCsUYyCaH09CQrzYrKj7F7CgAkD1rJ0l7l5idArAMijGQTR+v2MfxigFYz/dDpIQos1MAlkAxBrJh98kYffDrPrNjAEDOxRyXfnnR7BSAJVCMgStIdTj13NytSnY4zY4CALmz9Stp989mpwAKPYoxcAVTfj+gv45dMDsGAOTND0Ol+HNmpwAKNYoxcBl7TsVowtK9ZscAgLyLPSn9/ILZKYBCjWIMZMHhNPR/LKEA4En+miPtWmh2CqDQohgDWZj6+wFtPcoSCgAeZuHTLKkAskAxBjKx/0ys3lu6x+wYAJD/4k5z4g8gCxRjIBPDF+xQcipLKAB4qE0zpaMbzE4BFDoUY+ASP/11Qqv2RZodAwAKkCH9+KzkZAIAuBjFGLhIQrJDb/y4y+wYAFDwTmyRNk4zOwVQqFCMgYt8tHyfjkUlmB0DAK6OX0dLcXxCBqSjGAP/OhQZp6krD5gdAwCunsQoaQk74gHpKMbAv0b+wA53AIqgLbOkI+vNTgEUChRjQNLSnae0fPcZs2MAgAn+3RHPMMwOApiOYowiL8Xh1Ogfd5odAwDMc3KbtG2O2SkA01GMUeR9ue4fHT4bb3YMADDX8tel1GSzUwCmohijSItPTtWHy/aZHQMAzBf1j7ThU7NTAKaiGKNI+3TlQUXGJpkdAwAKh9/HSYnRZqcATEMxRpF1Pi5ZU3/n8GwA4BJ/VvrjA7NTAKahGKPI+vi3/YpJSjU7BgAULmsmSTGnzE4BmIJijCLp5IVEzfjjkNkxAKDwSYmTfnvL7BSAKSjGKJLeX7pHSZzMAwAyt+lz6dxBs1MAVx3FGEXOocg4zd141OwYAFB4OVOl1e+bnQK46ijGKHKm/L5fDidneAKAy9rylRR9wuwUwFVFMUaRcjo6UfM2HTM7BgAUfo4kac1Es1MAVxXFGEXKp6sOKpm1xQCQPRumS/HnzE4BXDUUYxQZFxJSNGvdP2bHAADrSImT1k02OwVw1VCMUWR8sfawYjluMQDkzLopUlKs2SmAq4JijCIhMcWh6as59BAA5FhilLThU7NTAFcFxRhFwtwNRxQZm2x2DACwpjUfSamMofB8FGN4PIfT0NSVB8yOAQDWFXtK2jnf7BRAgaMYw+Mt3XVKR84lmB0DAKxt/SdmJwAKHMUYHm/mmsNmRwAA6zu6Xjqx1ewUQIGiGMOj7Tsdq9X7I82OAQCegVljeDiKMTzaF2sPy+DszwCQP/76Rko4b3YKoMBQjOGxEpIdmrfpqNkxAMBzpCZIm2eZnQIoMBRjeKwfth1XTCIn9ACAfLXhU/FRHDwVxRge60tO/wwA+e/cAWnfr2anAAoExRgeadeJaG05EmV2DADwTJtnmp0AKBAUY3ikORuOmB0BADzXnl+kxAtmpwDyHcUYHsfhNPTD1hNmxwAAz5WaKO1cYHYKIN9RjOFxVu+LVGRsktkxAMCzbf3a7ARAvqMYw+Ms2HLc7AgA4PkOr5ai2MkZnoViDI+SmOLQoh0nzY4BAEWAIW2bY3YIIF9RjOFRft11WrFJHLsYAK6KbSyngGehGMOjLNhyzOwIAFB0RO6Rjm0yOwWQbyjG8BgXElK0YvcZs2MAQNGyfZ7ZCYB8QzGGx/hl+wklO5xmxwCAouXvH81OAOQbijE8xqIdp8yOAABFz/mD0uldZqcA8gXFGB4hIdmh1fsizY4BAEUTs8bwEBRjeITV+yKVlMoyCgAwxe6fzE4A5AuKMTzCr3+zjAIATHNskxR9wuwUQJ5RjGF5hmFo2d+nzY4BAEWYIe352ewQQJ5RjGF5249F61R0ktkxAKBo+5vlFLA+ijEsj2UUAFAIHPxdSoo1OwWQJxRjWN6vu1hGAQCmcyRJh1ebnQLIE4oxLO1MTJK2H79gdgwAgJQ2awxYGMUYlrb2wFkZhtkpAACSpIO/mZ0AyBOKMSxt3cGzZkcAAKQ7uV2KP2d2CiDXKMawtPUHGYABoPAwpEOrzA4B5BrFGJZ1Li5Ze0+zBzQAFCqHVpqdAMg1ijEsa/1B1hcDQKHDDniwMIoxLGvtAZZRAEChc+ZvKZbDaMKaKMawrHWsLwaAwol1xrAoijEs6UJ8inafjDY7BgAgM8c2mp0AyBWKMSxp0z/n5WR9MQAUTsc2mZ0AyBWKMSzpr2Oc7Q4ACq2T2ySn0+wUQI5RjGFJ2ynGAFB4JcdKkXvMTgHkGMUYlrTjOOuLAaBQO85yClgPxRiWExWfrGNRCWbHAABczvHNZicAcoxiDMvZfozZYgAo9CjGsCCKMSxn+3HWFwNAoXfyL8mRanYKIEcoxrAcdrwDAAtITUw7Cx5gIRRjWM5OdrwDAGvgyBSwGIoxLCUxxaFDZ+PMjgEAyI7IvWYnAHKEYgxLOXw2njPeAYBVnKUYw1ooxrCUg5HMFgOAZTBjDIuhGMNSDrOMAgCs4+w+sxMAOUIxhqWwvhgALCQ5Voo+bnYKINsoxrAUllIAgMWwnAIWQjGGpRyKjDc7AgAgJzhkGyyEYgzLSEh26FRMotkxAAA5ce6A2QmAbKMYwzIOn4uTwaHaAMBaWGMMC6EYwzKOnEswOwIAIKdiTpidAMg2ijEs4zTLKADAeqIpxrAOijEs40xMktkRAAA5FXtSrIODVVCMYRkUYwCwIEeyFH/W7BRAtlCMYRkUYwCwKHbAg0VQjGEZZ2IpxgBgSTEnzU4AZAvFGJbBjDEAWFQMM8awBooxLCOSGWMAsKaYU2YnALKFYgxLiE5MUWKK0+wYAIDcSIo2OwGQLRRjWML5uGSzIwAAcotiDIugGMMS4pIcZkcAAORWUozZCYBsoRjDEuKTU82OAADILYoxLIJiDEuIT2bGGAAsi2IMi6AYwxIoxgBgYRRjWATFGJbAUgoAsLCkWLMTANlCMYYlMGMMABbGUSlgERRjWEICxRhAAXhrVZJsI6M19JdE12X7zznV4+t4lRkXo5Ax0eozN16nYi9/HHWH09CryxIVMSFGAW9Eq/oHMRr9W5IMw3Bd550/khQ2LkZh42I0/g/3ExatO5qqplNjleo0Lt20Z0jO/xnj/v37y2az6a233nK7fP78+bLZbPl+eygavM0OAGSHp84YR62apQurv3K7zLtkJVV8eLIkyUhN1rllnyp+1+8yHCkKiLhWJTs9Jq/AEpluz3CkKmrlTCXs36DUCydl9wuUf3gjFW/fX97Bpf7dZorO/vKB4veulVdgCZXs9LgCqjZ2bePCunlyRJ9RyZsfLZg7DRQSfx5zaMrGZDUs+98cUVyyoU5fxKlRWS8t61tMkvTq8iTd9lW81j4UKHsWhWvs6mR9vCFFM+7wV70wL2047tCABQkK9ZeGtPDTtlMOvbY8SQvvLSbDkLp9Fa9O1b3VoKyXUp2GHv0xUVO7Bcjb7qGFzlkwy+H8/f01duxYDRo0SCVKZD4uAjnBjDEkSYZhqGPHjrrlllsyfG/SpEkqXry4jh49akKyNImpnlmMJcmndBVVemKm66vcfWNd3zv36ydK2Ldepe94UWXvfUupsWd15rs3s9yWkZqk5JP7Fdr6bpXvN0Fl7nhJKeeO6cy3o13Xidn6i5JP7lO5+99RUKNbFfnDONesVkrUScVuXaTi7foW3B0GCoHYZEP3fZugT24LUAn//8ro6iMOHYoy9NkdAWpQ1ksNynppxh0B2nDcqWUHsx6H/jji0O21vdW1lo+qFrer1zU+6lTdW+uPpc00/x3pVMOyXroxwls3VfNWw7J2/R2Z9r1xq5PVroq3mlX0Ktg7bTZn/o/jHTt2VLly5TRmzJgsrzNv3jzVq1dPfn5+qlq1qsaPH5/vOeA5KMaQJNlsNk2fPl3r1q3TlClTXJcfPHhQzz//vD788ENVqlTJtHxOw0M/XpQku5e8gkr891UsVJLkTIpT7LYlKnHjgwoIbyS/cjVUustQJR3bpaRjf2e+Kb9Alb37dQXWbSufUpXkV7GOSt78qJJP7lNq9GlJUsrZIwqo0UK+ZcIVfG1XOeMvyJmQtv7v3OJJKtGhv+x+xa7OfQdM8sRPiepa01sdq7l/cJqUasgmye+ijurvLdlt0qp/sp71bF3ZS78eTNWes2nlb+tJh1b941DnGmnbbxBm156zDv1zwanDUU7tOetU/TC79p9zavqWFL1+o1++38dCpwCKsZeXl9588019+OGHmU7ebNy4UX369NHdd9+tv/76SyNGjNCrr76qzz77LN+zwDNQjOFSuXJlTZgwQc8995wOHjwowzD04IMPqlOnTmrSpIk6d+6soKAglS1bVg888IAiIyNdP/vNN9+oQYMGCggIUKlSpdSxY0fFxcXlXzgP7sWp54/r6Ed9dWzygzrzwzhXgU06uU9yprotc/ApVVleIWWUdDzzYpwZZ1K8JJvsfkGSJN+wCCUd3SlnSpISD26SV1BJ2QNCFLtjuWzevipWq3V+3j2g0Jm9PUWbTjg0pmPGMtqykpcCfaUXliYpPsVQXLKh5xYnymFIJ2KyHohevN5Xd9f3UZ2JcfIZHa0mU+I0tIWv7mvoI0mqW8ZLb97kr5tnxqvTF/Eac5O/6pbx0qCFCXr7Zj8t2p+q+pNi1WRKrH4/7KFH4TEK5pO/Hj16qHHjxho+fHiG77377ru66aab9Oqrr6pWrVrq37+/Bg8erHHjxhVIFlgfxRhu+vXrp5tuukkDBw7UxIkTtX37dk2ZMkU33nijmjRpog0bNuiXX37RqVOn1KdPH0nSiRMndM8992jgwIHatWuXVqxYoZ49e7rtdJJXntqL/crXVqkuTyus90iV7PS4HFGndHLWC3ImxcsZd17y8pbdP8jtZ7wCi8sRdz5b2zdSkxW1YrqKXdPONQsc1OBm+YRF6Pinj+vCmjkqffsLcibG6sKqWSrZcZDO/z5Tx6Y8rFNfv6rUmMgr3AJgLUcuOPXUL4ma1TNA/t4Z1/OWCbRrbu9i+mFPioLejFHoWzGKSpKuLW/X5Zb/ztmRqll/pejLOwO06ZFAzbjDX++sSdaMLcmu6zx6na92Dw7S7sFBevQ6X83YkqxgP5taVfLSQ98n6Lu7AvRuJ3/d/U2CklI9cNQzLr8DY16MHTtWM2bM0K5du9wu37Vrl9q0aeN2WZs2bbR37145HJ67RA+5x853yGDq1KmqV6+efv/9d82bN09TpkxRkyZN9Oab/61tnTZtmipXrqw9e/YoNjZWqamp6tmzp8LDwyVJDRo0yNdM+VmyC5OA6tf994+wCPlVqK2jHw9U3N+rZPfxzdO2DUeqzixI21u7VKcnXJfbvLxVqtNjbteN/PF9BTe9TcmnDihh7xqVH/ChotfN0/mlU1Wmx0t5ygEUJhtPOHQ6ztC1U/77RMthSL8fdmji+mQlvRKsTtW9tX9IsCLjnfK221Tc36Zy78SoWr2s55L+b0miXmzjp7vrp80QNyjrpcMXDI1Zlax+jTO+liPjnRr5W5J+HxCodcccqlXKrpqlvFSzlJTilPacdapBWU9bc1xwOxa2a9dOt9xyi4YNG6b+/fsX2O3A8zFjjAzCwsI0aNAg1a1bV3fccYe2bt2q5cuXKygoyPVVp04dSdL+/fvVqFEj3XTTTWrQoIF69+6tTz75ROfPZ29GM7uy2hPc09j9g+RTsqJSo47LHlhCcqTKmeh+mCNHXFSWR6VIl16KUy+cVthdoy+7Zjjx8DalnD2s4Gu7KfGfbQqodp3svv4qVud6Jf7zV77cL1yZYfO0ElQ43RThrb8eC9SWR//7uq6CXfc19NGWRwPlddG0cOlidhX3t2nZwVSdjjPUvXbWc0nxKcowo+xlk7I6+trTi5L0dEs/VQqxy+FMK8PpUp2GHJ44F1DA4/hbb72lH374QWvWrHFdVrduXa1evdrteqtXr1atWrXk5cVrDhkxY4xMeXt7y9s77ekRGxur2267TWPHjs1wvfLly8vLy0tLlizRH3/8ocWLF+vDDz/Uyy+/rHXr1ikiIiJf8tg99RBGl3AmJyg16oS8Am+QX7kakt1bCYe3KrB22keBKWePyhF9Rn4V6mS5DVcpPn9cZe8ZI6+AkKyvm5qsc0s+VunbnpPN7iUZzv8+7XQ6ZBTgR59wZxTgbBr+E+xnU/0w90IU6GNTqYD/Lp++OVl1y9hVpphda46m6qlfkvR0S1/VLv3fz930eZx61PHR4OZps8G31fLWGyuTVCXUpnphXtp8wqF31yZrYGOfDBmW7E/bSW/GHf6SpGYVvfR3pFM/703RkWhDXjabapfyxHmrgn2ON2jQQPfdd58++OAD12XPPvusmjVrptGjR+uuu+7SmjVrNHHiRE2aNKlAs8C6KMa4omuvvVbz5s1T1apVXWX5UjabTW3atFGbNm302muvKTw8XN99952eeeaZfMng5aEzxueXfaqAGs3lHRqm1JhzurBqlmSzK/Ca9rL7BSqo4c06v+x/8vIPls2vmM4vmSy/CnXkV/G/Ynzsk0dVon1fFavVOq0Uzx+j5FP7FdbrNcnplCM2bfbeHhAkm5f7m3TUH7MVUO06+ZatLknyq3iNzq+YpqAGHRWzaaH8K9a9eg9GEedkxrjQ2H3WqWG/JulcgqGqxe16ua2vnm7pvhxi/zmnIuP/+8Pxw87+enV5kh7/KVGn4wxVCLZpUFMfvdbefQe/hBRDg39O1Ne9AlyfhFUKsevDzv4asCBRft7SjDv8FeDjgWPeVRjHR40apa+//tr172uvvVZz5szRa6+9ptGjR6t8+fIaNWoUyy2QJZvhqYs3kScjRozQ/PnztWXLFh0/flyNGzdW+/bt9fzzz6tkyZLat2+fZs+erf/973/asGGDfv31V3Xq1ElhYWFat26d7r//fs2fP1+dO3fOlzzvLdmjCb/uzZdtFSZnFoxV0tEdciREyysgVH6VrlHxdn3lU6K8pItP8PGbDEeK/COuVambH5dX0H9LKQ6P7aZSXYYqqEFHpV44pWOTH8z0tsre86b8qzR0/Tv5zCGd+e4Nle//oey+aTNXhuHUuSWTFbdjhXxKVVTp2/5PPiUqFOAjgHQbIqao9InfzI4BFAybXRqev0vsgILAjDGuqEKFClq9erVeeOEFderUSUlJSQoPD9ett94qu92ukJAQ/f7773r//fcVHR2t8PBwjR8/Pt9KsST5eHng7ImkMre/cNnv27x9VarTYxl2lrtY+AsLXf/vHVrW7d+X41umqio+8on77dnsKtXpcZXq9Hi2toH8wxpjeDSfQLMTANnCjDEsYdqqgxq1cKfZMYACs67apyp7/FezYwAFI6is9Nwes1MAV+SJq/vhgYL8+XADns2wMRzDg/lwNk1YAyMxLCHYj2IMz2YwHMOT+QZd+TpAIcBIDEtgxhiezslwDE/my4wxrIGRGJYQxIwxPBxLKeDRWEoBi2AkhiUEM2MMD8eMMTyaL0elgDUwEsMSgvwynj0K8CQUY3g0ijEsgpEYlhDoxzFe4dk4JTQ8WrFSZicAsoViDEsI8vOWl53iAM/FKaHh0YLCzE4AZAvFGJZgs9lUKtDX7BhAgXEyYwxPFlTO7ARAtlCMYRnlQv3NjgAUGNYYw6MxYwyLYCSGZZQNoRjDc7HGGB4tqKzZCYBsoRjDMsqG+JkdASgwzBjDo1GMYRGMxLCMcswYw4M5GI7hqezeHJUClsFIDMtgKQU8mcFwDE9VrLRk5/kNa+CZCsugGMOTcVQKeKxgllHAOijGsAyOSgFP5rQxHMNDFQ83OwGQbYzEsAyKMTyZw2A4hocqVd3sBEC2MRLDMkL8fVSSk3zAQ3FUCnisktXMTgBkGyMxLKV6mUCzIwAFgmIMj1WSGWNYByMxLKVa6SCzIwAFgp3v4LFYSgELoRjDUqoxYwwPxXGM4ZF8g6TgcmanALKNkRiWUr0MM8bwTMwYwyOVjDA7AZAjFGNYCjPG8FSsMYZHYn0xLIaRGJZSpWQx+XgxswbP4zB4XsMDsb4YFkMxhqV4e9lVpWQxs2MA+Y4ZY3iksvXMTgDkCCMxLKdGGOuM4XlYYwyPVK6R2QmAHKEYw3LqVQg1OwKQ7zgqBTyObzBLKWA5jMSwnIaVKMbwPJwSGh6nXH3JxichsBZGYlhOw0rFzY4A5DsHSyngacqzjALWQzGG5ZQM9FXF4gFmxwDylZMZY3gaijEsiJEYltSoMssp4FmYMYbHKdfQ7ARAjlGMYUkNKhY3OwKQryjG8Cje/lKZOmanAHKMYgxLasQOePAwnOADHqVsPcnL2+wUQI5RjGFJ9SuFsrMzPIpDXmZHAPJPlVZmJwByhWIMSwrx91G10oFmxwDyjcPsAEB+Cm9jdgIgVyjGsKwW1UqZHQHINxyVAh7DZpfCmTGGNTESw7JaUYzhQVhjDI8RVk8KKGF2CiBXKMawrFbVS7HOGB4jleEYnqIqyyhgXYzEsKzSQX6qFRZsdgwgXziZMYanCG9tdgIg1yjGsLRW1VlOAc/AcYzhMdjxDhZGMYalUYzhKVLZ+Q6eoEwdKbC02SmAXGMkhqW1rFZKdiba4AHY+Q4eoWpbsxMAeUIxhqWFBvjomgohZscA8oyd7+ARat1qdgIgTxiJYXlta5YxOwKQZw6n2QmAPPIJlCKYMYa1UYxheR3rljU7ApBnnBIalletg+TtZ3YKIE8oxrC8JpWLq0wwgzGsLdUwOwGQR7VuMTsBkGcUY1ie3W5Tx7phZscA8sTBcAxLs1GM4REYieERbr6G5RSwNtYYw9LKN5KCy5mdAsgzijE8QuvqpRXoyxpNWBdHpYCl1e5sdgIgXzASwyP4+3ipXS2OTgHrSnVyHGNYGMso4CEoxvAYLKeAlXFKaFhW8XCpQhOzUwD5gmIMj3FjnTB5cxo8WBSnhIZl1b/T7ARAvmEkhscoXsxXbWqUNjsGkCup7HwHq2rYx+wEQL6hGMOj9Ly2otkRgFzhcG2wpLB6Ulhds1MA+YaRGB6l0zXlFOTnbXYMIMdSDZYBwYIa9DI7AZCvKMbwKAG+Xrq1PsfShPVQjGE9NooxPA7FGB6nZxOWU8B6KMawnMrNpeJVzE4B5CuKMTxOy2qlVCHU3+wYQI5QjGE5DXqbnQDIdxRjeBy73abbmTWGxXCCD1iKl69Ur4fZKYB8RzGGR2I5BayG4xjDUup0kwI5PCY8DyMxPFLNssFqWCnU7BhAtqUaZicAcuC6gWYnAAoExRge697m7BQC62CNMSyjdC0poq3ZKYACQTGGx7q9cUUF+3NMY1hDCkspYBVNB5idACgwjMTwWAG+Xrrz2kpmxwCyhVNCwxK8A6TG95idAigwFGN4tPtbhpsdAcgWdr6DJdTvKQWUMDsFUGAYieHRaoQF6foa7DmNwi+Fne9gBex0Bw9HMYbH69+6qtkRgCtysPMdCrtyDaVK15mdAihQFGN4vBvrhCm8VDGzYwCXlcIJPlDYtRpsdgKgwFGM4fHsdpv6tapqdgzgslhjjEIttIpU/06zUwAFjpEYRUKfZpUVGuBjdgzgsgwxa4xCqtUTkheHv4TnoxijSAjy82atMQo/u5fZCYCMAkpK1/Y1OwVwVVCMUWQMbBOhID9mPFCI2RiSUQg1f0TyZT8NFA2MwigyQov56L6WnCYahZiNGWMUMj7FpBaDzE4BXDUUYxQpD11fTX7ePO1RSNl5bqKQafKAVKyk2SmAq4ZRGEVKmWA/3d2sstkxgMyxlAKFid1bas0h2lC0MAqjyBnUvrp8vNj7H4WPwVIKFCaN7pGKs/wMRQvFGEVOheIB6tGkotkxgIyYMUZh4eUndXjR7BTAVccojCJp8A015evF0x+FDMUYhUWzB6XQSmanAK46RmEUSVVKFdO9LfiIEIWLQTFGYeAbJLV91uwUgCkYhVFkDbmppoI5rjEKE9YYozBo+bgUWNrsFIApKMYoskoG+mpQ+2pmxwBcmDGG6QJKSq2fNDsFYBpGYRRpD15fTWVD/MyOAaShGMNs1w+V/EPMTgGYhlEYRVqAr5eGdqxldgxAkmQwJMNMweXTTv8MFGGMwijy+lxXWTXCgsyOAbDGGOa6abjkE2B2CsBUFGMUeV52m56/pbbZMQAZNk48A5NUai41utvsFIDpKMaApE71yqlVtVJmx0ARx5nvYAqbXerytsQfZgDFGEg3+o56nCoapuKoFDBFkwekCk3MTgEUCozCwL9qhAXrwes5fBvMQzHGVedfPG1tMQBJFGPAzVM31VTF4ux8ApNQjHG13fCSFMgyMiAdozBwkQBfL7122zVmx0ARxeHacFWF1ZOaPWR2CqBQYRQGLnFLvXK6qU6Y2TFQBLGUAldVl7clOzt8AhdjFAYyMaJ7Pfn78PLA1cWMMa6aa/tKVa83OwVQ6DAKA5moXLKYnuhQw+wYKGKYMcZVEVJR6vSG2SmAQolRGMjCoPbVVbd8iNkxUIRQjHFVdHtf8mdsAzLDKAxkwdfbrvG9G3FsY1w1LKVAgWt4t1Srk9kpgEKLURi4jGsqhGjIjTXNjoEighljFKigslLnt8xOARRqjMLAFTx+Qw01qlzc7BgoApwMyShIXcdLASXMTgEUaozCwBV42W0a37uR/Lx5uaBgGTYOnYUCUq+HVPc2s1MAhR7v9EA21AgL0nOdapsdAx7OEOvZUQCCykld3jE7BWAJFGMgmx68PkLNqvIxJAqOkxlj5DebXeo5RQosbXYSwBIoxkA22e02je/dWEF+3mZHgYdixhj5rs1QqVoHs1MAlkExBnKgSqlieuvOBmbHgIfiqBTIV5WaSze8bHYKwFIYhYEc6tawgu5vWcXsGPBAHJUC+cYvVLrzf5IXn3ABOcEoDOTCq92uUf2KnDkK+cvJjDHyy23vSyXCzU4BWA6jMJALft5e+ujeaxXMemPkI9YYI19c21eq39PsFIAlUYyBXAovFaixvRqaHQMexCmOSoE8KlNXunWs2SkAy6IYA3nQpUF59WvFx5XIH8wYI0/8i0v3fCn5FjM7CWBZFGMgj17ueo0aVQo1OwY8ADvfIddsXlKvaVLJamYnASyNURjII19vu6Y8cJ3Cgv3MjgKLY+c75FrH4VKNm8xOAVgeozCQD8qF+uuTvtfJ34eXFHKPGWPkSv1eUpunzE4BeARGYSCfNKpcXG/3amR2DFiYwZCMnCrXULp9otkpAI/BKAzko+6NKmjIjTXMjgGLcrLzHXKiWGnp7i8lnwCzkwAeg2IM5LOnb66lLg3KmR0DFsRSCmSbl6/UZ4ZUvLLZSQCPwigM5DObzabxvRtzZjzkGDPGyB6bdPskqer1ZgcBPA7FGCgAAb5e+qTvdSobwpEqkH0clQLZcvNIqWFvs1MAHolRGCgg5UMDNGNgc4X4c9poZI/TYEjGFbR4jCNQAAWIURgoQHXKhWha/2YK8OFUv7gy1hjjsur1kG4dY3YKwKMxCgMF7LqqJTXpvmvlbWf9KC6PNcbIUvj1Uo8pko3nCFCQKMbAVXBDnTC907sR72m4LKf4ZAGZCLtGunuW5M0+C0BBoxgDV8kdTSrqtW7XmB0DhZiDGWNcqngV6b5vpIDiZicBigSKMXAVDWgToSc5AQiywFIKuAmpKPX7QQqtaHYSoMigGANX2bOdaqtfq3CzY6AQcjAkI11Q2bRSXKKq2UmAIoVRGDDByNvr64GWlGO4Y8YYktJO9dz3e6lUdbOTAEUOxRgwyeg7KMdwx853ULHSUv+FUlgds5MARRLFGDDRqNvrUY7h4jCYMS7SAsv8W4rrmp0EKLIoxoCJbDabRt9RXwPbRJgdBYUASymKsMAyaWuKKcWAqSjGQCHw2m3X6LEOrCcs6ijGRVRoFWnAL5RioBCgGAOFxAu31tHQjjXNjgETOVhjXPSUqSM9uEgqzWEcgcKAYgwUIkM71tKo2+uJs0cXTawxLmIqNZMG/CyFVDA7CYB/UYyBQqZvq6qadF9T+Xnz8ixqWEpRhFS/Seq7QCpW0uwkAC7COy9QCN1av5xmPdRCoQE+ZkfBVcSMcRFR/07p3q8l30CzkwC4BMUYKKSuq1pS8x5rpYrFA8yOgquENcZFQLOHpJ7/k7z4oxcojCjGQCFWIyxY8x5rrTrlgs2OgqvAwVIKz2WzSx1HSF3HS3beeoHCilcnUMiVC/XXnEdbqVW1UmZHQQFjKYWH8g2S7polXf+02UkAXAHFGLCAEH8fff5gc93XoorZUVCAHAzJnie0ijRwkVSni9lJAGQDozBgET5edr3Ro4He7NFAvl68dD2Rkxljz1K5pfTwMqlcfbOTAMgm3l0Bi7m3RRV99UgLlQn2MzsK8hkzxh6k0b1pp3gOKmN2EgA5wCgMWFDT8JL6YfD1alS5uNlRkI9SmTG2Pptd6jhS6vGx5O1rdhoAOUQxBiyqXKi/5gxqqTuvrWR2FOQTh8GQbGmBZaT7v5WuH2p2EgC5xCgMWJift5fG92mk4bddIx8vZhutjjPfWVjVttKjq6TqN5idBEAeUIwBDzCgTYTmPdZaVUsVMzsK8iCVYmw9NrvU7v/STu8cXM7sNADyiGIMeIiGlYpr4ZC26tGkotlRkEsOJ8XYUoqVlu77RrrxFcnOWQsBT0AxBjxIkJ+33rurscb3bqRAX96orYajUlhIeJu0pRM1bjI7CYB8xCgMeKA7m1bSwiFtVb9iiNlRkAMclcIC7N5S+xfTDsUWUt7sNADyGcUY8FARpQP17WNt9OD1EbLRtyyBYlzIlakrPbRUumEYSycAD0UxBjyYr7ddr3a7RrMebKHKJQPMjoMr4KgUhZTNLrUeIg36TarQxOw0AAoQxRgoAlrXKK1FQ9upf+uqstO9Ci1mjAuhktWlAb9InUZL3pxtEvB0FGOgiCjm660R3etpzqBWqlYm0Ow4yEQqJ/goRGxS80fSdrCr0sLsMACuEkZhoIi5rmpJ/TSkrQa1ryYvpo8LFQczxoVDqRpSv++lLuMkX44NDhQlFGOgCPL38dKwznX13eOtVadcsNlx8C8Ha4zN5e0v3fCy9NgfUkQ7s9MAMAHFGCjCGlYqroVPXq9XutZVsJ+32XGKvFQnQ7JpanaSHl8rtX+etcRAEcYoDBRx3l52PdS2mpY910G9mlbi0G4mYsbYBCGVpLu+kO6bK5WMMDsNAJNRjAFIksoE++md3o307WOt1ahSqNlxiqRUTgl99dh9pDZPSYPXS3VvMzsNgELCZhiGYXYIAIWLYRias+GIxi3arcjYZLPjFBkdSp7XZ/FPmB3D89XpJt00XCpTy+wkAAoZFhUCyMBms+muZlXUuUF5TVi6VzPXHlZyqtPsWB4vlQ/xClblFtLNo6QqLc1OAqCQYsYYwBUdj0rQhKV79c2mo3I4GTIKSsviFzQ78TGzY3ieUjWljsNZMgHgiijGALLtwJlYvbtkj37864QYOfLfdaEx+iZpkNkxPEdQWan9C9K1/SQvPiAFcGUUYwA5tuP4Bb2zaLeW7z5jdhSP0iQkRt8lU4zzLKCk1OpxqeXjki9neQSQfRRjALm24dA5vbN4t9YeOGd2FI/QIDhOP6Q8bHYM6woqK7V+UrpuIIUYQK5QjAHk2aZ/zmvKb/u1ZOcpsQQ59+oExeuX1IfMjmE9oZXTDr3W5AHJx9/sNAAsjGIMIN/sPxOrT34/oG83H+MoFrlQMzBBSxwPmh3DOkpWl65/Wmp0t+TlY3YaAB6AYgwg352OTtS01Yc0a91hxSSmmh3HMiICErTcoBhfUeUWUotB0jV3SHYvs9MA8CAUYwAFJiYxRV+u+0efrzmsY1EJZscp9Cr5J2mVBpgdo3Dy9pfq95JaPCKVb2R2GgAeimIMoMA5nYaW7z6tmWsP6/c9Z1iHnIXyfslaY+tvdozCJbSy1OzBtEOuFStpdhoAHo5iDOCqOnIuXl+u/0ffbDyqMzFJZscpVMr4puhPez+zYxQCNimirdT8Eal2F5ZLALhqKMYATJHqcGrprtOa/ec/zCL/K9QnVVu9+podwzwlq6ftSNfwLqlEuNlpABRBFGMApjt5IVELtx3XD1uPa+vRC2bHMU2gl0M7fB4wO8bV5V9cqt9TanSPVLm52WkAFHEUYwCFyqHIOH2/9bi+33pc+07Hmh3nqvKzO7Xb936zYxQ8u49Uo2Pa7HDtzpK3n9mJAEASxRhAIbbzeLS+33pcC7cd19Hznn9UC7vNqQN+HlqMfQKlGjdJdbpJtW6RAoqbnQgAMqAYA7CE7ccuaPnfp7Vs92ltPRLlsWuSD/nfa3aE/FOstFT71rQyXO0GzkoHoNCjGAOwnLOxSVqx+4yW7T6t3/ec8aiTiBwMuF82w8JnDSxTV6p+o1Snq1SlJUeUAGApFGMAlpbqcGrD4fNavvu01h44px3HLijVwtPJB4v1k82ZYnaM7CteRYpoJ0V0SPtvcFmzEwFArlGMAXiU+ORUbTocpfUHz2rdwXPaciRKSanWmYE9GDhANkchPr5zYBmpalupWnspor1UMsLsRACQbyjGADxacqpT245Gaf2hc9p46Ly2H7+gU9GFt3geDH5ItpR4s2Ok8QmUKjSWKjSRKjZN++L4wgA8GMUYQJETGZukncejteN4tHaeiNaO4xd0KDKuUOzQdzDkYdmS467+DfsGSaVrSuUb/VeCy9RhjTCAIoViDABKW4Kx60SMdp+M0aGzcTp8Nk6Hz8br8Nl4JaQ4rlqOg6GPypYUXXA3EBgmlamdVoJL15bK1JJK15JCKko2W8HdLgBYAMUYAK7gdHSiDp+L/7cox+nIuXhFxiYrMjZJkbFJOheXnG+zzQeKPy57YlTuftjLTwoul1ZyQyr8+1Xxv/+WqiYFlMifoADggSjGAJBHDqehc3HJOhuXpMiYtMJ8Ni5ZCcmpSkhxKCHZqYQUhxJTHEpIdqRdluJQUopDhqSL52m/CX5XPo54ye6d9uXlK/kFSX4hkn/Iv/8N/e+/6ZcFlZUCSzPrCwB5QDEGAAAAJNnNDgAAAAAUBhRjAAAAQBRjAAAAQBLFGAAAAJBEMQYAAAAkUYwBAAAASRRjAAAAQBLFGAAAAJBEMQYAAAAkUYwBAAAASRRjAAAAQBLFGAAAAJBEMQYAAAAkUYwBAAAASRRjAAAAQBLFGAAAAJBEMQYAAAAkUYwBAAAASRRjAAAAQBLFGAAAAJBEMQYAAAAkUYwBAAAASRRjAAAAQBLFGAAAAJBEMQYAAAAkUYwBAAAASRRjAAAAQBLFGAAAAJBEMQYAAAAkUYwBAAAASRRjAAAAQBLFGAAAAJBEMQYAAAAkUYwBAAAASRRjAAAAQBLFGAAAAJBEMQYAAAAkUYwBAAAASRRjAAAAQBLFGAAAAJBEMQYAAAAkUYwBAAAASRRjAAAAQBLFGAAAAJBEMQYAAAAkUYwBAAAASRRjAAAAQBLFGAAAAJBEMQYAAAAkUYwBAAAASRRjAAAAQBLFGAAAAJBEMQYAAAAkUYwBAAAASRRjAAAAQJL0/zBvEvLRbUq1AAAAAElFTkSuQmCC",
|
||
"text/plain": [
|
||
"<Figure size 600x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"from imblearn.over_sampling import ADASYN\n",
|
||
"from sklearn.compose import ColumnTransformer\n",
|
||
"from sklearn.preprocessing import OneHotEncoder\n",
|
||
"\n",
|
||
"categorical_features = ['Smoking', 'AlcoholDrinking', 'Stroke', 'DiffWalking', 'Sex', 'AgeCategory', 'Race', 'Diabetic', 'PhysicalActivity', 'GenHealth', 'Asthma', 'KidneyDisease', 'SkinCancer'] # Ваши категориальные признаки\n",
|
||
"numeric_features = ['BMI', 'PhysicalHealth', 'MentalHealth', 'SleepTime'] # Ваши числовые признаки\n",
|
||
"\n",
|
||
"# Создание пайплайна для обработки категориальных данных\n",
|
||
"preprocessor = ColumnTransformer(\n",
|
||
" transformers=[\n",
|
||
" ('cat', OneHotEncoder(), categorical_features), # OneHotEncoder для категориальных данных\n",
|
||
" ('num', 'passthrough', numeric_features) # Оставляем числовые колонки без изменений\n",
|
||
" ]\n",
|
||
")\n",
|
||
"\n",
|
||
"# Создание экземпляра ADASYN\n",
|
||
"ada = ADASYN()\n",
|
||
"\n",
|
||
"# Преобразование данных с помощью пайплайна\n",
|
||
"X = preprocessor.fit_transform(df_train.drop(columns=['HeartDisease']))\n",
|
||
"y = df_train['HeartDisease']\n",
|
||
"\n",
|
||
"# Применение ADASYN\n",
|
||
"X_resampled, y_resampled = ada.fit_resample(X, y)\n",
|
||
"\n",
|
||
"# Создание нового DataFrame\n",
|
||
"df_train_adasyn = pd.DataFrame(X_resampled)\n",
|
||
"# Восстанавливаем названия столбцов для DataFrame\n",
|
||
"ohe_columns = preprocessor.named_transformers_['cat'].get_feature_names_out(categorical_features)\n",
|
||
"new_column_names = list(ohe_columns) + numeric_features\n",
|
||
"df_train_adasyn.columns = new_column_names\n",
|
||
"\n",
|
||
"# Добавление целевой переменной\n",
|
||
"df_train_adasyn['HeartDisease'] = y_resampled\n",
|
||
"\n",
|
||
"# Вывод информации о новой выборке\n",
|
||
"print(\"Обучающая выборка после oversampling: \", df_train_adasyn.shape)\n",
|
||
"print(df_train_adasyn['HeartDisease'].value_counts())\n",
|
||
"\n",
|
||
"# Визуализация\n",
|
||
"counts = df_train_adasyn['HeartDisease'].value_counts()\n",
|
||
"plt.figure(figsize=(6, 6))\n",
|
||
"plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
|
||
"plt.title('Распределение классов HeartDisease в тренировочной выборке после ADASYN')\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"2. Балансировка данных андерсемплингом. Этот метод помогает сбалансировать выборку, уменьшая количество экземпляров класса большинства, чтобы привести его в соответствие с классом меньшинства."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 372,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обучающая выборка после undersampling: (32848, 18)\n",
|
||
"HeartDisease\n",
|
||
"No 16424\n",
|
||
"Yes 16424\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 200x200 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"from imblearn.under_sampling import RandomUnderSampler\n",
|
||
"\n",
|
||
"rus = RandomUnderSampler()# Создание экземпляра RandomUnderSampler\n",
|
||
"\n",
|
||
"# Применение RandomUnderSampler\n",
|
||
"X_resampled, y_resampled = rus.fit_resample(df_train.drop(columns=['HeartDisease']), df_train['HeartDisease'])\n",
|
||
"\n",
|
||
"# Создание нового DataFrame\n",
|
||
"df_train_undersampled = pd.DataFrame(X_resampled)\n",
|
||
"df_train_undersampled['HeartDisease'] = y_resampled # Добавление целевой переменной\n",
|
||
"\n",
|
||
"# Вывод информации о новой выборке\n",
|
||
"print(\"Обучающая выборка после undersampling: \", df_train_undersampled.shape)\n",
|
||
"print(df_train_undersampled['HeartDisease'].value_counts())\n",
|
||
"\n",
|
||
"# Визуализация распределения классов\n",
|
||
"counts = df_train_undersampled['HeartDisease'].value_counts()\n",
|
||
"plt.figure(figsize=(2, 2))\n",
|
||
"plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
|
||
"plt.title('Распределение классов HeartDisease в тренировочной выборке после Undersampling')\n",
|
||
"plt.show()"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "aimenv",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.12.5"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 2
|
||
}
|