session_6a_datascience_cmu.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Foundations of Data Science - CMU Portugal Academy\n",
    "\n",
    "> In this class, we will focus on visualizing data using various libraries such as matplotlib, seaborn and plotly. \n",
    "> \n",
    "> Instructors:\n",
    ">   - David Semedo (df.semedo@fct.unl.pt)\n",
    ">   - Rafael Ferreira (rah.ferreira@campus.fct.unl.pt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import the Necessary Libraries "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split, cross_val_score, GridSearchCV, RandomizedSearchCV, KFold\n",
    "from sklearn.preprocessing import StandardScaler, MinMaxScaler, OneHotEncoder, LabelEncoder\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.datasets import load_iris\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.feature_selection import chi2, SelectKBest, RFE\n",
    "from sklearn.linear_model import LogisticRegression as LogReg"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading the Dataset\n",
    "\n",
    "**Origin:** \n",
    "\n",
    "The dataset was introduced by the British biologist and statistician Ronald A. Fisher in 1936 as part of his paper on discriminant analysis.\n",
    "\n",
    "**Structure:** \n",
    "\n",
    "The dataset contains 150 samples of iris flowers, with each sample belonging to one of three species:\n",
    "- Iris setosa\n",
    "- Iris versicolor\n",
    "- Iris virginica\n",
    "\n",
    "**Features:** \n",
    "\n",
    "Each sample has four features (attributes) measured in centimeters:\n",
    "1. Sepal Length: Length of the sepal\n",
    "2. Sepal Width: Width of the sepal\n",
    "3. Petal Length: Length of the petal\n",
    "4. Petal Width: Width of the petal\n",
    "\n",
    "**Target Variable:** \n",
    "\n",
    "The target variable is the species of the iris flower, represented as integer labels (0, 1, 2) corresponding to the three species."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "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>sepal length (cm)</th>\n",
       "      <th>sepal width (cm)</th>\n",
       "      <th>petal length (cm)</th>\n",
       "      <th>petal width (cm)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>6.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>6.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>5.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     sepal length (cm)  sepal width (cm)  petal length (cm)  petal width (cm)\n",
       "0                  5.1               3.5                1.4               0.2\n",
       "1                  4.9               3.0                1.4               0.2\n",
       "2                  4.7               3.2                1.3               0.2\n",
       "3                  4.6               3.1                1.5               0.2\n",
       "4                  5.0               3.6                1.4               0.2\n",
       "..                 ...               ...                ...               ...\n",
       "145                6.7               3.0                5.2               2.3\n",
       "146                6.3               2.5                5.0               1.9\n",
       "147                6.5               3.0                5.2               2.0\n",
       "148                6.2               3.4                5.4               2.3\n",
       "149                5.9               3.0                5.1               1.8\n",
       "\n",
       "[150 rows x 4 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load the iris dataset\n",
    "data = load_iris()\n",
    "X = pd.DataFrame(data.data, columns=data.feature_names)\n",
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2])"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = data.target\n",
    "y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train, Validation and Test Splits\n",
    "Splitting the dataset into training, validation, and test sets to evaluate model performance properly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original dataset\n",
      "Input Features: (150, 4)\n",
      "Target Features: (150,)\n",
      "\n",
      "Training set: (90, 4) (90,)\n",
      "Temporary set: (60, 4) (60,)\n",
      "\n",
      "Training set: (90, 4) (90,)\n",
      "Validation set: (30, 4) (30,)\n",
      "Test set: (30, 4) (30,)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# original dataset\n",
    "print(\"Original dataset\")\n",
    "print(\"Input Features:\", X.shape)\n",
    "print(\"Target Features:\", y.shape)\n",
    "print()\n",
    "\n",
    "# 1. Train, Validation, and Test Split\n",
    "# First, we split the data into a training set and a temporary set (which will be further split into validation and test sets)\n",
    "X_train, X_temp, y_train, y_temp = train_test_split(X, y, test_size=0.4, random_state=42, shuffle=True)\n",
    "print(\"Training set:\", X_train.shape, y_train.shape)\n",
    "print(\"Temporary set:\", X_temp.shape, y_temp.shape)\n",
    "print()\n",
    "\n",
    "# Now, split the temporary set into validation and test sets\n",
    "X_valid, X_test, y_valid, y_test = train_test_split(X_temp, y_temp, test_size=0.5, random_state=42, shuffle=True)\n",
    "print(\"Training set:\", X_train.shape, y_train.shape)\n",
    "print(\"Validation set:\", X_valid.shape, y_valid.shape)\n",
    "print(\"Test set:\", X_test.shape, y_test.shape)\n",
    "print()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cross Validation\n",
    "Using KFold cross-validation iterator to split the dataset and train the model on each fold."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "KFold splits:\n",
      "Fold: 1\n",
      "Validation Fold: (18, 4) (18,)\n",
      "Validation Fold Index: [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17]\n",
      "Train Fold: (72, 4) (72,)\n",
      "Train Fold Index: [18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41\n",
      " 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65\n",
      " 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89]\n",
      "\n",
      "Fold: 2\n",
      "Validation Fold: (18, 4) (18,)\n",
      "Validation Fold Index: [18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35]\n",
      "Train Fold: (72, 4) (72,)\n",
      "Train Fold Index: [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 36 37 38 39 40 41\n",
      " 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65\n",
      " 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89]\n",
      "\n",
      "Fold: 3\n",
      "Validation Fold: (18, 4) (18,)\n",
      "Validation Fold Index: [36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53]\n",
      "Train Fold: (72, 4) (72,)\n",
      "Train Fold Index: [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23\n",
      " 24 25 26 27 28 29 30 31 32 33 34 35 54 55 56 57 58 59 60 61 62 63 64 65\n",
      " 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89]\n",
      "\n",
      "Fold: 4\n",
      "Validation Fold: (18, 4) (18,)\n",
      "Validation Fold Index: [54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71]\n",
      "Train Fold: (72, 4) (72,)\n",
      "Train Fold Index: [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23\n",
      " 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47\n",
      " 48 49 50 51 52 53 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89]\n",
      "\n",
      "Fold: 5\n",
      "Validation Fold: (18, 4) (18,)\n",
      "Validation Fold Index: [72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89]\n",
      "Train Fold: (72, 4) (72,)\n",
      "Train Fold Index: [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23\n",
      " 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47\n",
      " 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "kf = KFold(n_splits=5, shuffle=False)  # here we turn off shuffling to better understand the splits\n",
    "\n",
    "f_count = 0\n",
    "print(\"KFold splits:\")\n",
    "for train_index, val_index in kf.split(X_train):\n",
    "    \n",
    "    X_train_fold, X_val_fold = X_train.values[train_index], X_train.values[val_index]\n",
    "    y_train_fold, y_val_fold = y_train[train_index], y_train[val_index]\n",
    "    f_count += 1\n",
    "\n",
    "    print(\"Fold:\", f_count)\n",
    "    print(\"Validation Fold:\", X_val_fold.shape, y_val_fold.shape)\n",
    "    print(\"Validation Fold Index:\", val_index)\n",
    "    print(\"Train Fold:\", X_train_fold.shape, y_train_fold.shape)\n",
    "    print(\"Train Fold Index:\", train_index)\n",
    "    print()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we want to keep same class distribution in the splits as in the complete dataset use ``StratifiedKFold``"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stratified KFold splits:\n",
      "Fold: 1\n",
      "Validation Fold: (18, 4) (18,)\n",
      "Validation Fold Index: [ 0  1  2  3  4  5  6  7  8  9 10 12 13 14 15 16 17 20]\n",
      "Train Fold: (72, 4) (72,)\n",
      "Train Fold Index: [11 18 19 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41\n",
      " 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65\n",
      " 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89]\n",
      "\n",
      "Fold: 2\n",
      "Validation Fold: (18, 4) (18,)\n",
      "Validation Fold Index: [11 18 19 21 22 23 24 25 26 29 30 31 32 33 34 38 39 44]\n",
      "Train Fold: (72, 4) (72,)\n",
      "Train Fold Index: [ 0  1  2  3  4  5  6  7  8  9 10 12 13 14 15 16 17 20 27 28 35 36 37 40\n",
      " 41 42 43 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65\n",
      " 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89]\n",
      "\n",
      "Fold: 3\n",
      "Validation Fold: (18, 4) (18,)\n",
      "Validation Fold Index: [27 28 35 36 37 40 41 43 46 47 49 50 51 52 53 55 56 57]\n",
      "Train Fold: (72, 4) (72,)\n",
      "Train Fold Index: [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23\n",
      " 24 25 26 29 30 31 32 33 34 38 39 42 44 45 48 54 58 59 60 61 62 63 64 65\n",
      " 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89]\n",
      "\n",
      "Fold: 4\n",
      "Validation Fold: (18, 4) (18,)\n",
      "Validation Fold Index: [42 45 48 54 58 59 60 61 62 63 64 65 66 67 70 71 73 76]\n",
      "Train Fold: (72, 4) (72,)\n",
      "Train Fold Index: [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23\n",
      " 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 43 44 46 47 49 50\n",
      " 51 52 53 55 56 57 68 69 72 74 75 77 78 79 80 81 82 83 84 85 86 87 88 89]\n",
      "\n",
      "Fold: 5\n",
      "Validation Fold: (18, 4) (18,)\n",
      "Validation Fold Index: [68 69 72 74 75 77 78 79 80 81 82 83 84 85 86 87 88 89]\n",
      "Train Fold: (72, 4) (72,)\n",
      "Train Fold Index: [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23\n",
      " 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47\n",
      " 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 70 71 73 76]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# for a stratified KFold\n",
    "from sklearn.model_selection import StratifiedKFold\n",
    "\n",
    "skf = StratifiedKFold(n_splits=5, shuffle=False)  # here we turn off shuffling to better understand the splits\n",
    "\n",
    "f_count = 0\n",
    "print(\"Stratified KFold splits:\")\n",
    "for train_index, val_index in skf.split(X_train, y_train):\n",
    "    \n",
    "    X_train_fold, X_val_fold = X_train.values[train_index], X_train.values[val_index]\n",
    "    y_train_fold, y_val_fold = y_train[train_index], y_train[val_index]\n",
    "    f_count += 1\n",
    "\n",
    "    print(\"Fold:\", f_count)\n",
    "    print(\"Validation Fold:\", X_val_fold.shape, y_val_fold.shape)\n",
    "    print(\"Validation Fold Index:\", val_index)\n",
    "    print(\"Train Fold:\", X_train_fold.shape, y_train_fold.shape)\n",
    "    print(\"Train Fold Index:\", train_index)\n",
    "    print()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using leave one out cross validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Leave One Out splits:\n",
      "Total number of splits: 90\n"
     ]
    }
   ],
   "source": [
    "# leave one out cross validation\n",
    "from sklearn.model_selection import LeaveOneOut\n",
    "\n",
    "loo = LeaveOneOut()\n",
    "\n",
    "f_count = 0\n",
    "print(\"Leave One Out splits:\")\n",
    "for train_index, val_index in loo.split(X_train):\n",
    "    X_train_fold, X_val_fold = X_train.values[train_index], X_train.values[val_index]\n",
    "    y_train_fold, y_val_fold = y_train[train_index], y_train[val_index]\n",
    "    f_count += 1\n",
    "\n",
    "    # it will print a lot of output, so we will comment it out (uncomment if you want to see it)\n",
    "    # print(\"Fold:\", f_count)\n",
    "    # print(\"Validation Fold:\", X_val_fold.shape, y_val_fold.shape)\n",
    "    # print(\"Validation Fold Index:\", val_index)\n",
    "    # print(\"Train Fold:\", X_train_fold.shape, y_train_fold.shape)\n",
    "    # print(\"Train Fold Index:\", train_index)\n",
    "    # print()\n",
    "\n",
    "print(\"Total number of splits:\", f_count)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cross validation is also baked in into the function ``cross_val_score`` that creates the folds, fits the model and evaluates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cross-validation scores: [1.         0.77777778 1.         1.         0.94444444]\n",
      "Average cross-validation score: 0.9444444444444444\n"
     ]
    }
   ],
   "source": [
    "# Performing cross-validation to assess the generalization performance of the Logistic Regression model.\n",
    "log_reg = LogisticRegression(max_iter=200)\n",
    "cross_val_scores = cross_val_score(log_reg, X_train, y_train, cv=5)\n",
    "print(\"Cross-validation scores:\", cross_val_scores)\n",
    "print(\"Average cross-validation score:\", np.mean(cross_val_scores))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hyperparameter Tuning\n",
    "Using Grid Search and Random Search to find the best hyperparameters for the Logistic Regression model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best parameters from Grid Search: {'C': 1}\n"
     ]
    }
   ],
   "source": [
    "# Grid Search\n",
    "param_grid = {\n",
    "    'C': [0.01, 0.1, 1, 10, 100],  # Inverse of regularization strength\n",
    "}\n",
    "\n",
    "# func\n",
    "grid_search = GridSearchCV(log_reg, param_grid, cv=5)  # also includes cross-validation\n",
    "grid_search.fit(X_train, y_train)\n",
    "\n",
    "print(\"Best parameters from Grid Search:\", grid_search.best_params_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best parameters from Random Search: {'C': 100}\n"
     ]
    }
   ],
   "source": [
    "# Random Search\n",
    "param_dist = {\n",
    "    'C': [0.01, 0.1, 1, 10, 100],  # Regularization strength\n",
    "}\n",
    "\n",
    "random_search = RandomizedSearchCV(log_reg, param_distributions=param_dist, n_iter=3, random_state=42, cv=5)  # also includes cross-validation\n",
    "random_search.fit(X_train, y_train)\n",
    "\n",
    "print(\"Best parameters from Random Search:\", random_search.best_params_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Grid SearchExplores tests all combinations:\n",
    "- Exhaustive method.\n",
    "- Computationally expensive\n",
    "\n",
    "Random Search samples from the search space:\n",
    "- Faster and more efficient.\n",
    "- May miss the best possible combination\n",
    "\n",
    "In this case since the search space is small it is more likely for Random Search to find the same parameters as grid search. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Shuffling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original dataset\n",
      "Input Features: (90, 4) Index([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
      "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
      "       36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,\n",
      "       54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,\n",
      "       72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89],\n",
      "      dtype='int64')\n",
      "Target Features: (90,) [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      " 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
      " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1]\n",
      "\n",
      "Shuffled dataset\n",
      "Input Features: (90, 4) Index([40, 22, 55, 70,  0, 26, 39, 65, 10, 44, 81, 35, 56, 86, 12,  4, 18, 28,\n",
      "       49, 62, 73, 69, 76, 30, 33, 11, 66, 67, 31, 75,  9, 68,  5, 42, 47, 16,\n",
      "       45, 34,  7, 78, 27, 19, 84, 25, 53, 13, 24,  3, 17, 38,  8, 87,  6, 64,\n",
      "       36, 80, 89, 54, 43, 50, 46, 61, 88, 15, 72, 41, 58, 48, 79, 57, 32, 85,\n",
      "       59, 63, 77, 37, 29,  1, 52, 21,  2, 23, 83, 74, 82, 20, 60, 71, 14, 51],\n",
      "      dtype='int64')\n",
      "Target Features: (90,) [0 0 1 1 0 0 0 1 0 0 1 0 1 1 0 0 0 0 0 1 1 1 1 0 0 0 1 1 0 1 0 1 0 0 0 0 0\n",
      " 0 0 1 0 0 1 0 1 0 0 0 0 0 0 1 0 1 0 1 1 1 0 1 0 1 1 0 1 0 1 0 1 1 0 1 1 1\n",
      " 1 0 0 0 1 0 0 0 1 1 1 0 1 1 0 1]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# shuffle split without changing the original dataset\n",
    "\n",
    "# shuffling with numpy\n",
    "np.random.seed(42)\n",
    "\n",
    "# load the dataset\n",
    "data = load_iris()\n",
    "X = pd.DataFrame(data.data, columns=data.feature_names)\n",
    "y = data.target\n",
    "\n",
    "# split the dataset - we put shuffle=False to check what happens when we shuffle the dataset\n",
    "X_train, X_temp, y_train, y_temp = train_test_split(X, y, test_size=0.4, random_state=42, shuffle=False)\n",
    "\n",
    "print(\"Original dataset\")\n",
    "print(\"Input Features:\", X_train.shape, X_train.index)\n",
    "print(\"Target Features:\", y_train.shape, y_train)\n",
    "print()\n",
    "\n",
    "X_shuffled, y_shuffled = X_train.copy(), y_train.copy()\n",
    "np.random.seed(42)\n",
    "shuffle_indices = np.random.permutation(len(y_shuffled))\n",
    "X_shuffled, y_shuffled = X_shuffled.iloc[shuffle_indices], y_shuffled[shuffle_indices]\n",
    "\n",
    "print(\"Shuffled dataset\")\n",
    "print(\"Input Features:\", X_shuffled.shape, X_shuffled.index)\n",
    "print(\"Target Features:\", y_shuffled.shape, y_shuffled)\n",
    "print()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature Scaling\n",
    "Scaling features to improve the performance of many machine learning algorithms."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original dataset\n",
      "(90, 4)\n",
      "[[5.1 3.5 1.4 0.2]\n",
      " [4.9 3.  1.4 0.2]\n",
      " [4.7 3.2 1.3 0.2]\n",
      " [4.6 3.1 1.5 0.2]\n",
      " [5.  3.6 1.4 0.2]\n",
      " [5.4 3.9 1.7 0.4]\n",
      " [4.6 3.4 1.4 0.3]\n",
      " [5.  3.4 1.5 0.2]\n",
      " [4.4 2.9 1.4 0.2]\n",
      " [4.9 3.1 1.5 0.1]\n",
      " [5.4 3.7 1.5 0.2]\n",
      " [4.8 3.4 1.6 0.2]\n",
      " [4.8 3.  1.4 0.1]\n",
      " [4.3 3.  1.1 0.1]\n",
      " [5.8 4.  1.2 0.2]\n",
      " [5.7 4.4 1.5 0.4]\n",
      " [5.4 3.9 1.3 0.4]\n",
      " [5.1 3.5 1.4 0.3]\n",
      " [5.7 3.8 1.7 0.3]\n",
      " [5.1 3.8 1.5 0.3]\n",
      " [5.4 3.4 1.7 0.2]\n",
      " [5.1 3.7 1.5 0.4]\n",
      " [4.6 3.6 1.  0.2]\n",
      " [5.1 3.3 1.7 0.5]\n",
      " [4.8 3.4 1.9 0.2]\n",
      " [5.  3.  1.6 0.2]\n",
      " [5.  3.4 1.6 0.4]\n",
      " [5.2 3.5 1.5 0.2]\n",
      " [5.2 3.4 1.4 0.2]\n",
      " [4.7 3.2 1.6 0.2]\n",
      " [4.8 3.1 1.6 0.2]\n",
      " [5.4 3.4 1.5 0.4]\n",
      " [5.2 4.1 1.5 0.1]\n",
      " [5.5 4.2 1.4 0.2]\n",
      " [4.9 3.1 1.5 0.2]\n",
      " [5.  3.2 1.2 0.2]\n",
      " [5.5 3.5 1.3 0.2]\n",
      " [4.9 3.6 1.4 0.1]\n",
      " [4.4 3.  1.3 0.2]\n",
      " [5.1 3.4 1.5 0.2]\n",
      " [5.  3.5 1.3 0.3]\n",
      " [4.5 2.3 1.3 0.3]\n",
      " [4.4 3.2 1.3 0.2]\n",
      " [5.  3.5 1.6 0.6]\n",
      " [5.1 3.8 1.9 0.4]\n",
      " [4.8 3.  1.4 0.3]\n",
      " [5.1 3.8 1.6 0.2]\n",
      " [4.6 3.2 1.4 0.2]\n",
      " [5.3 3.7 1.5 0.2]\n",
      " [5.  3.3 1.4 0.2]\n",
      " [7.  3.2 4.7 1.4]\n",
      " [6.4 3.2 4.5 1.5]\n",
      " [6.9 3.1 4.9 1.5]\n",
      " [5.5 2.3 4.  1.3]\n",
      " [6.5 2.8 4.6 1.5]\n",
      " [5.7 2.8 4.5 1.3]\n",
      " [6.3 3.3 4.7 1.6]\n",
      " [4.9 2.4 3.3 1. ]\n",
      " [6.6 2.9 4.6 1.3]\n",
      " [5.2 2.7 3.9 1.4]\n",
      " [5.  2.  3.5 1. ]\n",
      " [5.9 3.  4.2 1.5]\n",
      " [6.  2.2 4.  1. ]\n",
      " [6.1 2.9 4.7 1.4]\n",
      " [5.6 2.9 3.6 1.3]\n",
      " [6.7 3.1 4.4 1.4]\n",
      " [5.6 3.  4.5 1.5]\n",
      " [5.8 2.7 4.1 1. ]\n",
      " [6.2 2.2 4.5 1.5]\n",
      " [5.6 2.5 3.9 1.1]\n",
      " [5.9 3.2 4.8 1.8]\n",
      " [6.1 2.8 4.  1.3]\n",
      " [6.3 2.5 4.9 1.5]\n",
      " [6.1 2.8 4.7 1.2]\n",
      " [6.4 2.9 4.3 1.3]\n",
      " [6.6 3.  4.4 1.4]\n",
      " [6.8 2.8 4.8 1.4]\n",
      " [6.7 3.  5.  1.7]\n",
      " [6.  2.9 4.5 1.5]\n",
      " [5.7 2.6 3.5 1. ]\n",
      " [5.5 2.4 3.8 1.1]\n",
      " [5.5 2.4 3.7 1. ]\n",
      " [5.8 2.7 3.9 1.2]\n",
      " [6.  2.7 5.1 1.6]\n",
      " [5.4 3.  4.5 1.5]\n",
      " [6.  3.4 4.5 1.6]\n",
      " [6.7 3.1 4.7 1.5]\n",
      " [6.3 2.3 4.4 1.3]\n",
      " [5.6 3.  4.1 1.3]\n",
      " [5.5 2.5 4.  1.3]]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Original dataset features\n",
    "print(\"Original dataset\")\n",
    "print(X_train.shape)\n",
    "print(np.array(X_train))\n",
    "print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Standardized training set\n",
      "(90, 4)\n",
      "[[-0.53393871  0.75072443 -0.91465946 -0.94042762]\n",
      " [-0.83712157 -0.29194839 -0.91465946 -0.94042762]\n",
      " [-1.14030443  0.12512074 -0.98337345 -0.94042762]\n",
      " [-1.29189586 -0.08341383 -0.84594548 -0.94042762]\n",
      " [-0.68553014  0.95925899 -0.91465946 -0.94042762]\n",
      " [-0.07916441  1.58486268 -0.70851751 -0.5899577 ]\n",
      " [-1.29189586  0.54218986 -0.91465946 -0.76519266]\n",
      " [-0.68553014  0.54218986 -0.84594548 -0.94042762]\n",
      " [-1.59507873 -0.50048295 -0.91465946 -0.94042762]\n",
      " [-0.83712157 -0.08341383 -0.84594548 -1.11566258]\n",
      " [-0.07916441  1.16779355 -0.84594548 -0.94042762]\n",
      " [-0.988713    0.54218986 -0.7772315  -0.94042762]\n",
      " [-0.988713   -0.29194839 -0.91465946 -1.11566258]\n",
      " [-1.74667016 -0.29194839 -1.12080141 -1.11566258]\n",
      " [ 0.52720131  1.79339724 -1.05208743 -0.94042762]\n",
      " [ 0.37560988  2.6275355  -0.84594548 -0.5899577 ]\n",
      " [-0.07916441  1.58486268 -0.98337345 -0.5899577 ]\n",
      " [-0.53393871  0.75072443 -0.91465946 -0.76519266]\n",
      " [ 0.37560988  1.37632812 -0.70851751 -0.76519266]\n",
      " [-0.53393871  1.37632812 -0.84594548 -0.76519266]\n",
      " [-0.07916441  0.54218986 -0.70851751 -0.94042762]\n",
      " [-0.53393871  1.16779355 -0.84594548 -0.5899577 ]\n",
      " [-1.29189586  0.95925899 -1.18951539 -0.94042762]\n",
      " [-0.53393871  0.3336553  -0.70851751 -0.41472274]\n",
      " [-0.988713    0.54218986 -0.57108955 -0.94042762]\n",
      " [-0.68553014 -0.29194839 -0.7772315  -0.94042762]\n",
      " [-0.68553014  0.54218986 -0.7772315  -0.5899577 ]\n",
      " [-0.38234728  0.75072443 -0.84594548 -0.94042762]\n",
      " [-0.38234728  0.54218986 -0.91465946 -0.94042762]\n",
      " [-1.14030443  0.12512074 -0.7772315  -0.94042762]\n",
      " [-0.988713   -0.08341383 -0.7772315  -0.94042762]\n",
      " [-0.07916441  0.54218986 -0.84594548 -0.5899577 ]\n",
      " [-0.38234728  2.00193181 -0.84594548 -1.11566258]\n",
      " [ 0.07242702  2.21046637 -0.91465946 -0.94042762]\n",
      " [-0.83712157 -0.08341383 -0.84594548 -0.94042762]\n",
      " [-0.68553014  0.12512074 -1.05208743 -0.94042762]\n",
      " [ 0.07242702  0.75072443 -0.98337345 -0.94042762]\n",
      " [-0.83712157  0.95925899 -0.91465946 -1.11566258]\n",
      " [-1.59507873 -0.29194839 -0.98337345 -0.94042762]\n",
      " [-0.53393871  0.54218986 -0.84594548 -0.94042762]\n",
      " [-0.68553014  0.75072443 -0.98337345 -0.76519266]\n",
      " [-1.4434873  -1.75169033 -0.98337345 -0.76519266]\n",
      " [-1.59507873  0.12512074 -0.98337345 -0.94042762]\n",
      " [-0.68553014  0.75072443 -0.7772315  -0.23948778]\n",
      " [-0.53393871  1.37632812 -0.57108955 -0.5899577 ]\n",
      " [-0.988713   -0.29194839 -0.91465946 -0.76519266]\n",
      " [-0.53393871  1.37632812 -0.7772315  -0.94042762]\n",
      " [-1.29189586  0.12512074 -0.91465946 -0.94042762]\n",
      " [-0.23075585  1.16779355 -0.84594548 -0.94042762]\n",
      " [-0.68553014  0.3336553  -0.91465946 -0.94042762]\n",
      " [ 2.34629849  0.12512074  1.35290198  1.1623919 ]\n",
      " [ 1.4367499   0.12512074  1.21547401  1.33762686]\n",
      " [ 2.19470706 -0.08341383  1.49032994  1.33762686]\n",
      " [ 0.07242702 -1.75169033  0.8719041   0.98715694]\n",
      " [ 1.58834133 -0.70901752  1.28418799  1.33762686]\n",
      " [ 0.37560988 -0.70901752  1.21547401  0.98715694]\n",
      " [ 1.28515847  0.3336553   1.35290198  1.51286182]\n",
      " [-0.83712157 -1.54315577  0.39090621  0.46145206]\n",
      " [ 1.73993276 -0.50048295  1.28418799  0.98715694]\n",
      " [-0.38234728 -0.91755208  0.80319011  1.1623919 ]\n",
      " [-0.68553014 -2.37729402  0.52833418  0.46145206]\n",
      " [ 0.67879274 -0.29194839  1.00933206  1.33762686]\n",
      " [ 0.83038417 -1.96022489  0.8719041   0.46145206]\n",
      " [ 0.9819756  -0.50048295  1.35290198  1.1623919 ]\n",
      " [ 0.22401845 -0.50048295  0.59704816  0.98715694]\n",
      " [ 1.89152419 -0.08341383  1.14676003  1.1623919 ]\n",
      " [ 0.22401845 -0.29194839  1.21547401  1.33762686]\n",
      " [ 0.52720131 -0.91755208  0.94061808  0.46145206]\n",
      " [ 1.13356704 -1.96022489  1.21547401  1.33762686]\n",
      " [ 0.22401845 -1.33462121  0.80319011  0.63668702]\n",
      " [ 0.67879274  0.12512074  1.42161596  1.86333174]\n",
      " [ 0.9819756  -0.70901752  0.8719041   0.98715694]\n",
      " [ 1.28515847 -1.33462121  1.49032994  1.33762686]\n",
      " [ 0.9819756  -0.70901752  1.35290198  0.81192198]\n",
      " [ 1.4367499  -0.50048295  1.07804604  0.98715694]\n",
      " [ 1.73993276 -0.29194839  1.14676003  1.1623919 ]\n",
      " [ 2.04311562 -0.70901752  1.42161596  1.1623919 ]\n",
      " [ 1.89152419 -0.29194839  1.55904392  1.68809678]\n",
      " [ 0.83038417 -0.50048295  1.21547401  1.33762686]\n",
      " [ 0.37560988 -1.12608664  0.52833418  0.46145206]\n",
      " [ 0.07242702 -1.54315577  0.73447613  0.63668702]\n",
      " [ 0.07242702 -1.54315577  0.66576215  0.46145206]\n",
      " [ 0.52720131 -0.91755208  0.80319011  0.81192198]\n",
      " [ 0.83038417 -0.91755208  1.62775791  1.51286182]\n",
      " [-0.07916441 -0.29194839  1.21547401  1.33762686]\n",
      " [ 0.83038417  0.54218986  1.21547401  1.51286182]\n",
      " [ 1.89152419 -0.08341383  1.35290198  1.33762686]\n",
      " [ 1.28515847 -1.75169033  1.14676003  0.98715694]\n",
      " [ 0.22401845 -0.29194839  0.94061808  0.98715694]\n",
      " [ 0.07242702 -1.33462121  0.8719041   0.98715694]]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Standardization (zero mean, unit variance)\n",
    "scaler_standard = StandardScaler()\n",
    "X_train_standard = scaler_standard.fit_transform(X_train)\n",
    "X_test_standard = scaler_standard.transform(X_test)\n",
    "\n",
    "print(\"Standardized training set\")\n",
    "print(X_train_standard.shape)\n",
    "print(X_train_standard)\n",
    "print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Normalized training set\n",
      "(90, 4)\n",
      "[[0.2962963  0.625      0.09756098 0.05882353]\n",
      " [0.22222222 0.41666667 0.09756098 0.05882353]\n",
      " [0.14814815 0.5        0.07317073 0.05882353]\n",
      " [0.11111111 0.45833333 0.12195122 0.05882353]\n",
      " [0.25925926 0.66666667 0.09756098 0.05882353]\n",
      " [0.40740741 0.79166667 0.17073171 0.17647059]\n",
      " [0.11111111 0.58333333 0.09756098 0.11764706]\n",
      " [0.25925926 0.58333333 0.12195122 0.05882353]\n",
      " [0.03703704 0.375      0.09756098 0.05882353]\n",
      " [0.22222222 0.45833333 0.12195122 0.        ]\n",
      " [0.40740741 0.70833333 0.12195122 0.05882353]\n",
      " [0.18518519 0.58333333 0.14634146 0.05882353]\n",
      " [0.18518519 0.41666667 0.09756098 0.        ]\n",
      " [0.         0.41666667 0.02439024 0.        ]\n",
      " [0.55555556 0.83333333 0.04878049 0.05882353]\n",
      " [0.51851852 1.         0.12195122 0.17647059]\n",
      " [0.40740741 0.79166667 0.07317073 0.17647059]\n",
      " [0.2962963  0.625      0.09756098 0.11764706]\n",
      " [0.51851852 0.75       0.17073171 0.11764706]\n",
      " [0.2962963  0.75       0.12195122 0.11764706]\n",
      " [0.40740741 0.58333333 0.17073171 0.05882353]\n",
      " [0.2962963  0.70833333 0.12195122 0.17647059]\n",
      " [0.11111111 0.66666667 0.         0.05882353]\n",
      " [0.2962963  0.54166667 0.17073171 0.23529412]\n",
      " [0.18518519 0.58333333 0.2195122  0.05882353]\n",
      " [0.25925926 0.41666667 0.14634146 0.05882353]\n",
      " [0.25925926 0.58333333 0.14634146 0.17647059]\n",
      " [0.33333333 0.625      0.12195122 0.05882353]\n",
      " [0.33333333 0.58333333 0.09756098 0.05882353]\n",
      " [0.14814815 0.5        0.14634146 0.05882353]\n",
      " [0.18518519 0.45833333 0.14634146 0.05882353]\n",
      " [0.40740741 0.58333333 0.12195122 0.17647059]\n",
      " [0.33333333 0.875      0.12195122 0.        ]\n",
      " [0.44444444 0.91666667 0.09756098 0.05882353]\n",
      " [0.22222222 0.45833333 0.12195122 0.05882353]\n",
      " [0.25925926 0.5        0.04878049 0.05882353]\n",
      " [0.44444444 0.625      0.07317073 0.05882353]\n",
      " [0.22222222 0.66666667 0.09756098 0.        ]\n",
      " [0.03703704 0.41666667 0.07317073 0.05882353]\n",
      " [0.2962963  0.58333333 0.12195122 0.05882353]\n",
      " [0.25925926 0.625      0.07317073 0.11764706]\n",
      " [0.07407407 0.125      0.07317073 0.11764706]\n",
      " [0.03703704 0.5        0.07317073 0.05882353]\n",
      " [0.25925926 0.625      0.14634146 0.29411765]\n",
      " [0.2962963  0.75       0.2195122  0.17647059]\n",
      " [0.18518519 0.41666667 0.09756098 0.11764706]\n",
      " [0.2962963  0.75       0.14634146 0.05882353]\n",
      " [0.11111111 0.5        0.09756098 0.05882353]\n",
      " [0.37037037 0.70833333 0.12195122 0.05882353]\n",
      " [0.25925926 0.54166667 0.09756098 0.05882353]\n",
      " [1.         0.5        0.90243902 0.76470588]\n",
      " [0.77777778 0.5        0.85365854 0.82352941]\n",
      " [0.96296296 0.45833333 0.95121951 0.82352941]\n",
      " [0.44444444 0.125      0.73170732 0.70588235]\n",
      " [0.81481481 0.33333333 0.87804878 0.82352941]\n",
      " [0.51851852 0.33333333 0.85365854 0.70588235]\n",
      " [0.74074074 0.54166667 0.90243902 0.88235294]\n",
      " [0.22222222 0.16666667 0.56097561 0.52941176]\n",
      " [0.85185185 0.375      0.87804878 0.70588235]\n",
      " [0.33333333 0.29166667 0.70731707 0.76470588]\n",
      " [0.25925926 0.         0.6097561  0.52941176]\n",
      " [0.59259259 0.41666667 0.7804878  0.82352941]\n",
      " [0.62962963 0.08333333 0.73170732 0.52941176]\n",
      " [0.66666667 0.375      0.90243902 0.76470588]\n",
      " [0.48148148 0.375      0.63414634 0.70588235]\n",
      " [0.88888889 0.45833333 0.82926829 0.76470588]\n",
      " [0.48148148 0.41666667 0.85365854 0.82352941]\n",
      " [0.55555556 0.29166667 0.75609756 0.52941176]\n",
      " [0.7037037  0.08333333 0.85365854 0.82352941]\n",
      " [0.48148148 0.20833333 0.70731707 0.58823529]\n",
      " [0.59259259 0.5        0.92682927 1.        ]\n",
      " [0.66666667 0.33333333 0.73170732 0.70588235]\n",
      " [0.74074074 0.20833333 0.95121951 0.82352941]\n",
      " [0.66666667 0.33333333 0.90243902 0.64705882]\n",
      " [0.77777778 0.375      0.80487805 0.70588235]\n",
      " [0.85185185 0.41666667 0.82926829 0.76470588]\n",
      " [0.92592593 0.33333333 0.92682927 0.76470588]\n",
      " [0.88888889 0.41666667 0.97560976 0.94117647]\n",
      " [0.62962963 0.375      0.85365854 0.82352941]\n",
      " [0.51851852 0.25       0.6097561  0.52941176]\n",
      " [0.44444444 0.16666667 0.68292683 0.58823529]\n",
      " [0.44444444 0.16666667 0.65853659 0.52941176]\n",
      " [0.55555556 0.29166667 0.70731707 0.64705882]\n",
      " [0.62962963 0.29166667 1.         0.88235294]\n",
      " [0.40740741 0.41666667 0.85365854 0.82352941]\n",
      " [0.62962963 0.58333333 0.85365854 0.88235294]\n",
      " [0.88888889 0.45833333 0.90243902 0.82352941]\n",
      " [0.74074074 0.125      0.82926829 0.70588235]\n",
      " [0.48148148 0.41666667 0.75609756 0.70588235]\n",
      " [0.44444444 0.20833333 0.73170732 0.70588235]]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Normalization (min-max scaling to range [0, 1])\n",
    "scaler_minmax = MinMaxScaler()\n",
    "X_train_minmax = scaler_minmax.fit_transform(X_train)\n",
    "X_test_minmax = scaler_minmax.transform(X_test)\n",
    "\n",
    "print(\"Normalized training set\")\n",
    "print(X_train_minmax.shape)\n",
    "print(X_train_minmax)\n",
    "print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1200x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting distributions of features before scaling\n",
    "plt.figure(figsize=(12, 6))\n",
    "for i, feature in enumerate(X.columns, 1):\n",
    "    plt.subplot(2, 2, i)\n",
    "    sns.histplot(X_train[feature], bins=10, kde=True)\n",
    "    plt.title(f'Distribution of {feature}')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1200x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting features after standardization\n",
    "plt.figure(figsize=(12, 6))\n",
    "for i, feature in enumerate(X.columns, 1):\n",
    "    plt.subplot(2, 2, i)\n",
    "    sns.histplot(X_train_standard[:, i-1], bins=10, kde=True)\n",
    "    plt.title(f'Standardized {feature}')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1200x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting features after normalization\n",
    "plt.figure(figsize=(12, 6))\n",
    "for i, feature in enumerate(X.columns, 1):\n",
    "    plt.subplot(2, 2, i)\n",
    "    sns.histplot(X_train_minmax[:, i-1], bins=10, kde=True)\n",
    "    plt.title(f'Normalized {feature}')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Handling Categorical Data\n",
    "Converting categorical variables into a format suitable for machine learning algorithms.\n",
    "\n",
    "We will be using a toy example since iris dataset does not have categorical variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original dataset\n",
      "   Color Size\n",
      "0    Red    S\n",
      "1  Green    M\n",
      "2   Blue    L\n",
      "3  Green   XL\n",
      "4    Red    M\n",
      "Encoded dataset\n",
      "[[0. 0. 1. 0. 0. 1. 0.]\n",
      " [0. 1. 0. 0. 1. 0. 0.]\n",
      " [1. 0. 0. 1. 0. 0. 0.]\n",
      " [0. 1. 0. 0. 0. 0. 1.]\n",
      " [0. 0. 1. 0. 1. 0. 0.]]\n"
     ]
    }
   ],
   "source": [
    "# One-Hot Encoding\n",
    "# Creating a small categorical dataset and applying one-hot encoding to convert categorical variables into binary columns.\n",
    "cat_data = pd.DataFrame({\n",
    "    'Color': ['Red', 'Green', 'Blue', 'Green', 'Red'],\n",
    "    'Size': ['S', 'M', 'L', 'XL', 'M']\n",
    "})\n",
    "\n",
    "print(\"Original dataset\")\n",
    "print(cat_data)\n",
    "\n",
    "# One-hot encoding using sklearn\n",
    "encoder = OneHotEncoder()\n",
    "\n",
    "# Fit and transform the data\n",
    "cat_data_encoded = encoder.fit_transform(cat_data).toarray()\n",
    "\n",
    "print(\"Encoded dataset\")\n",
    "print(cat_data_encoded)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One can also use pandas for this"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Encoded dataset\n",
      "   Color_Blue  Color_Green  Color_Red  Size_L  Size_M  Size_S  Size_XL\n",
      "0       False        False       True   False   False    True    False\n",
      "1       False         True      False   False    True   False    False\n",
      "2        True        False      False    True   False   False    False\n",
      "3       False         True      False   False   False   False     True\n",
      "4       False        False       True   False    True   False    False\n"
     ]
    }
   ],
   "source": [
    "# one hot encoding with pandas\n",
    "cat_data_encoded = pd.get_dummies(cat_data)\n",
    "\n",
    "print(\"Encoded dataset\")\n",
    "print(cat_data_encoded)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original dataset\n",
      "   Color Size\n",
      "0    Red    S\n",
      "1  Green    M\n",
      "2   Blue    L\n",
      "3  Green   XL\n",
      "4    Red    M\n",
      "Encoded dataset\n",
      "   Color  Size\n",
      "0      2     2\n",
      "1      1     1\n",
      "2      0     0\n",
      "3      1     3\n",
      "4      2     1\n"
     ]
    }
   ],
   "source": [
    "# label encoding\n",
    "# Creating a small categorical dataset and applying label encoding to convert categorical variables into numerical ones.\n",
    "cat_data = pd.DataFrame({\n",
    "    'Color': ['Red', 'Green', 'Blue', 'Green', 'Red'],\n",
    "    'Size': ['S', 'M', 'L', 'XL', 'M']\n",
    "})\n",
    "\n",
    "print(\"Original dataset\")\n",
    "print(cat_data)\n",
    "\n",
    "# Label encoding using sklearn\n",
    "encoder = LabelEncoder()\n",
    "\n",
    "# Fit and transform the data\n",
    "cat_data_encoded = cat_data.apply(encoder.fit_transform)\n",
    "\n",
    "print(\"Encoded dataset\")\n",
    "print(cat_data_encoded)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Encoded dataset\n",
      "   Color  Size\n",
      "0      2     2\n",
      "1      1     1\n",
      "2      0     0\n",
      "3      1     3\n",
      "4      2     1\n"
     ]
    }
   ],
   "source": [
    "# label encoding with pandas\n",
    "cat_data_encoded = cat_data.copy()\n",
    "\n",
    "for col in cat_data.columns:\n",
    "    cat_data_encoded[col] = cat_data[col].astype('category').cat.codes\n",
    "\n",
    "print(\"Encoded dataset\")\n",
    "print(cat_data_encoded)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Feature Selection"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Filter Methods\n",
    "Evaluate features based on statistical tests."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Correlation\n",
    "# Computing the correlation matrix to identify the relationships between features.\n",
    "correlation_matrix = X.corr()\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt='.2f')\n",
    "plt.title(\"Correlation Matrix\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature: sepal length (cm), Score: 10.817820878494002, Selected: False\n",
      "Feature: sepal width (cm), Score: 3.7107283035324965, Selected: False\n",
      "Feature: petal length (cm), Score: 116.31261309207025, Selected: True\n",
      "Feature: petal width (cm), Score: 67.04836020011118, Selected: True\n"
     ]
    }
   ],
   "source": [
    "# Chi-Squared Test\n",
    "# Applying the chi-squared test to select features based on their statistical relationship with the target variable.\n",
    "chi2_selector = SelectKBest(chi2, k=2)\n",
    "\n",
    "# Fit and transform the data\n",
    "X_new = chi2_selector.fit_transform(X, y)\n",
    "\n",
    "# print feature name, score, and whether it was selected or not\n",
    "for i in range(len(data.feature_names)):\n",
    "    print(f\"Feature: {data.feature_names[i]}, Score: {chi2_selector.scores_[i]}, Selected: {chi2_selector.get_support()[i]}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Wrapper Methods\n",
    "Use a specific model to evaluate subsets of features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Selected features using RFE:\n",
      " Index(['petal length (cm)', 'petal width (cm)'], dtype='object')\n"
     ]
    }
   ],
   "source": [
    "# Recursive Feature Elimination (RFE)\n",
    "model_rfe = LogReg()\n",
    "rfe = RFE(estimator=model_rfe, n_features_to_select=2)\n",
    "rfe.fit(X_train, y_train)\n",
    "\n",
    "print(\"Selected features using RFE:\\n\", X.columns[rfe.support_])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Putting Everything Together (Test time)\n",
    "\n",
    "Now that we tested various processing techiques let's apply a full example combining everything and check the performance on the test set.\n",
    "\n",
    "Experiment with different combinations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best parameters from Grid Search: {'C': 1}\n",
      "Best score from Grid Search: 0.9333333333333333\n",
      "Validation Accuracy: 1.0\n",
      "Test Accuracy: 0.9666666666666667\n"
     ]
    }
   ],
   "source": [
    "# load the dataset\n",
    "data = load_iris()\n",
    "\n",
    "# split the dataset\n",
    "X = pd.DataFrame(data.data, columns=data.feature_names)\n",
    "\n",
    "# apply feature scaling\n",
    "scaler = StandardScaler()\n",
    "X_scaled = scaler.fit_transform(X)\n",
    "\n",
    "# create the splits\n",
    "X_train, X_temp, y_train, y_temp = train_test_split(X_scaled, y, test_size=0.4, random_state=42, shuffle=True)\n",
    "X_valid, X_test, y_valid, y_test = train_test_split(X_temp, y_temp, test_size=0.5, random_state=42, shuffle=True)\n",
    "\n",
    "# apply hyperparameter tuning using Grid Search with cross-validation\n",
    "param_grid = {\n",
    "    'C': [0.01, 0.1, 1, 10, 100],\n",
    "}\n",
    "\n",
    "# create the model\n",
    "log_reg = LogisticRegression(max_iter=200)\n",
    "\n",
    "# create the grid search\n",
    "grid_search = GridSearchCV(log_reg, param_grid, cv=5)\n",
    "\n",
    "# fit the model\n",
    "grid_search.fit(X_train, y_train)\n",
    "print(\"Best parameters from Grid Search:\", grid_search.best_params_)\n",
    "print(\"Best score from Grid Search:\", grid_search.best_score_)\n",
    "\n",
    "# evaluate the model on the validation set\n",
    "y_valid_pred = grid_search.predict(X_valid)\n",
    "accuracy = accuracy_score(y_valid, y_valid_pred)\n",
    "print(\"Validation Accuracy:\", accuracy)\n",
    "\n",
    "# evaluate the model on the test set\n",
    "y_test_pred = grid_search.predict(X_test)\n",
    "accuracy = accuracy_score(y_test, y_test_pred)\n",
    "print(\"Test Accuracy:\", accuracy)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Unsupervised Learning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import necessary libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.datasets import load_iris\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.manifold import TSNE\n",
    "from sklearn.cluster import KMeans, DBSCAN, AgglomerativeClustering\n",
    "from sklearn.metrics import silhouette_score\n",
    "from scipy.cluster.hierarchy import dendrogram, linkage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original dataset\n",
      "Input Features: (150, 4)\n",
      "Target Features: (150,)\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>sepal length (cm)</th>\n",
       "      <th>sepal width (cm)</th>\n",
       "      <th>petal length (cm)</th>\n",
       "      <th>petal width (cm)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>6.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>6.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>5.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     sepal length (cm)  sepal width (cm)  petal length (cm)  petal width (cm)\n",
       "0                  5.1               3.5                1.4               0.2\n",
       "1                  4.9               3.0                1.4               0.2\n",
       "2                  4.7               3.2                1.3               0.2\n",
       "3                  4.6               3.1                1.5               0.2\n",
       "4                  5.0               3.6                1.4               0.2\n",
       "..                 ...               ...                ...               ...\n",
       "145                6.7               3.0                5.2               2.3\n",
       "146                6.3               2.5                5.0               1.9\n",
       "147                6.5               3.0                5.2               2.0\n",
       "148                6.2               3.4                5.4               2.3\n",
       "149                5.9               3.0                5.1               1.8\n",
       "\n",
       "[150 rows x 4 columns]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load the Iris dataset\n",
    "data = load_iris()\n",
    "X = pd.DataFrame(data.data, columns=data.feature_names)\n",
    "y = data.target\n",
    "\n",
    "print(\"Original dataset\")\n",
    "print(\"Input Features:\", X.shape)\n",
    "print(\"Target Features:\", y.shape)\n",
    "\n",
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-9.00681170e-01,  1.01900435e+00, -1.34022653e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.14301691e+00, -1.31979479e-01, -1.34022653e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.38535265e+00,  3.28414053e-01, -1.39706395e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.50652052e+00,  9.82172869e-02, -1.28338910e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.02184904e+00,  1.24920112e+00, -1.34022653e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-5.37177559e-01,  1.93979142e+00, -1.16971425e+00,\n",
       "        -1.05217993e+00],\n",
       "       [-1.50652052e+00,  7.88807586e-01, -1.34022653e+00,\n",
       "        -1.18381211e+00],\n",
       "       [-1.02184904e+00,  7.88807586e-01, -1.28338910e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.74885626e+00, -3.62176246e-01, -1.34022653e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.14301691e+00,  9.82172869e-02, -1.28338910e+00,\n",
       "        -1.44707648e+00],\n",
       "       [-5.37177559e-01,  1.47939788e+00, -1.28338910e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.26418478e+00,  7.88807586e-01, -1.22655167e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.26418478e+00, -1.31979479e-01, -1.34022653e+00,\n",
       "        -1.44707648e+00],\n",
       "       [-1.87002413e+00, -1.31979479e-01, -1.51073881e+00,\n",
       "        -1.44707648e+00],\n",
       "       [-5.25060772e-02,  2.16998818e+00, -1.45390138e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.73673948e-01,  3.09077525e+00, -1.28338910e+00,\n",
       "        -1.05217993e+00],\n",
       "       [-5.37177559e-01,  1.93979142e+00, -1.39706395e+00,\n",
       "        -1.05217993e+00],\n",
       "       [-9.00681170e-01,  1.01900435e+00, -1.34022653e+00,\n",
       "        -1.18381211e+00],\n",
       "       [-1.73673948e-01,  1.70959465e+00, -1.16971425e+00,\n",
       "        -1.18381211e+00],\n",
       "       [-9.00681170e-01,  1.70959465e+00, -1.28338910e+00,\n",
       "        -1.18381211e+00],\n",
       "       [-5.37177559e-01,  7.88807586e-01, -1.16971425e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-9.00681170e-01,  1.47939788e+00, -1.28338910e+00,\n",
       "        -1.05217993e+00],\n",
       "       [-1.50652052e+00,  1.24920112e+00, -1.56757623e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-9.00681170e-01,  5.58610819e-01, -1.16971425e+00,\n",
       "        -9.20547742e-01],\n",
       "       [-1.26418478e+00,  7.88807586e-01, -1.05603939e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.02184904e+00, -1.31979479e-01, -1.22655167e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.02184904e+00,  7.88807586e-01, -1.22655167e+00,\n",
       "        -1.05217993e+00],\n",
       "       [-7.79513300e-01,  1.01900435e+00, -1.28338910e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-7.79513300e-01,  7.88807586e-01, -1.34022653e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.38535265e+00,  3.28414053e-01, -1.22655167e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.26418478e+00,  9.82172869e-02, -1.22655167e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-5.37177559e-01,  7.88807586e-01, -1.28338910e+00,\n",
       "        -1.05217993e+00],\n",
       "       [-7.79513300e-01,  2.40018495e+00, -1.28338910e+00,\n",
       "        -1.44707648e+00],\n",
       "       [-4.16009689e-01,  2.63038172e+00, -1.34022653e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.14301691e+00,  9.82172869e-02, -1.28338910e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.02184904e+00,  3.28414053e-01, -1.45390138e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-4.16009689e-01,  1.01900435e+00, -1.39706395e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.14301691e+00,  1.24920112e+00, -1.34022653e+00,\n",
       "        -1.44707648e+00],\n",
       "       [-1.74885626e+00, -1.31979479e-01, -1.39706395e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-9.00681170e-01,  7.88807586e-01, -1.28338910e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.02184904e+00,  1.01900435e+00, -1.39706395e+00,\n",
       "        -1.18381211e+00],\n",
       "       [-1.62768839e+00, -1.74335684e+00, -1.39706395e+00,\n",
       "        -1.18381211e+00],\n",
       "       [-1.74885626e+00,  3.28414053e-01, -1.39706395e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.02184904e+00,  1.01900435e+00, -1.22655167e+00,\n",
       "        -7.88915558e-01],\n",
       "       [-9.00681170e-01,  1.70959465e+00, -1.05603939e+00,\n",
       "        -1.05217993e+00],\n",
       "       [-1.26418478e+00, -1.31979479e-01, -1.34022653e+00,\n",
       "        -1.18381211e+00],\n",
       "       [-9.00681170e-01,  1.70959465e+00, -1.22655167e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.50652052e+00,  3.28414053e-01, -1.34022653e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-6.58345429e-01,  1.47939788e+00, -1.28338910e+00,\n",
       "        -1.31544430e+00],\n",
       "       [-1.02184904e+00,  5.58610819e-01, -1.34022653e+00,\n",
       "        -1.31544430e+00],\n",
       "       [ 1.40150837e+00,  3.28414053e-01,  5.35408562e-01,\n",
       "         2.64141916e-01],\n",
       "       [ 6.74501145e-01,  3.28414053e-01,  4.21733708e-01,\n",
       "         3.95774101e-01],\n",
       "       [ 1.28034050e+00,  9.82172869e-02,  6.49083415e-01,\n",
       "         3.95774101e-01],\n",
       "       [-4.16009689e-01, -1.74335684e+00,  1.37546573e-01,\n",
       "         1.32509732e-01],\n",
       "       [ 7.95669016e-01, -5.92373012e-01,  4.78571135e-01,\n",
       "         3.95774101e-01],\n",
       "       [-1.73673948e-01, -5.92373012e-01,  4.21733708e-01,\n",
       "         1.32509732e-01],\n",
       "       [ 5.53333275e-01,  5.58610819e-01,  5.35408562e-01,\n",
       "         5.27406285e-01],\n",
       "       [-1.14301691e+00, -1.51316008e+00, -2.60315415e-01,\n",
       "        -2.62386821e-01],\n",
       "       [ 9.16836886e-01, -3.62176246e-01,  4.78571135e-01,\n",
       "         1.32509732e-01],\n",
       "       [-7.79513300e-01, -8.22569778e-01,  8.07091462e-02,\n",
       "         2.64141916e-01],\n",
       "       [-1.02184904e+00, -2.43394714e+00, -1.46640561e-01,\n",
       "        -2.62386821e-01],\n",
       "       [ 6.86617933e-02, -1.31979479e-01,  2.51221427e-01,\n",
       "         3.95774101e-01],\n",
       "       [ 1.89829664e-01, -1.97355361e+00,  1.37546573e-01,\n",
       "        -2.62386821e-01],\n",
       "       [ 3.10997534e-01, -3.62176246e-01,  5.35408562e-01,\n",
       "         2.64141916e-01],\n",
       "       [-2.94841818e-01, -3.62176246e-01, -8.98031345e-02,\n",
       "         1.32509732e-01],\n",
       "       [ 1.03800476e+00,  9.82172869e-02,  3.64896281e-01,\n",
       "         2.64141916e-01],\n",
       "       [-2.94841818e-01, -1.31979479e-01,  4.21733708e-01,\n",
       "         3.95774101e-01],\n",
       "       [-5.25060772e-02, -8.22569778e-01,  1.94384000e-01,\n",
       "        -2.62386821e-01],\n",
       "       [ 4.32165405e-01, -1.97355361e+00,  4.21733708e-01,\n",
       "         3.95774101e-01],\n",
       "       [-2.94841818e-01, -1.28296331e+00,  8.07091462e-02,\n",
       "        -1.30754636e-01],\n",
       "       [ 6.86617933e-02,  3.28414053e-01,  5.92245988e-01,\n",
       "         7.90670654e-01],\n",
       "       [ 3.10997534e-01, -5.92373012e-01,  1.37546573e-01,\n",
       "         1.32509732e-01],\n",
       "       [ 5.53333275e-01, -1.28296331e+00,  6.49083415e-01,\n",
       "         3.95774101e-01],\n",
       "       [ 3.10997534e-01, -5.92373012e-01,  5.35408562e-01,\n",
       "         8.77547895e-04],\n",
       "       [ 6.74501145e-01, -3.62176246e-01,  3.08058854e-01,\n",
       "         1.32509732e-01],\n",
       "       [ 9.16836886e-01, -1.31979479e-01,  3.64896281e-01,\n",
       "         2.64141916e-01],\n",
       "       [ 1.15917263e+00, -5.92373012e-01,  5.92245988e-01,\n",
       "         2.64141916e-01],\n",
       "       [ 1.03800476e+00, -1.31979479e-01,  7.05920842e-01,\n",
       "         6.59038469e-01],\n",
       "       [ 1.89829664e-01, -3.62176246e-01,  4.21733708e-01,\n",
       "         3.95774101e-01],\n",
       "       [-1.73673948e-01, -1.05276654e+00, -1.46640561e-01,\n",
       "        -2.62386821e-01],\n",
       "       [-4.16009689e-01, -1.51316008e+00,  2.38717193e-02,\n",
       "        -1.30754636e-01],\n",
       "       [-4.16009689e-01, -1.51316008e+00, -3.29657076e-02,\n",
       "        -2.62386821e-01],\n",
       "       [-5.25060772e-02, -8.22569778e-01,  8.07091462e-02,\n",
       "         8.77547895e-04],\n",
       "       [ 1.89829664e-01, -8.22569778e-01,  7.62758269e-01,\n",
       "         5.27406285e-01],\n",
       "       [-5.37177559e-01, -1.31979479e-01,  4.21733708e-01,\n",
       "         3.95774101e-01],\n",
       "       [ 1.89829664e-01,  7.88807586e-01,  4.21733708e-01,\n",
       "         5.27406285e-01],\n",
       "       [ 1.03800476e+00,  9.82172869e-02,  5.35408562e-01,\n",
       "         3.95774101e-01],\n",
       "       [ 5.53333275e-01, -1.74335684e+00,  3.64896281e-01,\n",
       "         1.32509732e-01],\n",
       "       [-2.94841818e-01, -1.31979479e-01,  1.94384000e-01,\n",
       "         1.32509732e-01],\n",
       "       [-4.16009689e-01, -1.28296331e+00,  1.37546573e-01,\n",
       "         1.32509732e-01],\n",
       "       [-4.16009689e-01, -1.05276654e+00,  3.64896281e-01,\n",
       "         8.77547895e-04],\n",
       "       [ 3.10997534e-01, -1.31979479e-01,  4.78571135e-01,\n",
       "         2.64141916e-01],\n",
       "       [-5.25060772e-02, -1.05276654e+00,  1.37546573e-01,\n",
       "         8.77547895e-04],\n",
       "       [-1.02184904e+00, -1.74335684e+00, -2.60315415e-01,\n",
       "        -2.62386821e-01],\n",
       "       [-2.94841818e-01, -8.22569778e-01,  2.51221427e-01,\n",
       "         1.32509732e-01],\n",
       "       [-1.73673948e-01, -1.31979479e-01,  2.51221427e-01,\n",
       "         8.77547895e-04],\n",
       "       [-1.73673948e-01, -3.62176246e-01,  2.51221427e-01,\n",
       "         1.32509732e-01],\n",
       "       [ 4.32165405e-01, -3.62176246e-01,  3.08058854e-01,\n",
       "         1.32509732e-01],\n",
       "       [-9.00681170e-01, -1.28296331e+00, -4.30827696e-01,\n",
       "        -1.30754636e-01],\n",
       "       [-1.73673948e-01, -5.92373012e-01,  1.94384000e-01,\n",
       "         1.32509732e-01],\n",
       "       [ 5.53333275e-01,  5.58610819e-01,  1.27429511e+00,\n",
       "         1.71209594e+00],\n",
       "       [-5.25060772e-02, -8.22569778e-01,  7.62758269e-01,\n",
       "         9.22302838e-01],\n",
       "       [ 1.52267624e+00, -1.31979479e-01,  1.21745768e+00,\n",
       "         1.18556721e+00],\n",
       "       [ 5.53333275e-01, -3.62176246e-01,  1.04694540e+00,\n",
       "         7.90670654e-01],\n",
       "       [ 7.95669016e-01, -1.31979479e-01,  1.16062026e+00,\n",
       "         1.31719939e+00],\n",
       "       [ 2.12851559e+00, -1.31979479e-01,  1.61531967e+00,\n",
       "         1.18556721e+00],\n",
       "       [-1.14301691e+00, -1.28296331e+00,  4.21733708e-01,\n",
       "         6.59038469e-01],\n",
       "       [ 1.76501198e+00, -3.62176246e-01,  1.44480739e+00,\n",
       "         7.90670654e-01],\n",
       "       [ 1.03800476e+00, -1.28296331e+00,  1.16062026e+00,\n",
       "         7.90670654e-01],\n",
       "       [ 1.64384411e+00,  1.24920112e+00,  1.33113254e+00,\n",
       "         1.71209594e+00],\n",
       "       [ 7.95669016e-01,  3.28414053e-01,  7.62758269e-01,\n",
       "         1.05393502e+00],\n",
       "       [ 6.74501145e-01, -8.22569778e-01,  8.76433123e-01,\n",
       "         9.22302838e-01],\n",
       "       [ 1.15917263e+00, -1.31979479e-01,  9.90107977e-01,\n",
       "         1.18556721e+00],\n",
       "       [-1.73673948e-01, -1.28296331e+00,  7.05920842e-01,\n",
       "         1.05393502e+00],\n",
       "       [-5.25060772e-02, -5.92373012e-01,  7.62758269e-01,\n",
       "         1.58046376e+00],\n",
       "       [ 6.74501145e-01,  3.28414053e-01,  8.76433123e-01,\n",
       "         1.44883158e+00],\n",
       "       [ 7.95669016e-01, -1.31979479e-01,  9.90107977e-01,\n",
       "         7.90670654e-01],\n",
       "       [ 2.24968346e+00,  1.70959465e+00,  1.67215710e+00,\n",
       "         1.31719939e+00],\n",
       "       [ 2.24968346e+00, -1.05276654e+00,  1.78583195e+00,\n",
       "         1.44883158e+00],\n",
       "       [ 1.89829664e-01, -1.97355361e+00,  7.05920842e-01,\n",
       "         3.95774101e-01],\n",
       "       [ 1.28034050e+00,  3.28414053e-01,  1.10378283e+00,\n",
       "         1.44883158e+00],\n",
       "       [-2.94841818e-01, -5.92373012e-01,  6.49083415e-01,\n",
       "         1.05393502e+00],\n",
       "       [ 2.24968346e+00, -5.92373012e-01,  1.67215710e+00,\n",
       "         1.05393502e+00],\n",
       "       [ 5.53333275e-01, -8.22569778e-01,  6.49083415e-01,\n",
       "         7.90670654e-01],\n",
       "       [ 1.03800476e+00,  5.58610819e-01,  1.10378283e+00,\n",
       "         1.18556721e+00],\n",
       "       [ 1.64384411e+00,  3.28414053e-01,  1.27429511e+00,\n",
       "         7.90670654e-01],\n",
       "       [ 4.32165405e-01, -5.92373012e-01,  5.92245988e-01,\n",
       "         7.90670654e-01],\n",
       "       [ 3.10997534e-01, -1.31979479e-01,  6.49083415e-01,\n",
       "         7.90670654e-01],\n",
       "       [ 6.74501145e-01, -5.92373012e-01,  1.04694540e+00,\n",
       "         1.18556721e+00],\n",
       "       [ 1.64384411e+00, -1.31979479e-01,  1.16062026e+00,\n",
       "         5.27406285e-01],\n",
       "       [ 1.88617985e+00, -5.92373012e-01,  1.33113254e+00,\n",
       "         9.22302838e-01],\n",
       "       [ 2.49201920e+00,  1.70959465e+00,  1.50164482e+00,\n",
       "         1.05393502e+00],\n",
       "       [ 6.74501145e-01, -5.92373012e-01,  1.04694540e+00,\n",
       "         1.31719939e+00],\n",
       "       [ 5.53333275e-01, -5.92373012e-01,  7.62758269e-01,\n",
       "         3.95774101e-01],\n",
       "       [ 3.10997534e-01, -1.05276654e+00,  1.04694540e+00,\n",
       "         2.64141916e-01],\n",
       "       [ 2.24968346e+00, -1.31979479e-01,  1.33113254e+00,\n",
       "         1.44883158e+00],\n",
       "       [ 5.53333275e-01,  7.88807586e-01,  1.04694540e+00,\n",
       "         1.58046376e+00],\n",
       "       [ 6.74501145e-01,  9.82172869e-02,  9.90107977e-01,\n",
       "         7.90670654e-01],\n",
       "       [ 1.89829664e-01, -1.31979479e-01,  5.92245988e-01,\n",
       "         7.90670654e-01],\n",
       "       [ 1.28034050e+00,  9.82172869e-02,  9.33270550e-01,\n",
       "         1.18556721e+00],\n",
       "       [ 1.03800476e+00,  9.82172869e-02,  1.04694540e+00,\n",
       "         1.58046376e+00],\n",
       "       [ 1.28034050e+00,  9.82172869e-02,  7.62758269e-01,\n",
       "         1.44883158e+00],\n",
       "       [-5.25060772e-02, -8.22569778e-01,  7.62758269e-01,\n",
       "         9.22302838e-01],\n",
       "       [ 1.15917263e+00,  3.28414053e-01,  1.21745768e+00,\n",
       "         1.44883158e+00],\n",
       "       [ 1.03800476e+00,  5.58610819e-01,  1.10378283e+00,\n",
       "         1.71209594e+00],\n",
       "       [ 1.03800476e+00, -1.31979479e-01,  8.19595696e-01,\n",
       "         1.44883158e+00],\n",
       "       [ 5.53333275e-01, -1.28296331e+00,  7.05920842e-01,\n",
       "         9.22302838e-01],\n",
       "       [ 7.95669016e-01, -1.31979479e-01,  8.19595696e-01,\n",
       "         1.05393502e+00],\n",
       "       [ 4.32165405e-01,  7.88807586e-01,  9.33270550e-01,\n",
       "         1.44883158e+00],\n",
       "       [ 6.86617933e-02, -1.31979479e-01,  7.62758269e-01,\n",
       "         7.90670654e-01]])"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Standardize the data before applying unsupervised learning methods\n",
    "scaler = StandardScaler()\n",
    "X_scaled = scaler.fit_transform(X)\n",
    "X_scaled"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dimensionality Reduction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Principal Components: [[ 0.52106591 -0.26934744  0.5804131   0.56485654]\n",
      " [ 0.37741762  0.92329566  0.02449161  0.06694199]]\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Dimensionality Reduction Techniques\n",
    "\n",
    "# Principal Component Analysis (PCA)\n",
    "# PCA is a linear technique used for reducing the dimensionality of data by projecting it onto a set of orthogonal axes (principal components).\n",
    "pca = PCA(n_components=2)\n",
    "X_pca = pca.fit_transform(X_scaled)\n",
    "\n",
    "# print the feaurures being considered as the principal components\n",
    "print(\"Principal Components:\", pca.components_)\n",
    "\n",
    "# Plot the reduced dimensions\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.scatter(X_pca[:, 0], X_pca[:, 1], c=y, cmap='viridis', s=50)\n",
    "plt.title(\"PCA - 2 Principal Components\")\n",
    "plt.xlabel(\"Principal Component 1\")\n",
    "plt.ylabel(\"Principal Component 2\")\n",
    "plt.colorbar(label=\"Class Labels\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAqgAAAIhCAYAAACCB0hMAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAADhs0lEQVR4nOzdd3hUxdcH8O/cuy09pJJAgBBq6J3QkRqa2FBRBMQOiqI/ERtgA18boAgWBKWLVGkCSpHee+8REhIS0pMt9877xyYLS3azJbubdj7Pc5W9Ozv3LCTZk7kzZxjnnIMQQgghhJAyQijtAAghhBBCCLkXJaiEEEIIIaRMoQSVEEIIIYSUKZSgEkIIIYSQMoUSVEIIIYQQUqZQgkoIIYQQQsoUSlAJIYQQQkiZQgkqIYQQQggpUyhBJYQQQgghZQolqIS42e7duzFp0iSkp6fb/RrOOZYsWYLOnTsjLCwMGo0G1atXR58+ffDzzz+btWWMgTGGqVOnFuln3rx5YIzh4MGDpnOTJk0yvcbScfXqVWffahH//PMPnn32WTRo0AA+Pj6oVq0aHnzwQRw6dMihfv79918MGTIE1apVg0qlQkBAADp06IBZs2YhJyfHZfFWVuvXr8ekSZNKOwxCCDGhBJUQN9u9ezcmT57sUII6YcIEPPnkk2jYsCF+/vlnbNiwAZ988gnCw8OxevVqi6+ZOnUq0tLS7L7Gxo0bsWfPniJHRESE3X3YMmvWLFy9ehVjx47F+vXrMX36dCQnJ6N9+/b4559/7Opj4sSJ6NKlC27cuIGPP/4YmzdvxpIlS9CjRw9MmjQJ77//vsvirazWr1+PyZMnl3YYhBBioijtAAgh5vLy8jBt2jQ888wz+PHHH82eGzFiBGRZLvKanj17Ytu2bfj000/x1Vdf2XWdVq1aISQkxCUxWzNz5kyEhYWZnevbty/q1KmDzz77DA888ECxr1+2bBk++ugjjBo1Cj/99BMYY6bn4uPj8fbbb2PPnj1uiZ0QQkjpoRFUQtxo0qRJ+N///gcAiI6ONt1G37Ztm9XX5OTkQKvVWh3JFISi37b169fHqFGjMHPmTFy7ds0lsbvC/ckpAPj6+iI2NhYJCQk2X//RRx+hSpUqmDFjhllyWsjPzw+9e/c2Pc7Pz8eECRMQHR0NlUqFatWqYfTo0UVGr2vVqoUBAwZg7dq1aNGiBby8vNCwYUOsXbsWgHFqRMOGDeHj44O2bduaTZEAjL8o+Pr64tSpU+jRowd8fHwQGhqKMWPGIDc316ytozFt3LgRLVu2hJeXFxo0aIBffvmlyPtOSkrCiy++iOrVq0OlUiE6OhqTJ0+GwWAwtbl69SoYY/jyyy/x9ddfIzo6Gr6+voiLi8PevXvN3svMmTMBwOJUj2XLlqFdu3YICAiAt7c3ateujWeffdbKvxghhLgIJ4S4TUJCAn/11Vc5AL5ixQq+Z88evmfPHp6RkVHs6+rUqcP9/Pz4V199xc+cOcNlWbbaFgAfPXo0T0xM5N7e3nzYsGGm5+bOncsB8AMHDpjOTZw4kQPgSUlJXK/Xmx0Gg6Hkb9qG9PR0HhAQwB966KFi2928eZMD4I8//rhd/cqyzPv06cMVCgX/4IMP+KZNm/iXX37JfXx8eIsWLXh+fr6pbc2aNXn16tV548aN+eLFi/n69et5u3btuFKp5B9++CHv2LEjX7FiBV+5ciWvV68eDw8P57m5uabXDx8+nKtUKl6jRg3+6aef8k2bNvFJkyZxhULBBwwYUKKYYmNj+W+//cb/+usv/thjj3EAfPv27aZ2iYmJPCoqitesWZP/8MMPfMuWLfzjjz/marWajxgxwtTuypUrHACvVasW79u3L1+1ahVftWoVb9KkCa9SpQpPT0/nnHN+8eJF/uijj3IApq/PPXv28Pz8fL57927OGONPPPEEX79+Pf/nn3/43Llzzb7GCCHEHShBJcTNvvjiCw6AX7lyxe7X7N+/n9eoUYMD4AC4n58fHzBgAP/tt9+KJKuFCSrnnL/33ntcEAR+7NgxznnxCaqlIyYmpuRv2IannnqKKxQKfvDgwWLb7d27lwPg77zzjl39bty4kQPg//d//2d2funSpRwA//HHH03natasyb28vPh///1nOnf06FEOgEdERPCcnBzT+VWrVnEAfM2aNaZzw4cP5wD49OnTza716aefcgB8586dTsWk0Wj4tWvXTOfy8vJ4UFAQf/HFF03nXnzxRe7r62vWjnPOv/zySw6Anzp1inN+N0Ft0qSJ2S8e+/fv5wD44sWLTedGjx7NLY1XFPZZmMwSQoin0C1+QkqJLMswGAymQ5Ik03Nt2rTBxYsXsXHjRrz77ruIi4vD33//jWeeeQaDBg0C59xin2+//TaCgoIwfvx4m9ffsmULDhw4YHasWrXK6Zjt8cEHH2DhwoX45ptv0KpVK4dea0vhoqsRI0aYnX/sscfg4+ODv//+2+x88+bNUa1aNdPjhg0bAgC6desGb2/vIuctTZ146qmnzB4PHToUALB161anY6pRo4bpsUajQb169cyuvXbtWnTv3h2RkZFm/xbx8fEAgO3bt5v12b9/f4iiaHrctGlTq+/nfm3atAEADBkyBL///jtu3Lhh8zWEEOIKlKASUko++ugjKJVK0xETE2P2vFKpRJ8+ffDpp5/ir7/+QkJCArp164a1a9diw4YNFvv09/fH+++/j40bN5qSJGuaNWuG1q1bmx2NGzcuUczFmTx5Mj755BN8+umnGDNmjM32hYnalStX7Oo/NTUVCoUCoaGhZucZY6hatSpSU1PNzgcFBZk9VqlUxZ7Pz883O69QKBAcHGx2rmrVqqZYnInp/v4AQK1WIy8vz/T41q1b+PPPP83+HZRKJRo1agQAuH37drF9qtVqADDr05ouXbpg1apVMBgMeOaZZ1C9enU0btwYixcvtvlaQggpCVrFT0gpeeGFFzBgwADT48LEwZrg4GC8/vrr2LZtG06ePIl+/fpZbPfyyy9j+vTpGD9+PF5++eVSjbnQ5MmTMWnSJEyaNAnvvvuuXa+JiIhAkyZNsGnTJuTm5pqNaloSHBwMg8GAlJQUs4SQc46kpCTTaKCrGAwGpKammiWASUlJpljcFVNISAiaNm2KTz/91OLzkZGRDvdZnAcffBAPPvggtFot9u7diylTpmDo0KGoVasW4uLiXHotQggpRCOohLiZtRGryMhIs9HLJk2aAAD0en2RkbVCZ86cMb3WGpVKhU8++QQHDhzAsmXLXPEWbMZcnI8//thUr3TixIkOXe+DDz7AnTt38Nprr1mc1pCdnY1NmzYBAHr06AEAWLBggVmb5cuXIycnx/S8Ky1cuNDs8aJFiwAYpwm4K6YBAwbg5MmTiImJKTIC3rp1a6cSVHtGVdVqNbp27YrPP/8cAHDkyBGHr0MIIfaiEVRC3KwwiZs+fTqGDx8OpVKJ+vXrw8/Pz2L7jIwM1KpVC4899hh69uyJqKgoZGdnY9u2bZg+fToaNmyIhx9+uNhrPvnkk/jyyy+tTgUAgEOHDiEgIKDI+djYWPj7+zvwDq376quv8OGHH6Jv377o37+/WXkjAGjfvn2xr3/sscfwwQcf4OOPP8bZs2cxatQoxMTEIDc3F/v27cMPP/yAxx9/HL1790avXr3Qp08fjB8/HpmZmejYsSOOHz+OiRMnokWLFhg2bJhL3lMhlUqFr776CtnZ2WjTpg12796NTz75BPHx8ejUqRMAuCWmjz76CJs3b0aHDh3w2muvoX79+sjPz8fVq1exfv16zJ49G9WrV3eoz8Kv0c8//xzx8fEQRRFNmzbFJ598gv/++w89evRA9erVkZ6ejunTp0OpVKJr164Ox04IIXYr3TVahFQOEyZM4JGRkVwQBA6Ab9261WpbrVbLv/zySx4fH89r1KjB1Wo112g0vGHDhvztt9/mqampZu1xzyr+e23atMm0Ot/eVfwA+ObNm132vrt27Vrstey1fft2/uijj/KIiAiuVCq5v78/j4uL41988QXPzMw0tcvLy+Pjx4/nNWvW5EqlkkdERPCXX36Z37lzx6y/mjVr8v79+xe5jqW/y8LV8F988YXp3PDhw7mPjw8/fvw479atG/fy8uJBQUH85Zdf5tnZ2WavL2lMXbt25V27djU7l5KSwl977TUeHR3NlUolDwoK4q1ateLvvfee6fqW4r73fU6cONH0WKvV8ueee46HhoZyxpip6sTatWt5fHw8r1atGlepVDwsLIz369eP//vvv0X6JIQQV2KcW1kOTAghxKIRI0bgjz/+QHZ2dmmHQgghFRLNQSWEEEIIIWUKJaiEEEIIIaRMoVv8hBBCCCGkTKERVEIIIYSQcmDKlClo06YN/Pz8EBYWhsGDB+PcuXM2X7d9+3a0atUKGo0GtWvXxuzZs4u0Wb58OWJjY6FWqxEbG4uVK1e64y3YjRJUQgghhJByYPv27Rg9ejT27t2LzZs3w2AwoHfv3sjJybH6mitXrqBfv37o3Lkzjhw5gnfffRevvfYali9fbmqzZ88ePP744xg2bBiOHTuGYcOGYciQIdi3b58n3pZFdIufEEIIIaQcSklJQVhYGLZv344uXbpYbDN+/HisWbPGtNELALz00ks4duwY9uzZAwB4/PHHkZmZaVY7u2/fvqhSpUqpbW1cqQr1y7KMmzdvws/PD4yx0g6HEEIIIXbgnCMrKwuRkZEQBM/f/M3Pz4dOp3NL35zzIjmJWq22ayvpjIwMAEBQUJDVNnv27EHv3r3NzvXp0wdz5syBXq+HUqnEnj178MYbbxRpM23aNDvfhetVqgT15s2biIqKKu0wCCGEEOKEhIQEh3dKK6n8/HzUivbFrSTJLf37+voWqak8ceJETJo0qdjXcc4xbtw4dOrUCY0bN7baLikpCeHh4WbnwsPDYTAYcPv2bURERFhtk5SU5NibcaFKlaAWbi2ZkJDgsq0cCSGEEOJemZmZiIqKsrpFtDvpdDrcSpJw6lIU/PxdO3qblSmjUUxCkbzEntHTMWPG4Pjx49i5c6fNtveP0BbO7rz3vKU2pXm3uVIlqIV/0f7+/pSgEkIIIeVMaSZMfr5K+Pu6eHqBLANwPC959dVXsWbNGuzYscPmiHLVqlWLjIQmJydDoVAgODi42Db3j6p6Eq3iJ4QQQgixgckAk5mLD8di4JxjzJgxWLFiBf755x9ER0fbfE1cXBw2b95sdm7Tpk1o3bo1lEplsW06dOjgWIAuRAkqIYQQQkg5MHr0aCxYsACLFi2Cn58fkpKSkJSUhLy8PFObCRMm4JlnnjE9fumll3Dt2jWMGzcOZ86cwS+//II5c+bgrbfeMrUZO3YsNm3ahM8//xxnz57F559/ji1btuD111/35NszQwkqIYQQQogtnLnncMCsWbOQkZGBbt26ISIiwnQsXbrU1CYxMRHXr183PY6Ojsb69euxbds2NG/eHB9//DFmzJiBRx55xNSmQ4cOWLJkCebOnYumTZti3rx5WLp0Kdq1a1fyvzcnVao6qJmZmQgICEBGRgbNQSWEEELKidL8/C68dsLNGPj7iy7uW0JU5CXKSyyoVIukCCGEEEKcUThv1NV9EsvoFj8hhBBCCClTym2COmXKFDDGSnUCLyGEEEIqB+MqftcfxLJymaAeOHAAP/74I5o2bVraoRBCCCGEEBcrdwlqdnY2nnrqKfz000+oUqVKaYdDCCGEkMpAdtNBLCp3Cero0aPRv39/9OzZ02ZbrVaLzMxMs4MQQgghxFGMu+cglpWrVfxLlizB4cOHceDAAbvaT5kyBZMnT3ZzVIQQQgghxJXKzQhqQkICxo4diwULFkCj0dj1mgkTJiAjI8N0JCQkuDlKQgghhFREjLthkRSNoFpVbkZQDx06hOTkZLRq1cp0TpIk7NixA9999x20Wi1E0byArlqthlqt9nSohBBCKoG8a7eQsnYvMg+eh6yXoIkKRWj/dghs3xBM4dqC7oRUNuUmQe3RowdOnDhhdm7kyJFo0KABxo8fXyQ5JYQQQtwlcck23Jz3FyAIgGxc6aJPy0TWkYvwrhOJup8+C0WATylHSVxK5sbD1X0Si8pNgurn54fGjRubnfPx8UFwcHCR84QQQoi73N54wJicAqbk1PhnY7KRezkJFz/8FfW/eQlMKDcz6QgpU+g7hxBCCLETl2TcnL+5+EayjJxzCcg6ctEzQRGPoFX8nlVuRlAt2bZtW2mHQAghpBLJOnYJ+tQs2w0FASkbD8K/VT33B0VIBVSuE1RCCCHEk3S30u1rKMvQ3kx1ayzEw9xRWJ8K9VtFCSohhBBiJ6a2/2NT9FK5MRLiaUzmYC5e1OTq/ioSmoNKCCGE2Mm/eR1AYLYbMoaAdg3dHxAhFRQlqIQQQoidlEF+qNK5ibG8VDGYQkBI71bFtiHljOymg1hECSohhBDigKiXB0IdHmg5SWUMYAzRbz9OdVAJKQFKUAkhhBAHKAN90WD6Kwju3QpMab5JjE/96qg7ZZRxlJVUKFRmyrNokRQhhBDiIIW/D2q9/jCqPxePnLPXwfUS1JHB8KoZXtqhEVIhUIJKCCGEOEnh64WA1vVLOwziCVRmyqPoFj8hhBBCCClTaASVEEIIIcQGJhsPV/dJLKMElRBCCCHEFg6Au3hVEy2Ssopu8RNCCCGEkDKFRlAJIYQQQmxg3A23+GkE1SoaQSWEEEIIIWUKjaASQgghhNhCZaY8ikZQCSGEEEJImUIjqIQQQgghNrhja1Kag2odjaASQgghhJAyhUZQCSGEEEJsoTmoHkUJKiGEEOIiUk4+Mg6dh5STD2WgL/xb1YWgUpZ2WMQVKEH1KEpQCSGEkBKStXr8N2cDbm84AK43mM6LvhqEP9oFVYd0BRNoVh0h9qIElRBCCCkBWWfAhfd+Qfapa0W2wpSy83Fz3iZob6ai5huPgDFWSlGSkjIuknLtvx8tkrKOfp0jhBBCSiB59S6Lyem9UjcdQsb+sx6MipDyjRJUQgghxElckpG8ek+xySkAQGBIXr3bM0ER95DddBCLKEElhBBCnKS9lQb97QzbDWWOrGOXwW0lsoQQADQHlRBCCHEa10v2N5ZkQOaASPNQyyVaxe9RNIJKCCGEOEkVEgCmsO+jVBUWCCbSxy4h9qDvFEIIIcRJoo8GVbo2A2wlnowhdGB7zwRF3IO76SAWUYJKCCGElEDEE90gKETAWgkpUYAy2B8hfdt4NjDiUkxmbjmIZZSgEkIIISWgiQpD3c+eheijMZ4ozDkE4x9UoYGo93/PQeHnXToBElIO0SIpQgghpIR8G9VCk/njkbb1GO7sOA5DVq5x1LRnKwR2iAVTiKUdIikpd9ySp1v8VlGCSgghhLiA6KVGaL+2CO3XtrRDIaTcowSVEEIIISac66CX10In/wqJnwXAILKmUAnDoRT6gLFKmjpwBrh6zqiLt06tSCrpVxkhhBBC7sd5JnIMIyHxIzAuUzEW6pT4YeRJB6GXO8Nb8QMY05RqnKTio0VShBBCCAEA5BregMSPFTy6t4q88c8Gvgt5hg89HleZUAa2Ot2xYwcGDhyIyMhIMMawatWqYtuPGDECjLEiR6NGjUxt5s2bZ7FNfn6+Y8G5GCWohBBCCIEkn4eBb0XxWZMMPV8BmSd5Kixyj5ycHDRr1gzfffedXe2nT5+OxMRE05GQkICgoCA89thjZu38/f3N2iUmJkKjKd1RcrrFTwghhBDo5ZUARAC2t2/Vy39CLT7v9pjKFDeu4s/MzDQ7rVaroVarizSPj49HfHy83d0HBAQgICDA9HjVqlW4c+cORo4cadaOMYaqVas6ELj70QgqIYQQQiAjxc6WAmSe7NZYyiSZuecAEBUVZUomAwICMGXKFLe8hTlz5qBnz56oWbOm2fns7GzUrFkT1atXx4ABA3DkyBG3XN8RNIJKCCGEEDD44u4uA8XhYMzX3eFUKgkJCfD39zc9tjR6WlKJiYnYsGEDFi1aZHa+QYMGmDdvHpo0aYLMzExMnz4dHTt2xLFjx1C3bl2Xx2EvSlAJIYQQAqXQGzr5NztaSlCy3m6Pp8zhzPVloQr68/f3N0tQ3WHevHkIDAzE4MGDzc63b98e7du3Nz3u2LEjWrZsiW+//RYzZsxwa0zFoVv8hBBCCIHI4iCgDozzUK22gsjaQBQaeios4gKcc/zyyy8YNmwYVCpVsW0FQUCbNm1w4cIFD0VnJY5SvTohhBBCygTGGLyVs8EQAMtJqgiGcHgrpns6tDKBye45PGH79u24ePEiRo0aZbMt5xxHjx5FRESEByKzjm7xE0IIIQQAILLa8FWugVb6Hjp5OQBtwTPeUAlDoBZHQ2DBpRlipZadnY2LFy+aHl+5cgVHjx5FUFAQatSogQkTJuDGjRv47TfzqRpz5sxBu3bt0Lhx4yJ9Tp48Ge3bt0fdunWRmZmJGTNm4OjRo5g5c6bb309xKEElhBBCiInAIuGl+AQaPgEyvwaAQWC1wJhXaYdWuu5Zde/SPh1w8OBBdO/e3fR43LhxAIDhw4dj3rx5SExMxPXr181ek5GRgeXLl2P6dMsj3+np6XjhhReQlJSEgIAAtGjRAjt27EDbtm0dfDOuxTjnrq7qVWZlZmYiICAAGRkZbp+MTAghpPLhkoy8a7fAdXqoQgOhDKbPGlcozc/vwmun/1kf/j7Fzc91ou8cCYEDz1FeYgGNoBJCCCElJOsNSF6xE8mrd0OflmU679+6HiKGPgDf2JrFvJqUC24s1E+KogSVEEIIKQFZZ8DFD+ch69hl4L6bkpmHLyLz8AXUfncoqnQqOv+PlCNl4BZ/ZUKr+AkhhJASSFz0t8XkFAAgywDnuDJ1CXSpmUWfL2M45zDIh6GT1kEvbwXnOaUdEqmkaASVEEIIcZKs0yPlz72Wk9NCHOCyjNsb9iPy6Z6eC85BOmkVtNI0yLh3kY0XVMIT0IhvgjHvUoutTHBjoX5SFI2gEkIIIU7KPnkNUk6+7YYyx50dJ9wfkJPypVnIk8ZBRsJ9z+RBJ/+KHMNT4DyvVGIjlRMlqIQQQoiTpDyt7UaFbXPtb+tJknwaWumLgkeWRoJlSPwEtNJ3ngyr7JHddBCLKEElhBBCnKQK9rOvIWNQhQa4NxgnaaX5KH57UwCQoZUXgvOymWSTiocSVEIIIcRJ3vWjoI4Ist2Qc4T0bu3+gJxg4P8AkOxomQmJn3J3OGVX4RxUVx/EIkpQCSGEECcxxhAx9IHiGwkClMH+qNK9mWeCchCHI6Oidsy3JcQFyk2COmvWLDRt2hT+/v7w9/dHXFwcNmzYUNphEUIIqeSCe7VCxNM9jA/E+z5WGYMy0Af1po6CqFF5Pjg7CKw6APtG8oxtKyfOGbjs4oNGUK0qN2WmqlevjqlTp6JOnToAgF9//RUPPvggjhw5gkaNGpVydIQQQiqzyKd7wr9VPaSs2YP0fWfA9QaoQgMQ0q8dQvq0gcKv7O1jL8nnoZOXgPN82N7SSIDIWkNgNTwRGiHlJ0EdOHCg2eNPP/0Us2bNwt69eylBJYQQUup8G9aAb0PHEjhDRg6yT18D10tQVwuGd0ykm6K7i3Md8gwToOcrYVwcZWv+qXGUTyO+7ubIyjiqg+pR5SZBvZckSVi2bBlycnIQFxdntZ1Wq4VWe3duTWZm2d/FgxBCSMWnT8/Gfz+tx53tx8ANd2sNecVEoNrIvghoXc9t1zYmp6sKHtlKTgUAArzEr6EQ2rstpnLBHWWhqMyUVeVmDioAnDhxAr6+vlCr1XjppZewcuVKxMbGWm0/ZcoUBAQEmI6oqCgPRksIIYQUpb+ThbOvzUTaVvPkFADyLifi4gfzkLbtmFuuLclnC0ZObd3SF8FQD2phDPyUO6ASB7glHkKsKVcJav369XH06FHs3bsXL7/8MoYPH47Tp09bbT9hwgRkZGSYjoSE+3fIIIQQQjzr+vdroLudCcgWhs84AM5x9ctl0Kdnu/zaOnkpbNc8BQAJXooJ0Cheh8CqujyOconKTHlUuUpQVSoV6tSpg9atW2PKlClo1qwZpk+fbrW9Wq02rfovPAghhJDSokvNRPrOU5aT03twSUbqpkMuv77EL8C+mqcCZH7J5dcnxF7lKkG9H+fcbI4pIYQQUpZlHb0EcFu31wFwjoz9Z11+fQalnS05yukyFfeRmXsOYlG5+ep79913ER8fj6ioKGRlZWHJkiXYtm0bNm7cWNqhEUIIIXaRdXr72+brXH59hdAOBmkHbM9B5VCwti6/PiH2KjcJ6q1btzBs2DAkJiYiICAATZs2xcaNG9GrV6/SDo0QQgixi7qqHduiAoAoQF0txOXXVwqPIV/6BkBxibIIkTWDKDRw+fXLNSoz5VHlJkGdM2dOaYdACCGElIhf09pQhgZAn5JRfENJRkjfNi6/vsCC4SV+hDxpgpUWIgANvMTPXH5tQhxRruegEkIIIeUJEwVUG967+EYCg0+jmvBrHuOWGFTi4/ASp4MhvPCCKCzGL7Km8FUshyi4rw5ruUVzUD2q3IygEkIIIRVBcM+WMGTk4L+f1gMCA+SC+aCCAMgyfBpEoc6k4WDMfcmLShwIpdAPBv5vwWp9JRSsDUShoduuWe5x2J6660yfxCJKUAkhhBAPC3+kMwLaN0TKun3IPHQeXGeAJioMIf3bIqB1fTDRvTc4ZZ4AmSdCQBgUQmcwZk9tVEI8hxJUQgghpBRoqoUg6oX+APp77Jp6eQe00reQ+N0aqwzhUIsjoRKeBWOUFljDZQbu4lvyru6vIqGvREIIIWUGl2RkHjqPjP1nIeXroAoNRHCvltBEun5Fe2Wjk5YiT3oXhfNNC3HcQr70OQzyAXgrZlGSSsoE+iokhBBSJuReuolLHy2A7tYdQBRM8/OSFm9FlW7NUOuNRyCo7S00T+4l8YsFyam1iZQcBv4PdPIcqMUXPRxdOUFlpjyKVvETQggpdfkJKTj31o/QpaQbT0iycTvQgi1B7+w4jksfLwC3sUUosUwnLYDtj3wOrTQXnNuzFSoh7kUJKiGEkFJ349dNkLX6uyva7ydzZB48j8wD5z0bWAWhlzcAsJ14ciRD5mfcH1B5RGWmPIoSVEIIIaVKn5aF9N2nTKOlVgkCkv/c45mgKhiOXAfa5rgxEkLsQ3NQCSGElKq8a7esj5zeS5aRe/GG+wNyES7LkHK0YEoRokbl2WvzDOjl9ZB5EhjzBUMVuxNPxsJtN6qMONwwB9W13VUklKASQggpXQ4VpC/7t0T1aVlIXr0bKev2QcrOAwB414lE2OCOCOre3K01Tjk3IF/6HDr5NwAGGLculQsOWwSIrClEVstt8ZVr3A235GmRlFWUoBJCCClV3tFVjav2JRtJlCjAN7aGZ4JyUt61Wzj/9k8wZOWajQrnXkrE1S+XIX33KdR+dyiYwvWF8TnnyDWMg4Gvw92hOYMDPchQi2NcHhchzqA5qIQQQkqVIsAHQV2bGrf6LI4kI3RAnGeCcoKsM+DCe3OLJKcAAG58nL7nNG7O3+KW6xv4Vhj4Wjh+31gEwKARP4JSeMANkVUMnLvnIJZRgkoIIaTURQ7vDYWvxnqSyoAqXZvCr0WMZwNzQPquk9Dfzih+Pi0HklfvhpSvc/n1ddJ8GJNNW5RgqAHACwzBUAmPw1exDmrxaZfHRIizKEElhBBS6tThVVB/2svwrl3VeEIUjLfBGQNEAaGD4hD9vyFgDs1X9ay0rcfsmk8r5+uQedD15bIM/CDsKSUF6OGtmI4A1Sn4qw7AS/EJRKGBy+OpcAoL9bv6IBbRHFRCCCFlgiYyBA2/exU55xKQsa9gq9OwQAR1awZloG9ph2eT/k6W3fds9enZyDx8ESlr9yDn/H8AAJ+GNRA2IA6+TaOdTMQd2cTAelvOMyHjDhh8IbBgJ+IgpOQoQSWEEFKm+NSPgk/9qNIOw2GKAB/jCKodSWrqpkPIPf+fcUpDQf3X9N2nkf7vSVTp1gzRbz3m8EIqkdWDxE/AdqKqgMCii5w1yIehlX6Agf9t6kNkLaAWR0HB4sv06LVHuKOwPhXqt4pu8RNCCCEuENStmX0jqIJgTE4B880JCqoY3Nl+DAk/rnP4+irhGdhOTkUoWX8ILNDsrE5ahRzDEBj4P2Z9SPwYcg1jkC99Bk4reogHUYJKCCGEuECVLk2gqOILCMWMijHY3jGLAylr90GfluXQ9ZVCP4isKawvlBIBeEGteM3srCSfR570FoyJ6f1zWI2x6uQ50Mt/OhRPRcM5c8tBLKMElRBCCHEBQaVE3U9GQvRWF1Myy96EhCP1nyMOXZ8xNXwUv0Jk7QrOiAXXEwuuHApfxWKI993eNxb1txUXg1b+yaF4KpzCW/yuPohFNAeVEEIIcRHvmEjEfj8Wt1buRMr6/eBavXkDO2+TM4FBl5zu8PUZC4CvcgEM8nHo5ZWmrU6VQi8o2ANgrOjHvk7+E7ZX/3PI/BRk/h8EVt3huAhxFCWohBBCyrT8hBQk/7kHaduOQc7Jh+jnheAeLRE6sD3UVYNKO7wiVGGBiHpxANSRwUiYucapPjgHBI3K6RgUQlMohKZ2ts62u1/O04HKmqC6oywU3eK3ihJUQgghZVbajuO48vlS4+ZIBXM3Dek5uLVyJ5LX7EHMh08joE390g3SAi7JSFqy1fkOJNlj74shABzp9rWlslPEQ2gOKiGEkDIp51wCrkxdYlzdfv/CIpmDGwy49NF85CekeDw2zjkyj1zEzQVbcGPeJqRtPQpZd/d2ftbxy9CnOrbIyURg0NQIg2/jWq4J1gal8DBs70AlQGStILAIT4RUJtEiKc+iEVRCCCFlUtIfOwp2ZrIyb5MDXOZIXr0LNcYM9lhc2aeu4uqXy6BNTDPueAXjiKnoo0G1UfEI7dcWupQM5zoXBIheKtR+b6jH6o6qxWegkxfAuGLf2hxZGWrxJY/EQwhAI6iEEELKIClPi/Rdp0y1Qa03lHF782FwW6WbXCT79DWcH/8ztEl3TNfnBTFKOfm4PmMlbq3aZVzJ7yiBIbBDLBp8OxpeNcNdGLWty9aAt2I2ACWspQUMQeA8vXLXQpXddBCLKEElhBBS5hgycgHZvmSIa/WQ83Rujsh4W//atBXGZLiYRO2/n9ZDUyscTGnHTlAMCO7TGnU+GYGm899BzPtPQRMZ4sKo7aMUusFHsQ4C6ll8nuMO8qT/IV+a6uHIyL127NiBgQMHIjIyEowxrFq1qtj227ZtA2OsyHH27FmzdsuXL0dsbCzUajViY2OxcuVKN74L+1CCSgghpMwRvR1YwS4wCGql+4IpkHP6GvKvJ9tOnGWOjF2nENyzpc2i/UypQPVn+yKgdX0og/1dG7CDOC5AxlmrzwKATv4JevlvzwVVlhSu4nf14YCcnBw0a9YM3333nUOvO3fuHBITE01H3bp1Tc/t2bMHjz/+OIYNG4Zjx45h2LBhGDJkCPbt2+fQNVyN5qASQggpcxT+PvCJrYGcswnFJ4SigIA29R3et94ZOWcTjAmnrQSVc2SfuY7o/w1Bzvn/kHclqehrBAaAofaEJ6EI8HFbzI7QSr/AOG5V3H1nEVppLpRCDw9FVXZwmYG7uLC+o/3Fx8cjPj7e4euEhYUhMDDQ4nPTpk1Dr169MGHCBADAhAkTsH37dkybNg2LFy92+FquQiOohBBCyqTwhzvbTgYlGeEPdfRIPNzOKQfGtsZFU/W/fBHhj3SG6KMxe96veQzqf/kCAuNiXR2mUzjPhMQPwvakSAkS3w3O8z0RVqWRmZlpdmi1Wpf236JFC0RERKBHjx7YutW8/NmePXvQu3dvs3N9+vTB7t27XRqDo2gElRBCSJkU2LERwh7uhOQVO42r+e+d91nwOHJ4b/g1i/FIPF7R4fbNixUYvGsbyzGJXmpUHxWPyGE9kXspEVxngDoiCKqwQPcG6yCOPAfb54JBY7thReLGQv1RUVFmpydOnIhJkyaVuPuIiAj8+OOPaNWqFbRaLebPn48ePXpg27Zt6NKlCwAgKSkJ4eHmi/LCw8ORlJRU4uuXBCWohBBCyiTGGKo/3w/eMZG4tWwH8q7e/cD0rlsNVYd0RZVOjT0Wj3+LulCGBkBvq4SUzBHSt63ZKUGlhG/DGm6MrmQYAmFcxa+30RIA1GDwc29AlUxCQgL8/e/OQVarnagCYUH9+vVRv/7dDR/i4uKQkJCAL7/80pSgAihS0oxz7rEyZ9ZQgkoIIaTMYowhuEcLBD3QHNrEVEhZeVAE+JTKFqdMFFDj5YG49NGCYtuFP9IZ6qpVPBSVazCmhpI9CD1fCUAqpqUIlfAwGHP/orSyxh2F9Qv78/f3N0tQ3al9+/ZYsODu13DVqlWLjJYmJycXGVX1NJqDSgghpMxjjEETGQKf+lGlkpwWCuzQCNETnoTgVVBlQGBmR/iQrqg2qm+pxVcSanEUjGmBtSSMAVBAJT7ruaCIyx05cgQREXd3BIuLi8PmzZvN2mzatAkdOnTwdGhmaASVEEIIcUBQ16YIaNcAaVuPIvvkVXBJhleNMAT3aQ1VKZeKKglRqA9vxQ/INbwM463+exdMCQBU8Fb8AJF5Zs5vmcMZ4OJV/I7Oac3OzsbFixdNj69cuYKjR48iKCgINWrUwIQJE3Djxg389ttvAIwr9GvVqoVGjRpBp9NhwYIFWL58OZYvX27qY+zYsejSpQs+//xzPPjgg1i9ejW2bNmCnTt3uuY9OokSVEIIIWWGITsPd/49AX1KBgQvFQLaNvDorkr2EjUqhMa3RWh8W9uNyxGl0A1+yr+hkxZDJ68ERwYYAqESHoZKfAICi7DdCXGbgwcPonv37qbH48aNAwAMHz4c8+bNQ2JiIq5fv256XqfT4a233sKNGzfg5eWFRo0aYd26dejXr5+pTYcOHbBkyRK8//77+OCDDxATE4OlS5eiXbt2nntjFjBeifYty8zMREBAADIyMjw214MQQohtXJJx89dNuLVyF7jeAIiCcdW+zOHbNBrR/3scqtCA0g6TlJLS/PwuvPatqd3gr3HtuF5mvgHh72yjvMQCmoNKCCGkVHHOcfWb5Uhatt2YnAKAJJtKOmWfuoazr38PfVqWx2PLvXQTyWt249aKncg8fMG4zSmplDh3z0Eso1v8hBBCSlXWsctI23LYegNJhv5ONm7O34yaYx/2SEy5lxNxbdpy5J6/Yay5CgCcQxkaiKgX+3u0vBUhlRGNoBJCCClVKWv2GG/pF0eWkbrlCKQc9+9glHvpJs69MQu5F28aT9wz1KVPScflTxYitbiEmlRMMnPPQSyiBJUQQkipyj55xXhL3wauNyD3cqLb47n69R+Q9YZid426Nn0lDNmO7b5ECLEfJaiEEEJKlUNrdd08BzTnXALyLiXa3NKUGww0ilrJFBbqd/VBLKMElRBCSKnyio4wFrq3hTFoosLcGkvWiSv2xQKG7BNX3BoLIZUZJaiEEEJKVdjA9jZHLCEICOwQC2WQe/eA5wb57qKoYhtycENxW4KSCocz9xzEIkpQCSGElKrADrHwbVzL+silwCCoFIgc1svtsXjVCLVrPiwE94/mElKZUYJKCCGkVDFRRJ3Jw+Hfqp7xhCgYt30XjB9RigBf1Pv8OXjVcv+OUgFtG0AR6GO7ocwREt/G7fGQsoPLzC0HsYzqoBJCCCl1oo8GdT8egdzLiUjdfAi6lAwIGiUC28cisH1DMIXokTiYQkT1UfG4+tUfxTQCQvq2gaZaiEdiImUEh+tvyVOhfqsoQSWEEFJmeNeOgPeLA8A5R/bxy8g4cB5Zxy5BFV4FwQ+0sDgHVZ+aicwjFyFr9VCFV4F/ixgw0fmENrhXK0j5OiTMXmucG1tYZUAQAFlGcJ/WqDH6Qaf7J4TYRgkqIYSQMiXvShIuf7YI+QkpgCiAMYBLHDd+2YjQAe0R9UJ/MIUIfXo2Er5fgzs7T5otslIG+SFiWE+Exrd1OoawgXGo0qkxbv91CNknr4AbJHhFV0VIfFt41aC5p5WRO8pCUZkp6yhBJYQQUmbk/5eCc2/OhpSvN56Q5Lt3QTmQ8uceGDJzEfXSAJx7Yxa0t9KLVADQp2Xh+vSVMNzJRsTQB5yORVnFDxFPdAPQzek+CCHOoQSVEEJImfHfnI3G5NRaQX4O3Nl2DFJufkFyan3F/c3fNiOwQyy8alUtUUyyVo/Uf44gZc0e46guA3wa1kTYoDgEdogFE8r2emPO86GX10EvbwBHOhjCoRIfgoJ1B2OemdtbIbhja1JaJGUVJaiEEELKBN3tDGTsPXN3zqc1goDMA+dsLzARBaSs3YsaYwZbbSJr9UjffQq65HQwtRIBrepBExVqet6QkYPz7/yMvCtJxsoCBdfMPnkF2ccvI7BDI9R+90mPLeJylEE+hlzDKHCkwVi4RwYgwmDYAAG14aOcB4FVL+UoCSmKElRCCCFlQt6lRNvJKWD/dqeSjMxDFyw+xTnHrT92IHHxVsi5WmNpK5njP74Wfs1iUOvNR6EMDcCljxcg71pywYvujcH4IH3PKST8tB41Xh5oX0weJPEryDE8BSC/4Ezh35tU8OgasvVD4adcC8b8SyPEcoVz+748He2TWFa270sQQgghJSDrDRbP35izETfmbDQmp4CxOH9BtpB14grOvv49MvadQfbJq8UnxBy4vW4fDFm5Lo685LSGWQC0uJuY3k8Cxw3o5N89GBUh9ik3CeqUKVPQpk0b+Pn5ISwsDIMHD8a5c+dKOyxCCCEu4lU7wr5tRq3tOGWhnaXdnnIv3MCtP3ZYf50sQ5+eg/9+XG8cWbWBSxLu/HvSvpg8hPNs6PlqFI6WFtMSWmm+J0Iq9wpX8bv6IJaVmwR1+/btGD16NPbu3YvNmzfDYDCgd+/eyMnJKe3QCCGEuIAqNAABbeubdpCySubQ1AiznczKHKH92xU5nbx2r+3EU5ahvZlq17anTBCgT8202c6TZH4TgN6uthwJ4NxWIktMi6RcfRCLys0c1I0bN5o9njt3LsLCwnDo0CF06dLF4mu0Wi20Wq3pcWZm2foBQgghxFy1UfHIOn4FslZXpHwUAIAxBHZqhND+7XHh3TnGc5bm8QkCvGMiENi+YZGnso5dsivxNPbDLMdxDy5ziN5q+/rzFKZ0oLGIcjReRSqJcvsVmZGRAQAICgqy2mbKlCkICAgwHVFRUZ4KjxBCiBO8aoSh/pcvQB1exXhCFMBEwZgoMoaQvq0R/fbj8G8eg9rvPQWmVJiPpBaMvvrUq4a6n460uLqe25ucAjaTU2OHHIEdGtnfpwcIqAEGezYUECGytmD2TK2o5OgWv2eVmxHUe3HOMW7cOHTq1AmNGze22m7ChAkYN26c6XFmZiYlqYQQUsq4JCNj/1lkn75m3KGpZjiqdG0K0cs4CukdE4lGc95E1pGLyDhwDrLWAFV4IIJ7tIQqNMDUT5WOjeC3cAJSNx1C+r4zkPP1UEcEIaRPG/g1r221PqlXdFXoU7PsqgagDPKDPj3beqIqCPBvXRfqCOuDJaWBMREqcRi00jewvkgKACSoxeGeCosQu5XLBHXMmDE4fvw4du7cWWw7tVoNtbqM3XYhhJBKLPPwRVz96nfoU7OMI6MM4AYZCbPXotqI3ggb3BGAcV6nf6t68G9Vr9j+FH7eCH+kM8If6Wx3DGH92yNzv41FtgKDb+NoRL00AOf/9yOkPF3RhFZgUFetglrjHrX72p6kFkbBIP8NiR+HtSRVyR6EgvXybGDlFgNcPuJJI6jWlLtb/K+++irWrFmDrVu3onp1Ki5MCCHlRdaxS7jw/lzo07IBGEdSucGYOMn5OiTMXoukZcWsrncR/9b14NestvVqAIyBCQzVRvaBd+0INPzuVQT3agmmvDtdQPTRIPyRzmgwfTSUgb5uj9kZjGngo5gPJXsMd8ejCt+zD9TCq/BSfEm390mZVG5GUDnnePXVV7Fy5Ups27YN0dHRpR0SIYQQO3HOcW36SpvVzm/M+wvBPVtAWcXPbbEwUUDMxGdweepi40iqKBgXTTEGcOOCp9rvDYVvwxoAAHVEEGq98QiiXugPbWKasXxV9RAIKkcWIpUOxnzgrZwCmb8Ng7wNHJkQWGjBNqdepR1eueKOOaM0B9W6cpOgjh49GosWLcLq1avh5+eHpKQkAEBAQAC8vOibjBBCyrLs41eMZZtskTlu/3UQEU90d2s8orcadT8agZwLN5D610Fob6VBUKsQ0LY+gro0haBRFX2NjwbedSLdGpe7CKwKVOJDpR0GIXYrNwnqrFmzAADdunUzOz937lyMGDHC8wERQgixW875BLtKNoFz5Jz7zzNBAfCpWw0+dat57HqkHHNH3VKqg2pVuUlQOW1YSwgh5ZcjP8Lp5z0hlV65SVAJIYSUX951Iu2rKSoweMe47jY65xzZp64iZe0+5F68AcaMq/NDB7Rz6XVIxWdj+rTTfRLLKEElhBDidn7NY6AKC4QuJb340VQOhMS3cck1ZZ0BV/5vKdJ3nry7EApA/s1U3N6wH2EPdUT15/tZrZdKyL1okZRn0XclIYQQt2OCgBpjHgTAii39GDG0O1QhAdYbOODajBVI33XK+ODe3aMK/py8cheSFm91ybUIIa5FCSohhBCPCGjbADEfPAXRR2M8IQrGgzEwhYDIYT0R8XRPl1wr/+ZtpG05YvMeauLS7ZBytS65JqngOHPPQSyiW/yEEEI8JrBDIzRtXQ93/j2J7FNXwSUZXjXDEdyzBRT+Pi67TuqmQ4Ag2NzOlOv0uLPjOEL6umZaASHENShBJYQQ4lGCSongHi0Q3KOF266hTUyDPaUDmCgUtCXEBpmBU5kpj6Fb/IQQQiocQaU07gxlA+eAoKKxGkLKGkpQCSGEVDj+reqaL4yyRpbh37qe+wMqBucc3CCVagzEtsJV/K4+iGX0ayMhhJAKJ7BjIygCfGDIzLW+UEoQ4BVdFT71ozwbXIGsY5eRvGY3MvadBTdIUPh7I7hvG4QNbA9VaKBbrinzBOjkteA8DYwFQinEQ2S13XItQkqCElRCCCFlBjdISN99Gql/H4Y+NROinxeqdG6KoAeaQ9So7O5HUCpQ+92huPDeL+CyXHSTAEGA6KVC9PjHXfwO7HNzwRYkLvjbrD6rITMXt/7YgZS1e1H302fh27CGy67HeRZyDeNh4H/BWOdLAMChlb6CgnWDl+IrCKyKy65XIblj1T2NoFpFt/gJIYSUCfk3b+Pkc1/j8meLkHHgHHIv3kTW0cu4PmMlTgybiuzT1xzqz69ZbdT/6kX4xtY0f4IxBLSphwYzRsOrRpgL34F90rYeNSanQNFpCDKHnK/DxffnQp+e7ZLrca5FjuEZGPhmGBeOyQAMAIzTCgz8X+TonwDnrrleRUW3+D2LRlAJIYSUOkNWLs7/76e7SVnhiGfB7XkpJx8X3v0FDb8dA01UqN39+tSPQr2pzyHn4g3oEu+AKUX41KsOVVigi9+BfTjnSFy81TiIaa3IgMwh5WqR+tdBVH28W4mvqZOXQuLHi7mgBBmXoJV/hUYcXeLrEeIKlKASQggpdbfX74c+Lcv6fFGZQ9YbkPj7NkS/+ZhdfeacvY5bK3fhzs6TxpFKUUCVTo2hCg0otQQ1/+ot5F9Ptt2Qc9zedKjECSrnHDrpNztaytBJ86EWXgJjYomuWVFx2Xi4uk9iGd3iJ4QQUuqS1+61uesTJBl3th6DlJNvs7/bGw7g7Buz7yanha/feRJnX5+F2xsPuCBqxzly297gklv8eZBxGfbUhOVIBsdtF1yTkJKjBJUQQkip4pIMfUqGfW0NEnSpmcW2yT59DddmrDQmvPfP8ZRkgHNcm77S4TmtrmDa5tXFba1zdIjOdiJbadFWpx5FCSohhJDSJTDjYW9zRfG3oG+t2Gm7P4Hh1sqddl/TVbxjIqEMDbDdUGAI6tbMBVf0AUM1u1oyVAFDiAuuSUjJUYJKCCGkVDHG4Ne0tl1JqjI0AKpw6+WQZJ0e6btP2S7SL8lI33UKsk7vaLglwkQB4Y90tt1OEBDSr13Jr8cY1OIzMK7KKo4IlfAUGKOlKdbQKn7PogSVEEJIqQt7sEPRWqX3Ywxhg+LAROsfXVJOvu1+CskcUrbt+ayuFjYoDkEPNDc+uD8/EQRAEBD9zhNQV3VNXVKV8CQExACwNvIsgqEqVOJIl1yPEFegBJUQQkipC2jfEEE9W1pvIDD4xNZA2IMdi+1H9NYAzM5RKcZcNM/TMUwQUOutx1Bz7MPQRN1Th5UxBMY1RINvXkKVTo1ddz3mCx/lIois8O9XLDiMo6Uii4WvcikV6reBRlA9i8byCSGElDrGGGqNewSayGDcWv6v2Up9plIgpG8bVB8VD0FV/MeWoFYioF0DZOw/B8jF3OYXBAS0awBBrXTVW3AIEwSExLdBcN/W0KdkQMrXQVnFDwo/L7dcT2Ah8FUuhSSfgE5eA440MARAKQyAyFqA2ZvUV2ZlYCepHTt24IsvvsChQ4eQmJiIlStXYvDgwVbbr1ixArNmzcLRo0eh1WrRqFEjTJo0CX369DG1mTdvHkaOLDp6npeXB43G87/AFaIElRBCSJnABAERQx9A+KOdkXnoAvR3siH6ahDQqp5DI53hj3RGxt4zxTeSZYQ/3KmEEZccY8yjNVlFoQm8hCYeux5xrZycHDRr1gwjR47EI488YrP9jh070KtXL3z22WcIDAzE3LlzMXDgQOzbtw8tWrQwtfP398e5c+fMXluaySlACSohhJAyRlApERgX6/Tr/ZpEI+qlAUiYvdY4p/PekdSCx1EvD4Rfk2gXREsqC84BLrt2BNVW6d/7xcfHIz4+3u7206ZNM3v82WefYfXq1fjzzz/NElTGGKpWrepYMG5GCSohhJAKJ2xwR3hFRyBp+Q5k7i8YGWIMAW3qIfzhzvBrVrt0AyTkHpmZ5rV91Wo11Gq1y68jyzKysrIQFBRkdj47Oxs1a9aEJElo3rw5Pv74Y7MEtjRQgkoIIaRC8mtWG37NakPK1ULKyYPo4wXR2/Uf+qRycMeipsL+oqKizM5PnDgRkyZNcum1AOCrr75CTk4OhgwZYjrXoEEDzJs3D02aNEFmZiamT5+Ojh074tixY6hbt67LY7AXJaiEEEIqNNFbTYkpKdMSEhLg7+9veuyO0dPFixdj0qRJWL16NcLC7laPaN++Pdq3b2963LFjR7Rs2RLffvstZsyY4fI47EUJKiGEEEKILRyu3wm2oD9/f3+zBNXVli5dilGjRmHZsmXo2bNnsW0FQUCbNm1w4cIFt8VjD6qDSgghhBBSQS1evBgjRozAokWL0L9/f5vtOec4evQoIiIiPBCddTSCSgghhBBigzvnoNorOzsbFy9eND2+cuUKjh49iqCgINSoUQMTJkzAjRs38NtvvwEwJqfPPPMMpk+fjvbt2yMpKQkA4OXlhYCAAADA5MmT0b59e9StWxeZmZmYMWMGjh49ipkzZ7roXTqHRlAJIYQQQmwoCztJHTx4EC1atDCtsB83bhxatGiBDz/8EACQmJiI69evm9r/8MMPMBgMGD16NCIiIkzH2LFjTW3S09PxwgsvoGHDhujduzdu3LiBHTt2oG3bti74W3Me49zRKlzlV2ZmJgICApCRkeHWuR6EEEIIcZ3S/PwuvPbpZ5+En0rl0r6zdDrE/rKY8hIL6BY/IYQQAkDW6XFnxwmkbjkMfWomRF8vVOnSBMG9WkHh654tSEn5wWXm+kL9Lu6vIqEElRBCSKWXn5CC8+/+An1KOsCYaYufnLPXcfO3zYiZ+Az8m8eUbpCEVCI0B5UQQkilZsjMwfnxP0GfWrCbz70z3zgg5+tx8YN5yLuSVDoBkrKBM/ccxCJKUAkhhFQ4uRdv4vZfB3F70yHkXbtVbNuU9Qegv5MNyLLlBpyDSzISf9/m+kAJIRbRLX5CCCEVRvbJq0iY/SdyL940O+/buBaiXhkE79pFazumrNtrPmpqiSzjzo4TMIx+kOajVlJlocxUZUIjqIQQQiqEzMMXcW78T8i9lFjkuezT13D2jVnIOf+f2Xkuy9CnZNh3AUmG/radbQkhJeJQgpqXl4edO3fi9OnTRZ7Lz883FYYlhBBCPEnWG3Bl6mJA5pZHQ2UOrjfgyudLYVZdkTEwhWj3dZiKbjxWVmWhDmplYneCev78eTRs2BBdunRBkyZN0K1bNyQm3v0tNSMjAyNHjnRLkIQQQiqm/IRkJP2xAzcXbMHtvw5Cysl3qp/03adhyMwt/la9zKG9cRvZxy+bTjHG4NeiDiDY/jhUhgZAXTXIqfhI+ce5ew5imd0J6vjx49GkSRMkJyfj3Llz8Pf3R8eOHc12LCCEEELsoUvJwPnxP+PU89/gxi8bkbR4K659sxzHnvwUN+ZtApesLFiyIuvIRUC04yNNFJB55JLZqbAH46wvkCrEGMIe7ABmRyJLCCk5u7/Tdu/ejc8++wwhISGoU6cO1qxZg/j4eHTu3BmXL1+23QEhhBACQJ+WhbOvf4+sk1eMJ2RuSki5zoCkJVtxbfoKOLLRoWwwAHY0Z4yBGySzc/6t6iF0YPviXgS/ptEIe7CD3fGQiodu8XuW3QlqXl4eFArzuTczZ87EoEGD0LVrV5w/f97lwRFCCKl4bvy2yVjWqZhR0tRNh5B94ordfWoiQ2BPhsoNEtSRwWbnGGOIemUQqr/QH4pAH7PnBI0K4Q93Qp2PR0JQ0vxTQu7366+/Yt26dabHb7/9NgIDA9GhQwdcu3bN6X7t/m5r0KABDh48iIYNG5qd//bbb8E5x6BBg5wOghBCSOUg5eQj7e8jtm+piwKS/9wDv6a17eo3uFcr3Jy/xWY7phARGNew6HnGEP5wJ4QNikPW8cvQp2VB9NHAr0UdiBrX7r9OyimZGQ9X91nOffbZZ5g1axYAYM+ePfjuu+8wbdo0rF27Fm+88QZWrFjhVL92j6A+9NBDWLx4scXnvvvuOzz55JMO3Y4hhBBS+eReugmul2w3lGSHRlBVoQEIHdQesPF5zw0STo76CknLdlj8zGIKEf4t6yK4Z0sExsVSckqIDQkJCahTpw4AYNWqVXj00UfxwgsvYMqUKfj333+d7tfuBHXChAlYv3691ee///57yLZ+IyaEEFKpcdn+gQxH2gJA1Av9EdyntfGBYD1TlXO1uDFnA27M2ehQ/6Ryozmolvn6+iI1NRUAsGnTJvTs2RMAoNFokJeX53S/tByREEKIx2iiQgFmx4eywOAdXXTXp+IwUUSt1x9Bw+9fs6sc1K0/dhTZcYoQ4phevXrhueeew3PPPYfz58+jf//+AIBTp06hVq1aTvdLCSohhBCPUQX7I6Bdg2JHOAEAMkdIfBunrqEM8oP21h3bDQUByWv3OHUNUvnQCKplM2fORFxcHFJSUrB8+XIEBxsXIR46dAhPPvmk0/3SkkRCCCEeVW14b2QeuQiuNxh3frLi2oyVyL10ExFPdIfoo7G7/9zz/xVbIcBElpF1rGRlEmWdAem7TuL2xoPQJt+B6KVCYIdGCIlvC1Wwf4n6JmWLOxLKipCgBgYG4rvvvityfvLkySXqlxJUQgghHuUVXRX1pozCpY8XwHAn2ziaaiFRlXO1uLX8X2TsP4v6X74EhZ+XXf07UuT//pqojtAm3cGFd+dAezPV7D3kXb2FpCXbUOvtIQjq0tTp/gkpq44fP25326ZNnfsecDhB3bFjBzp06FCkJqrBYMDu3bvRpUsXpwIhhBBSefjG1kST38bjzo4TuPbNcnDZSqIoc+QnpOD6zFWo/Y59tws1NcLsC0Jg8IquamfE5qR8Hc6/8zN0yemmOE1kDi5LuDJlCZQBvvBrZl+pLFLWueOWfPkcQW3evLlx0wsr1ZsKn2OMQZKc+yXQ4QS1e/fuSExMRFiY+Q+AjIwMdO/e3elACCGEVC6CUgEuybZHMWWOOztOQP98fyjtuG2uqRYC3ybRyD51tdgpBJA5wgYUs4NUMdL+OQpdUlrxjRhwc8EW1G/2glPXIKSsunLF/hJwznI4QS3MiO+XmpoKHx8fC68ghBBSkXBJRvruU0heswc55xIAzuEVHYGwQXGo0rWpQzsupe8+ZRxEslVRSubI2H/O7oVT1Ub2wbn//VjQt4XOBQbfxtHwb1XP7ljvdXv9PttxyxzZJ65Am5gGdYTtqgKkjOPMeLi6z3KoZs2abr+G3T9FHn74YQDGYdsRI0ZArVabnpMkCcePH0eHDrRPMSGEVGSyzoBLHy9A5oFzZvMucy/cwNUvlyFl3T7U/WSk3YuapJx8e3YoBQQGKU9rd5y+sTVR96PhuPTpIsi5WmNpK84BUQAkGf4t66L2hCfBROeK2WiT0uyLu6AtJaikIps/fz5mz56NK1euYM+ePahZsyamTZuG6OhoPPjgg071aXeCGhAQAMA4gurn5wcvr7uT1VUqFdq3b4/nn3/eqSAIIYSUD9dnrkbmwfPGB/fePi8Ypcw5l4DLU5eg7scj7OpPFRoACILtrU9lbtft/Xv5t6qHpovexZ1tx5Bx4BxkrR6q8CoI6d0KPvWjHOrrfsyBUWJBrSzRtUjZwGXj4eo+y7tZs2bhww8/xOuvv45PP/3UNNUzMDAQ06ZNc3+COnfuXABArVq18NZbb5XK7fwdO3bgiy++wKFDh5CYmIiVK1di8ODBHo+DEEIqI11qJlI3H7J8y7yQzJF54BzyribBq5btBUjBPVsi7Z+jNtsJ3moEtmsAANDeuoO0f45Cn5oBQaNGYFxD+MTWtDj9TNSoENK3DUL6OldT1ZqAdg2QuvmwzXJWoq8G3nUiXXpte8g8BXp5BSR+GQxKiCwOSqEXGKOtW4lrffvtt/jpp58wePBgTJ061XS+devWeOutt5zu1+E5qBMnTnT6YiWVk5ODZs2aYeTIkXjkkUdKLQ5CCKmM7mw7Zt9tbVFA6t9HUH1UvM2mfs1j4F0nErlXkopN9qo+0hlgDFe++N2Y0DKYdqS69ccOeNWOQO33h0ITGWLfmymhsIFxSN14sPhGAkNov3YQVJ4bQeVchlb6Elr5Jxj/sQqnMCxCvhQEL8U3UAqdPRZPRUJ1UC27cuUKWrRoUeS8Wq1GTk6O0/06PPnm1q1bGDZsGCIjI6FQKCCKotnhTvHx8fjkk09M82EJIYR4jj4ty745m5xDn5ppV59MEFDnoxHQVCtILO8dBRWM1wru0xrhQ7ri0sfzjckp58bpBZJsSmrzrt7CuTdmQ5eS7sA7cp53TCQiR/Sx3kBg8K4TiYihD3gknkL50qfQyrMBSABkAIaCA+C4g1zDszDI+zwaU0VBO0lZFh0djaNHjxY5v2HDBsTGxjrdr8MjqCNGjMD169fxwQcfICIiwuItlbJCq9VCq707qT4z074fmIQQQooSvNXgxZVtKsQYRG+17XYFlEF+aDhjNNK2HkPyn3uQ/99tMFGAX7PaCBvUAX4tYpC+6xQyD16w3oksw5CVh5sL/0at1z1zhy3iiW5Qhfjj5oK/zUpOCWolQvq2QeTIPhA0nrulLvHL0Mlzi2nBAXDkGSbBV7m+TH9+k/Ljf//7H0aPHo38/HxwzrF//34sXrwYU6ZMwc8//+x0vw4nqDt37sS///6L5s2bO31RT5kyZUqJt9oihBBiFBgXi8T5W2w3lGQEdmjsUN+CRoWQ+DZWy0il/LnX6o5TJrKMtL+PIOr5/g5tjVoSwT1bIqhHC+ScuQ5dSgYEjRJ+TWo7lKC7ik5aBECEcfTUGhkyzkHix6FgzTwUWcVAt/gtGzlyJAwGA95++23k5uZi6NChqFatGqZPn44nnnjC6X4dTlCjoqKs7hxQ1kyYMAHjxo0zPc7MzERUVMlWbhJCSGXlXTsCvo1rIfv0deur7gUB6ogg+DU37p5kyMpF6qZDyDh0HrJWD021EIT0bQOfhjUcGsHLOf9f8clpAa6XkHc9Gb4Na9jdd0kxxuAb6/66kLZI/DiKT07vbXsSClCCSlzj+eefx/PPP4/bt29DluUimzk5w+EEddq0aXjnnXfwww8/oFatWiUOwJ3UarVZvVZCCCElE/3OEzg3bjZ0tzOKJoyCANFXgzqThoEJAu7sOIErX/4OrjeYFlflnE1A6qZD8GtZBzHvP10qI40VlyOjceV/5M7TOHf9iGc5Ge+zS3JyMs6dOwfGGBhjCA0NLVF/Di+Sevzxx7Ft2zbExMTAz88PQUFBZgchhJCKSxUSgAYzRiNsUJzZ/EqmVCCkTys0/HYMNFFhyDx8AZenLAbXGcxX/hcsaso6egmXJv8Gbqv+aQHvetWMt/htYEoRmqiSfTCWR5xngqEK7P1YV7Cm7g2IVBqZmZmmxfNdu3ZFly5dEBkZiaeffhoZGRlO9+vUCGppyc7OxsWLF02Pr1y5gqNHjyIoKAg1anjudg4hhFRmykBfRL00ENVG9EH+f7cBzqGODDab9/nfnA3FdyJzZB27jKyjl+Dfsq7Na4YNjEP2scvFNxIFBD3QAgpfr+LbVSCcZyNfmgqd/AcAnR2vECCyRhAFx+YIE9BWp1Y899xzOHr0KNatW4e4uDgwxrB7926MHTsWzz//PH7//Xen+nU4QR0+fLhTF3KFgwcPonv37qbHhfNLhw8fjnnz5pVSVIQQUrFwziHxg9DLm8CRDQFhUIoPQmS1zdoJGpXFIvS5F28i71Ki7QuJAlLW7bMrQQ2Mi4VfyzrIOnrJ8lxUQYDCR4PIp3rYvm4FwXkOsg1PQuZnYd/cUwGAAhqRFg8T11m3bh3++usvdOrUyXSuT58++Omnn9C3b1+n+3U4QQWAS5cuYe7cubh06RKmT5+OsLAwbNy4EVFRUWjUqJHTwdjSrVu3crNAixBCyiOZX0eO4WXI/AzufkRwaOVvoWC94a34Eoz5FttH/n8p9l1MkpF37ZZdTZkooM7EZ3Bt2gqkbT1qvN1fuMhKkqGpEYqYD56GKizQvmtXAPnStwX/TramSRhX9jNEwFvxDRRCc/cHVwHRKn7LgoODERAQUOR8QEAAqlSp4nS/Ds9B3b59O5o0aYJ9+/ZhxYoVyM7OBgAcP368VHeZIoQQUjIyv4Vs/WOQ+fmCM4VF3o2jcwa+BTmGkeC8+FvJTGH/pi2CwrE97aPHP47G895G5FM9ENKnNcIHd0T9L19E7Kyxd4v9VwKc50MnL4Lt5JRBQB14K+bCT7kdCqG1J8KrkKhQv2Xvv/8+xo0bh8TEu3dNkpKS8L///Q8ffPCB0/06PIL6zjvv4JNPPsG4cePg5+dnOt+9e3dMnz7d6UAIIYSULq30PTjSYP12sQyJH4JeXgeV+JDVfnxja9quWQoAAoNfyzoOx6muWgURlehWviUSPwkg246WHBxpUApd3R0SqURatGhhVibuwoULqFmzpmk90PXr16FWq5GSkoIXX3zRqWs4nKCeOHECixYtKnI+NDQUqampTgVBCCGkdHGeW7DQxtZcRgE6+bdiE1RlkB8COzZG+q5T1uulAoDMETqgnVPxEq3tJgW4A22JdVw2Hq7uszwaPHiw26/hcIIaGBiIxMREREdHm50/cuQIqlWr5rLACCGEeI7MrwHIs6clJH7aZquoF/sj59RV6NNzrCap1Z7tC02k627LS3layHk6iL5eEFROLbEoNwRmb+UaBoGV/iYCpGLxxJROh7+Dhw4divHjx2PZsmVgjEGWZezatQtvvfUWnnnmGXfESAghpJxRhQSgwfTRuPbtSmTuP2c8yRjAORRVfFFteG+E9LW8rakjOOfI2HsGt1bsRPaJK8bLKEUEdW+O8Ic7w6tWeImvURYJLAoiaw+J70fx81A51MJQT4VVodEiKc9yOEH99NNPMWLECFSrVg2cc8TGxkKSJAwdOhTvv/++O2IkhBDiZgKrBcAbQK6tlhCZfTU0VaEBqPvRCGiT7iDryEXIej3UVYPg36oumGj/QiprOOf476f1SF6x06yIP9dLSP37CNL+OYqYD59GQNsGJb5WWaQRX0eOYSiMu0JZmu8rQkANKIVBHo6MVCaSJOGbb77B77//juvXr0OnM19EmZaW5lS/Dq/iVyqVWLhwIc6fP4/ff/8dCxYswNmzZzF//nyILviBQwghxPMY84JKGAJjSaLiyFAJjt0tU1etgpD4Nggb1AEBbRu4JDkFgLQth43JKVB0QZYkg0sSLn28ELrkdJdcr6xRCG3hrZgJQAnzj3Oh4L+14KNcAMYqz8YF7kSr+C2bPHkyvv76awwZMgQZGRkYN24cHn74YQiCgEmTJjndr9OTdGJiYhATE+P0hYn7ZGfrcOb0bciSjDr1ghEcTD+cCCG2qcWXoZc3giMFlhdLCRBZOyiFfp4OrQjOOZJ+32598BDG81ySkLJuH6qN7OPJ8DxGKfSBn3IndPLvMMibwHkOBFYdKnEIFKwnGFOWdoikglu4cCF++ukn9O/fH5MnT8aTTz6JmJgYNG3aFHv37sVrr73mVL8OJ6iSJGHevHn4+++/kZycDPm+ye///POPU4GQkku+lYOpU3Zh4W/HkZdnAAAoFAIefqQB3nm/E+rUCSrlCAkhZZnAQuGrXIZcw6uQ+FEYR1MZjHMcOZSsP7wUU8pE0pN/LRn5CXZsCCBzpP59pMImqAAgsBBoxFcA8ZXSDqVCozmoliUlJaFJkyYAAF9fX2RkZAAABgwY4Nk6qGPHjsW8efPQv39/NG7c2KwOFik9N/7LRK/u85GYmA1JujucYDDIWP7HGWxYfxEbNj+Fps0q5oIBQohrCKwafJUrYJCPG0fkkA3GQqESHoTAqpd2eCaGLFtzZe+Ssu1vWxqMW8vug1aaDwPfBUCCwGpDLTwFpTAIjGlKO0RCrKpevToSExNRo0YN1KlTB5s2bULLli1x4MABqNVqp/t1OEFdsmQJfv/9d/TrV/q3eMhdz49aWyQ5LSRJHLm5ejz52HIcP/MSRNHhqceEkEpGITSFQmha2mFYpfD3trut6Gt/W0/jnCNPmgS9PB+FW5ICgMxPIU96B1rpF/go50NgoaUaJ6ERVGseeugh/P3332jXrh3Gjh2LJ598EnPmzMH169fxxhtvON2vwwmqSqVCnTqO7/xB3OfM6RTs3HG92DaSxJGQkIlNGy8hvn9dD0VGCCHuoakRBk1UKPL/S7E+BxUABIbgni08FpejtPLsguQUMJ/3Kxf89xJyDc/BR7ESjDk+uCDzFEj8ADjXQWC1ILJmLr/zybkEA98Og7wTgBYCqwGl8HCFS6opQbVs6tSppj8/+uijiIqKwq5du1CnTh0MGuR8BQmHv9rffPNNTJ8+HZzb2MKOeMz6dRchira/yBUKAevWXvBARIQQ4l6MMVQd0rX45JQBTBQR2q9s7lbFeT600mwbrSRI/AQkvtuhvmWeghz9WGTpOyDXMAZ50jjkGB5Gtr4P9PIW54O+j0E+gix9V+QanoNOXgCdvAz50hfI0schz/AJODe47FqkfGjXrh3GjRuHdu3a4aOPPnK6H4cT1J07d2LhwoWIiYnBwIED8fDDD5sdxPOys3QQBNsJqixzZGfpbLYjhJDyIKhnS4Q/0tn44P6fgaIAphAR8+HTUIUFejw2exj4VgBZdrQUoZOW292vzFOQrX8YBr4e91djMI7IvgCd9IdDsVoiyaeQYxgKjqSCM4aCQwYgQyfPRZ6h4tRHLwtlpnbs2IGBAwciMjISjDGsWrXK5mu2b9+OVq1aQaPRoHbt2pg9u+gvRcuXL0dsbCzUajViY2OxcuVKh+KyJCkpCZMnT3b69Q4nqIGBgXjooYfQtWtXhISEICAgwOwgnhdZzQ8Gg+0NfQWBISLSzwMREUKI+zHGUP35foiZ9Az8mtS+e14pIrhXSzT87lUEtKlfihEWT+ZJsO9jWIKMm3b3m2f4qCBptFQqzDjknCdNgMxv2d2nxetIn+BuQmoJh57/DoN8vETXIXfl5OSgWbNm+O677+xqf+XKFfTr1w+dO3fGkSNH8O677+K1117D8uV3f+HZs2cPHn/8cQwbNgzHjh3DsGHDMGTIEOzbt89db8MujFeie/WZmZkICAhARkYG/P39Szscl0m9nYt6tb+DXm87Sd21bySaNKWV/ISQikfK10HO10H00UBQOl3m22N00u/Ik96xoyWDgnWDj3KOzZYyT0aWvgOK3/4UAASoxVehEcfacf2iJH4Z2fqedrQUoWSPwFs51XbTYpTm53fhtbf1eAO+CudXpVuSbdCi29/fOPW+GGNYuXIlBg8ebLXN+PHjsWbNGpw5c8Z07qWXXsKxY8ewZ88eAMDjjz+OzMxMbNiwwdSmb9++qFKlChYvXuzYG7rHsWPH0LJlS0iSpV+UbHN6OXdKSgp27tyJXbt2ISXFjlp0xG2CQ7zx3AstUNy8d1Fk6NWnNiWnhJBSpU/NROLCv3Hhw3m48ME83Ph1k8t2ehI1KigDfctFcgoACqEr7PsY5lAKve3q0yDvhe3kFABkGOTtdvVpiSSfsrdlQU1dUpzMzEyzQ6vVuqTfPXv2oHdv86+dPn364ODBg9Dr9cW22b3bsXnPrubwd3FOTg5effVV/Pbbb6Yi/aIo4plnnsG3334Lb++yW86jIvtkygNISsrByuVnIYrMVG6q8M+t20Til19pP2ZCSOngnOPWsh24Me8v44mCrUkzD51H0pJtqDqkKyJH9K5UtbUZwsAQDY5LxbQSAPhCKQy0s1f7ExuOfLvbEveu4o+KijI7P3HixBJtE1ooKSkJ4eHmA1Ph4eEwGAy4ffs2IiIirLZJSkpCccaNG1fs8yUdvHQ4QR03bhy2b9+OP//8Ex07dgRgXDj12muv4c0338SsWbNKFBBxjlIpYu5vD2Lo003w0+xD2LvnBmTO0bhJGJ5/oSUGP1wfSqVr9r8mhBBHJa/ejRu/bCz6REGimrR0G5hCQOSwXh6OrPTo5J9tJKcAwOEtzgZj9g3+CKymnVdnkPl5ZOgaQEAtqMSnoRIetvs6jNl7O5pBZGW3zFdZkZCQYHaLvyQF7u93/y99hTM77z1vqY2tXxaPHDli89pdunSxN8wiHE5Qly9fjj/++APdunUznevXrx+8vLwwZMgQSlBLkSAw9Okbgz59Y0o7FEIIMZHytLg5b5PNdolLtiF0YByUgb4eiKp0ca5FvmTPQhcOxuxPVkTWGgxR4Eiw2a/x0EHGBeRLH0InzYOPciEEZnsqmEHeZmdEHEox3s62ZZs7R1D9/f3dMre2atWqRUZCk5OToVAoEBwcXGyb+0dV77d161bXBnsfh+eg5ubmWgw6LCwMubllezs5Qgghnndn+3HI+XaUuJM5Urccdn9AZYCB/w27S0zJy+zulzEBGvF/DkZjHFGTcQ05hmfBue05rAZ5lwP9V4zcgHP3HO4UFxeHzZs3m53btGkTWrduDaVSWWybDh06uDc4GxxOUOPi4jBx4kTk59+du5KXl4fJkycjLi7OpcERQggp//ITUsAUdkwxEhjyrye7P6AyQOY3YNza1BYJMr87Gsq5Hnp5O3TSUujl9eA8s8grVOIAaMTJMH7EO/IxL0HmZ2DgO+1qay/OnVvFTYrKzs7G0aNHcfToUQDGMlJHjx7F9evG3SQnTJiAZ555xtT+pZdewrVr1zBu3DicOXMGv/zyC+bMmYO33nrL1Gbs2LHYtGkTPv/8c5w9exaff/45tmzZgtdff92Tb60Ih2/xT58+HX379kX16tXRrJlxy7SjR49Co9Hgr7/+ckeMhBBCyjNRsHv3QSZWlrnyGti32p6BwQucc+jkudBK34Mj7Z7nVVAKj8FLfAeM+ZjOqsVhUAoPQCctgp5vB+ep4LCn7qkInbQCSqH4uYMCawCZX4c9iarIKsj26G64xQ8H+zt48CC6d+9uely4UGn48OGYN28eEhMTTckqAERHR2P9+vV44403MHPmTERGRmLGjBl45JFHTG06dOiAJUuW4P3338cHH3yAmJgYLF26FO3ale4ObE7VQc3Ly8OCBQtw9uxZcM4RGxuLp556Cl5eXu6I0WUqah1UQggpyzL2ncXFib/a1bbWW48huGdLN0dU+iR+Ddn6B1D8Xq1GGvFTyPwidPJcKy0EiKwxfBSLwZjlz2GtNBf50qewJykWWRv4KpcW28Yg70SO4Zli2xjjagJfZcl3JSoLdVD/7voWfFxcBzXHoEWP7V9SXmKBU8XivLy88Pzzz7s6FkIIIeWcrDdAztNC8FKb6pH6t64HZWgA9LczrU+6Y4Doo0GVLk08GG3pEVlNKFiXgtvp1kYhGQAfCIhEvvxeMb3JkPhJaKXZ0CjesNKTD+wfsbW946DIOkLBOsPAd1np1zgyqBHt2YigfHDnIilSlFOF+s+dO4cxY8agR48e6NmzJ8aMGYOzZ8+6OjZCCCHlRM65BFyeshhHBk/EsSGf4MiDH+LSp4uQfeY6mCgg+q3HAIHB4o4izPifWm8+BkGl9HTopcZLMRUMobA8F1UAIMJbMRM6+Xcrbe4lQycvBOd6i88qhO529AEYNwXoa7MVYwzeillQsMLbzYV9F/77esFb8QMUQuneJibut3HjRuzceXfe8syZM9G8eXMMHToUd+7ccbpfhxPUP/74A40bN8ahQ4fQrFkzNG3aFIcPH0aTJk2wbJn9Kw0JIYRUDLf/Ooizr8/CnZ0nAalgNE3mSN99CufemIWU9fvh1ywG9aY+B031EOPzAjMeAFThQajz0XAExsWW0jsoHQILh69yNZTsIQDmibnI2sFHsRRKoTMMfAfsmevJkQaZX7ByrVAo2UAU/7EvgCEQSmGAXfEz5g0f5U/wVayBSngSIusMBesFjfgx/JX7oBR62NVPeVE4gurqo7z73//+h8xM42K9EydO4M0330S/fv1w+fJlm8X8i+PwLf63334bEyZMwEcffWR2fuLEiRg/fjwee+wxp4MhhBBSvuScvY5r01YYb91L992+L0hWr89YCa+aYfBrEo3YH99AzqlryDlnXJnuFRMJv2a1K9UOUvcSWCi8lf8Hmb8LiZ8AoIfAYiCaFdw32N0fh+URVADwUkyCpD8DGRdQ9La8CEAJb8WPYEzjwDsARKExvITGDr2GVBxXrlxBbKzxl8vly5djwIAB+Oyzz3D48GH069fP6X4dTlCTkpLMShgUevrpp/HFF184HQghhJDy59aKXcaR0PuT03uJAm6t2AnfRrXAGINv41rwbVzLYzG6CuccEt8HrTQfEj8EgENkTaASn4aCdQFjTs2aAwAILBAC62z5OURBxiXYXlAlQGDVrD7LmD98lcuglWYbpwMgo+AZEQoWD404BqJQz6n4KwOag2qZSqUy1cHfsmWLKUcMCgoyjaw6w+EEtVu3bvj3339Rp4552YidO3eic2fL31yEEEIqHllnwJ1d99zWt0aSkb7nNOR8HQSNyjPBuRjnBuQZ3oaer4JxtNF4y93At8Ng+Aci6whv8UcIguur2ajEp5EvTbbRSoSC9YDAQoptxZgvNIq3oOavQuaXwaGHwKIgsCquC7iC4jIDl12coLq4v9LQqVMnjBs3Dh07dsT+/fuxdKmxAsT58+dRvXp1p/t1OEEdNGgQxo8fj0OHDqF9+/YAgL1792LZsmWYPHky1qxZY9aWEEJIxSTl5ttOTgvJHIacfKgKElRukMAlGUylKBe39/OlqdDz1QWP7p0PavyzxHchyxAHL/E9KIWHwZjr6rmqhIehleaA4yYsz0VlAARoxDF298mYGiJr6KoQSSX23Xff4ZVXXsEff/yBWbNmoVo14yj+hg0b0Lev7QV31jhcB1UQ7LuFwRiDJJWt3SOoDiohhLiOrDPgyOAPAdmOjxHG0OyPD5Gx9wySV+9G7vn/AADKYD+EDoxDaP92UPh5uzli58g8DVn69rB3LqiC9YW3YgYYc6qSo5UYbiBH/wxkXIFxoZMM8xXzs6AUKu5dzLJQB3Vj3DvwUTg2P9eWHEM++u6ZSnmJBQ5PmJFl2a6jrCWnhBBCXEtQKYwr720NXIgC/NvUw9XPl+LqF78j98IN01P61Czc/HUzTr8yA9ok50vSuJNeXgNHtvY08L+glb93aQwCqwZf5UZ4K2ZCwbpCYA0gsjbQiB/AX7m7QienpGw7fPgwTpw4YXq8evVqDB48GO+++y50Op3T/To/o5sQQkilF/5wJ0C2PQdVUCmRceCc8fH9N+44hz41Cxc/mAtu75QBD5L5TTg2I45DJ80F51qXxsGYEkohHj7KOfBTroevcgnU4ggw5vjIm8xvwyDvgkHeBZnfdmmcFRWVmbLsxRdfxPnz5wEAly9fxhNPPAFvb28sW7YMb7/9ttP9OnX/Yf/+/di2bRuSk5Mh3/eD6euvv3Y6GEIIIeWLb6NaiBo9CAkz1xhHUu/9TCh4XO3Zvrg5f4v1XaQAQJaRn5CCzEPnEdC2gfsDdwCDF+zbhekujgwY+F4oWVf3BOUkiV9DvuErGPgG3B0VFqFgfaFRvHVfeStCbDt//jyaN28OAFi2bBm6dOmCRYsWYdeuXXjiiScwbdo0p/p1OEH97LPP8P7776N+/foIDw83m9xeHia6E0IIca2wgXHwqlUVt/7YgYz954yJKGMIaFMP4Q93hi4lHVxvx/xNgSH1n6NlLkFVCA9AK3/r8Os4L1tTFiR+Adn6xwDk4P6FXga+Edn6f+GrXAaR1S2lCMs2KjNlGefcNFi5ZcsWDBhg3OghKioKt287PzrvcII6ffp0/PLLLxgxYoTTFyWEEFKx+DWJhl+TaEh5WkjZ+RB9NRC91ACAW8v/NdZKtbWYSubQ38nyQLSOEVlTCKwRZH4WjsxFZSzYfUE5iHOOXP1oFE1OC0kAcpCrfwW+yk004ETs1rp1a3zyySfo2bMntm/fjlmzZgEwFvAPDw93ul+HE1RBENCxY0enL0gIIaTiEr3UpsTUdM5HY99Kf4FB6e/jpsicZ9x3fjpy9I8VFLe3fbufoQoUzPl96A3yMejlZQXzX72gFB6AUujv8C5PhSS+HzIu2moFGZcg8X1QsPZOXacioxFUy6ZNm4annnoKq1atwnvvvWeqk//HH3+gQ4cOTvfrcIL6xhtvYObMmU7PKSCEEFK5BLRvCIiC7ZqpMkeVLk08ExQAzmUY+L8wyFvBkQsBkVCJj0BgUUXaiqw2fJWrkav/BBI22exbJY4CY45vSsB5JnIMYyDxnbi7IYAAg7QBedLH8FHMgkKIK+b1BovlrfTyPzB+5NuaaqGAXv4HCoES1PtRgmpZ06ZNzVbxF/riiy8gis7XA3Y4QX3rrbfQv39/xMTEIDY2Fkql0uz5FStWOB0MKRs458jN1cPLSwlBKP/fPISQ0qUM9EVwjxZI3XLY+kiqIEAZ5GcsW+UBknwaOYaXwZEA40ehMS6t/C2U7EF4KaaAMfV9r/ICZzeL2XGUAeBQssFQCy85HBPnBuQYnoPEDxdGWfD/wsQ+GzmGkfBR/A6F0NTsvWilX6HnawHkAfCFShgMlTgcIospaJXrQCSOtCXEMo2mZDVjHU5QX331VWzduhXdu3dHcHAwzVOpQM6euY3Z3x/E4oUnkZdngEIhYOCD9fDKmDZo1976/s6EEGJL1CuDkJ+QgpyzCUVX8wsCRB816n48Akzhuh2YrJH4ZWQbHgeQX3DGfFRRz9eAGzLhrfgRjBmrMXIuIdfwLGR+ppieOZRsOLwUHzr12Wjgf0PiB4tpIQOQoJW+gkL4FQCgk/5AnvQOjMlxYUKbDZ28GDp5CbwVM6EUeoGxCNhXiUAGY5HWn+U3oJNXg/NbYPCBQugJkbWoFLkAjaBaJkkSvvnmG/z++++4fv16kdqnaWlpTvXrcIL622+/Yfny5ejfv79TFyRl07o/z+OZp1aBcw6DwfjhYTDI+HP1Oaxcfhb/91VPvPRKa7v6upWUjdu3cxEQoEH1KNoZgxACiBoV6n3+HJLX7EHKmj3QJacDAASNCiF9WiP8kc5QhQV6JJZ8w5cwJqfWFjzJMPB/YOD/mspEGfg2SLzobcz7SXwrgA+diksrLcTd2/pWrwAD3wmZ/weZJyFPGg/LQ7oSAIZcw2j4KtZCJTwErWRfGUiV8FCRc5znI8/wPvR8JQq3VgU4tPJsCKwRvBXfUYmqSmry5Mn4+eefMW7cOHzwwQd47733cPXqVaxatQoffujc9wLgRIIaFBSEmJgY2w1JuXHhfCqeeWoVDAa5yMBGYbL69ptbUK9+MB7oEW21n7+3XME3X+7Bju3XTeeatwjHa6+3wyOPNawUv2ETQqwTVEpUfbQLwh/uBH1qFrgkQRnkB0GltP1iF5F5Mgx8E2yPJorQSfOhFIwJqk5aAtvJIyDjOiR+CApm3y/05rGds9m/EYfEL0EnLYIxUbT2Gg6AQyf/Ci/Fp1Cyx6Dny2D9vQtQskchsAjzXriEXMNLMPCdpj7v7UPmZ5GjfxS+yjVFXluR0AiqZQsXLsRPP/2E/v37Y/LkyXjyyScRExODpk2bYu/evXjttdec6tfhnaQmTZqEiRMnIjeX5qhUFLO/PwSZ82JraIsiw7Sv9hbTx0E8NHApdu1MMDt//Fgynh2+Bh+8uxW8uAsQQioNJghQhQZAXTXIo8kpAEj8HOy71S2ZjZjK/BrsLTEl8wTbjSxyYHoD18HAt8B2TBJ08gpwLsNLMQkK1tPCtYx/VrAe8FJMLtKDgW+Gge+A9b83CRzpyJccrxVLyr+kpCQ0aWJc3Ojr64uMjAwAwIABA7Bu3Tqn+3V4BHXGjBm4dOkSwsPDUatWrSKLpA4fPmzllaSsWrzwJCRD8cmjJHFs23oNKck5CA0zLwNzYP9NjH9ri6ndveSCBREzpu1Hq9aReOiRslWAmxBSuTA4OWLFNMUsjrqvaZHFVfZRsPbQ8z9hO+lUQmCRsDsgaAHkgjFfeCu+h4HvhE6aD4kfBQCIrDlU4jAoWCfTnFuzV0vzYRzPKi6xl6CXV4DzCWDMz864yhfOGbhMI6j3q169OhITE1GjRg3UqVMHmzZtQsuWLXHgwAGo1c59LwBOJKiDBw92+mKk7NHrJWRn62w3LJCamlckQZ098yBEUYDBYP2HlyAwfDdjPyWohJBSJbCGsOdWPSBCZC1Nj5TsAWj5adgefVVAdLKGqEocBr1hlc24lGxwsQuZLL0G8AIAMCZAybpAKXSx+9USPw77Rp11kPglKFhzB2Ij5d1DDz2Ev//+G+3atcPYsWPx5JNPYs6cObh+/TreeOMNp/t1OEGdOHGi0xcjZY9CIUCjUSA/345tCAEEBpqXjeCcY9XKs8Ump4BxJPXA/pu4lZSN8Kq+TsdLCCElIbBgKFg/GPh62FqMpBafNj1SiU9AK8+00bsIJRsEgQU5FZtCaAGV8Ax08m9W+2cIhUbxJgRWBSJrA4kfQvHJowgF6w3G3F8doaKjOaiWTZ061fTnRx99FNWrV8fu3btRp04dDBo0yOl+HU5QCx06dAhnzpwBYwyxsbFo0aKF00GQ0sMYwyOPNsDSJadMC6IsEUWGVq0jUDXCPLnU6STo9fb8Zm2UkaGlBJUQUqq8FG8hW/8vOLJgOUllULD+ENndXXAEVhVe4lTkSW8XnLn/56UIAVHQKN4rUWwacSIYC4VWmg3jtqQijAkoh8ji4K34PwgsDACgFp9HruGAjR4lqMWRJYpJZI0h8QOwPYqqgshql+haZRnnRSukuaLPiqZ9+/Zo377kGz04nKAmJyfjiSeewLZt2xAYGAjOOTIyMtC9e3csWbIEoaGhJQ6K2HYrKRu/zDmKX+cew62kbHh5KTFgUD28+HIrtGrt2CrKl0a3xqKFJ4ttI0kcr71edNs+lUqEj68SOdl6m9dhDAgJ9XYoNkIIcTWBRcFH+Qdy9WMg4yyMH4WFdUQZVMJT0IjvFak8ohIfAWNVkG/4suB1pmegZIOhUbwDgQWWKDbGGDTiaKiFZ6GXN0HGTTB4QSF0hcjMq6gohZ5QC2Oglb9D0TmixmkMGvEDKATHKwrcSy0OQ65hn41WhVMPqLRgZbBmzRq72zo7iupUof7MzEycOnUKDRs2BACcPn0aw4cPx2uvvYbFixc7FQix36GDiRg8YAmysnSmRUjZ2Tr88ftpLFl0Ep9NfQBjxra1u79mzaviu1nxGPPyBggCM1voJIrGx2+N74BBg+sXeS1jDEOfaoK5c44UPwKrYOjRIxpBQV4OvFNCCHEP49al6yDxIzDI/4AjDwKLgFJ4EAKzPtCiFB6AQtkdMj8DGdcAqKFgrcBYgEvjY8wLKvFBm+00inEQ5VhopZ8g8SOm8yJrC7X4okNzTa1RsN4QWUdIfA8sj6KKYAiARvFqia9VlsmcQXbxLXlX9+cp9q5HYoxBkuyrflHktdzB2j8BAQHYsmUL2rRpY3Z+//796N27N9LT050KxBMyMzMREBCAjIwM+PuXz9/ybqfkomXTH5GVpS2yYv5ei5Y+jAGD6jnU9+6dCZg+bR82rr9ouu3QoWN1vDq2LfoPtN7XhQtpiGszB3qdZPV2BWPA+k1D0bFTDYdiIoQQYh+ZJ4PzdDAWBIGFgPMc6OV1kPhlMCggCu2gYB0trtS3hfM85BrGw8DXwThaW5hYGSCgLryVs9x6e780P78Lr7282WT4iCXbvvN+OVI+Hjk2sVznJe7i8AiqLMtFSksBgFKphCzbPxeRmEtLy0NmphbBwV7w87NeluHXeceQmak1jZxaIggMX3y+2+EEtUOnKHToFIX09HykpuYhMECN4BDbt+Tr1g3CwiUP46knVkAyyGaJs0JhHIH99vt4Sk4JqaT06dlI++codMl3IGhUCGjbAD4Na9DmHS4msDCAhYFzDq30M/KlbwDkwfRRL38Phih4K76GQmjlUN+MecFHOQMyfws6eSXkgq1OlUIviKxNpfi3pEVSnuXwr1EPPPAAxo4di5s3b5rO3bhxA2+88QZ69Ojh0uAqg/VrLyC+10LUqjYdTRvORlTVaRj6+HLs2/Ofxfbzfz1ebHIKGFfMHzmchAsXnNv/NjBQg5iYKnYlp4X69I3BvkPP4cWXWyEg0Jhge/so8eRTTfDvnpF4ZkQzp2IhhJRf3CDh+qw1OD50Cv77aT1S1u5D0rIdODduNs68PAP5CSmlHWKFpJVnIl/6DMbkFAAMBQfAcQM5hqdgkI861bfAakAjjoW34jN4Kd6DQmhbKZJTUtQ///yD2NhYZGZmFnkuIyMDjRo1wo4dO5zu3+EE9bvvvkNWVhZq1aqFmJgY1KlTB9HR0cjKysK339IuEo74aNIOPPHYcuy9JxmVZY4N6y+id48FWLSw6L7Pybdy7O7/VlK2S+K0V0xMFUz9oicSEt9Aes54JN1+EzNn90PTZuEejYMQUvo457jy5TKkrNkDyDLAObhBAiTjnba868k4O24WtInO/SJNLJP5DWilb4prAcCAPOkDT4VUcRSMoLryQDkeQZ02bRqef/55i1MTAgIC8OKLL+Kbb4r7WiyewwlqVFQUDh8+jHXr1uH111/Ha6+9hvXr1+PQoUOoXr2604HY6/vvv0d0dDQ0Gg1atWqFf//91+3XdIfVK8/iy893Ayi6+5JkMG47+soL63HyRLLZc76+Kruv4ednf1tXE4Ty+01HCCm57OOXcWfbMeubHckypFwtbsz9y6NxVXQ6aSlsf7TLkPkpZOq6IFs/HDppDTi3f8MWQgDg2LFj6Nu3r9Xne/fujUOHDjndv9N1UHv16oVevXo5fWFnLF26FK+//jq+//57dOzYET/88APi4+Nx+vRp1KhRvuY3Tv9mHwSB2ZxL+sOsQ/j2+3jTuYceaYAfZx8qdoEUAFSr7ocmTWnkkhDiHrLOgDs7TyD1r0PGuaXeGlTp1BghfVpDGeSH5D/3AqJgGjG1SJJxZ+dJ6NOzoQyk+siuYOCHYXuXLCOO/yDxm8iT/kW+FAUf5W8QWU33BliO0RxUc7du3bK4JqmQQqFASorz03jsHkG1Z66Bu0czv/76a4waNQrPPfccGjZsiGnTpiEqKgqzZs1y63Vd7eaNLBw8kGhzLqnBIGPZ76fNzj33Yksrre9iDBj9ahsaxSSEuIU2KQ2nX/wGV//vd2SduAxtYhryLt3Ezd8248Twz3Fn1ynknLlefHJaSJaRd+mm7XbETo4uVja257iJHP1QcF70M54Yufr2vjsSXk+qVq0aTpwoOhWx0PHjxxER4Vhd9nvZnaDaM9fg66+/djoQW3Q6HQ4dOoTevXubne/duzd2795t8TVarRaZmZlmR1mQnp5vd9vcHD2ke37I160bhJk/9ANjxhql92LMeAx+qAFeHl2ywszuxDnH4UOJWPHHGaxfewFpaXm2X0QIKROkPC3Oj/8Z2lvpxhP3/qJdMM/08qcLIevt2z654GXERUTWGMYi/Y6SwJEEnfy7q0MiFVS/fv3w4YcfIj+/aE6Tl5eHiRMnYsCAAU73b3eC6u65Brbcvn0bkiQhPNz8tnV4eDiSkpIsvmbKlCkICAgwHVFRUW6LzxHBwfYXq/f3V0MUzf+Zhj7VBOv+Goqu3cxvxdSKDsQXX/fC3PkPFnlNWbFh3QW0bz0H3Tr9ihHDVuOJx5ajXvR3eOXFdUhNpUSVkLIu7e8j0N26Y1z4ZIkp2WSAYMfPIcbgFV3VVeFVeirxCdh7i98SnbTQdcFUMFxmbjnKq/fffx9paWmoV68e/u///g+rV6/GmjVr8Pnnn6N+/fpIS0vDe+85v/Wv3XNQ3T3XwF73l7PgnFstcTFhwgSMGzfO9DgzM7NMJKnhVX3RsVMU9u75r9i5pKKC4YmhjSw+16lzDXTqXANJidlITMyGr68SdeoGmf1dyDKHVmuARqMoE2VA5v96DKNf2oD7Q9HpJCxeeBJ7dv+HLduecSiBJ4R4Vsq6fcYa7cWNesocUqYdFUcEAYHtG0IVTAXKXUVktaESRkInz3Xi1Rwybrg8JlIxhYeHY/fu3Xj55ZcxYcIEFO77xBhDnz598P333xcZVHSE3Qlq4VyDOnXqWHy+pHMNbAkJCYEoikVGS5OTk63+BajVaqjV1ovel6Y33mqPRwcvs/o8Y4DAGF58ufhiylUjfFE1wnxxwf59NzBr5kGsWXUOer0Mb28lnny6MV5+pTXq1Q92SfyOuvFfJl4bvRGA5dt5ksRx9Uo63h3/N3742flbAoQQ99ImpRWfnN7DJ7amcS6qpW96gUFQK1FtZO+iz5ES0YjvAVBCJ/98z1l756ZaH4iq7GiRVFE1a9bE+vXrcefOHVy8eBGcc9StWxdVqlQpcd923wd291wDW1QqFVq1aoXNmzebnd+8eTM6dOjgtuu6S+8+Mfhs6gMAjLst3UuhEKBQCPht4WDUredYQvnj7EPo1X0+Vq80JqcAkJurx7xfjqJD21+wYd0F17wBB8395ajNzzRJ4vjj99NIvZ3rkZgIIY4TirmTdr9qz/ZBUI/mBS9kxlX9BdOPVGGBqP/FC9BEhbkhysqNMQFeinfgp9wNtTgOSjYIgD1bdIpQsE7uDo9UQFWqVEGbNm3Qtm1blySngAMjqO+//z5WrFiBevXqYcyYMahfvz4YYzhz5gxmzpwJSZJKNNfAHuPGjcOwYcPQunVrxMXF4ccff8T169fx0ksvufW67jJmbFu0ah2B72cexNo15yFJHBqNAk8+1RgvvdIKDWNDHepv6z9X8dYbxgTeYDD/bVkycMhMwrChq7DnwLMOJ74l9deGS5BtlMYCAL1exq6dCRg0uL4HoiKEOMq/bX2kbT1qc4W+6OcFn/pR8GscjcineyJ1y2HoktMLtjqtD/+WdcHsmaNKnCawMGjEVwARyJdiCgr4F/fvJkEtDvdUeOUOjaB6lt0JqrvnGtjj8ccfR2pqKj766CMkJiaicePGWL9+PWrWLL912+I6RiGuYxQkSUZOjh6+viqny0NN+2ovRJFZndfKOSDJMn6YdQhffuPZ22q5uXq72+bl2b/6lxDiWWGD4pC25XDxjQSG0AHtISiNHzHqqkGIfLqnB6Ij1qiF52CQt0Pih2EtSVUJI6EQyt8dSVIxOVSo351zDez1yiuv4JVXXvHY9TxFFAX4+zs/X/Z2Si62/nPVZjvJwLF44UmPJ6h16gbh8qU7NjcYAIBatQI8EBEhxBk+9aojYlhPJM7fYrmBwOAVHQFwjstTl0BQiPBrVhtVujSFoKb5jaWFMTV8FL8hX/o/6OQlAO5O12MIgVp8GSphRKnFVx7QCKpnObWTVOFcA2JdTo4Oq1edw9Ur6fDSKPFAz1po1tx9pVRuOzBvMytLB71eglLpTK28uzjn2LUzAXN+OoKTJ5KhVAro3KUmnnuhRZEpBCNGNsOGdReL7Y8xoHZMFbRtX61EcRFC3CvyqR5QhQYgceHf0BXWQwUgqJVQVwtG3qWbyLuSWHCWIXXLYSTMXotabw9BYLuGpRJzaZJ5EvTyOnCeBsYCoRT6QmCeryjDmAZeig+h4eNg4LvBeTYYC4WCxYExpzeWrDRkDsguTiht7NdTqdFXpItxzvHNl3vxf5/vRm6OHkqlAFnmmPjBNrRqHYEffxmIunWDXH7dwEB7JsAbaTQKKBQlm/uVl6fHiKdXY8P6i1AoBNOc1zOnb2PWzIOY8H4nvPNuR1N5q959Y9CiZVUcP3ar2CkIH07qWiZKYhFCihfSuzWCe7ZEzunr0N3OgOClQvquU0jdXFAP2/TJa/y/lJuPS5Pno+4nz8K/peVqMBUN57nIM7wPPV9TcEYAICNfmgoF6wlvxf+BMc/fMWLMF0pG1RNI2UYz1F3sw/e2YdKH25GbY5xzqdfLpoTs6JEk9Oz6Gy5fvuPy61aN8EXrNhE2568qFAyPPNrALAmUJBmXL9/BubO3kZ2ts+t6L4xai782XgJgviCr8L1O+WQnfph1d+MGURSwfNUQNGkaVvCY3fMcA2PAV9N646FHGth1fUJI6WOCAN/GtRDUrRnU4UFI3XTIegkqDoBzJMz+07SGoSLjXIccw4iC5FQuOAwF/+cw8H+QrX8SnNtRL5aUCbTVqWdRgupCp04mY/o3+6w+L0kcmZlavPfOP265/tg32kG2cb9AkjhefMW4DWp+vgFff7EHjep9j+aNfkCbFj+jVvXpeOXFdbh4Mc1qHydPJGP1ynM2r/XZJzuh1d5d8BQS6o1/dgzH4t8fRo+e0ahdOxCxjULx6ti2OHb6JTz/YksH3i0hpCxJWb/P9s5RHMi/nmysjVrB6eQ/IPGDsL5qXoKM89DKv3oyLELKDbrF70I//3gEooJBMlhP3CSJY/3aC7jxXyaqVXft7ikPPtQAb/4vDl99sQeCwMwSSFE0Pp4xMx7NW1RFTo4OgwcsxYH9N83a6bQSliw6hVUrzmHN+ifQuk1kkev8OveY2W19a9Lv5GP92otmo6IKhYD+A+uh/8B6LnjHhJCyIvfiTevbn94n70oSfGPLb/UVe+ikX2HHllvQSfOhFl4CYzReVNbRIinPogTVhXbuuF5sclqIc+DQwUSzBJVzjnNnU3H7di4CAzVo1DjUqbmYEz/qipatquLb6fuxd49xyzrGgJ69auP1N9uhY6caAIB3x/9TJDktZDDIyMvT47GHl+H0+Vfg5WW+8vbqlXSbySlgnE5wxQ3TGQgh7qNLTkfK+v1I33sacp4O6qpBCOnbGoGdGpvKRlnCHCmPV8HnmXOeDxn2bYrCcQscyWBwbBGtzG9A5olg8ILA6tMiJ1Lh0K9sLiQ5sBzv3oVCSxadRNOGs9G25c/o13sROrT9BQ3qzMTcOUecmqs18MH62PTPMFy69ioOHX8BV2+8jmUrHzMlp2lpeVg4/0Sxt+gliSP1dh5WLD9b5DmNRmFXrVZZBtQa+qFJSHmRuuUwToz8Akm/b0P+1VvQ3bqDrBOXceXzpTj98nToUtKtvta3US3jblF28Gng+RXsnmXvtqKOtzfI+5CtfwpZ+s7IMQxBtmEgsvQdkS/NBOf2rSEgzuEc4LKLDyemY3///feIjo6GRqNBq1at8O+//1ptO2LECDDGihyNGjUytZk3b57FNpZ2DvUkSlBdqGmzMLtXx8c2CgEAvP3mZrwwai2uXcswez7xZjbGjvkLL4xyfkFBaJgP6tYNQpUq5iv8N/11CTqdZPP1gsCwykKC2r1HLch2xCTLHA/0qGV3vISQ0pNx8ByufrnMuEPUvb+8FvxZm5iG8+/MgayzvOlGSHzb4u9mA4DA4NMgCt61I1wUdVnlBYai06Ms8weDfbsG6qTVyDE8BYmbr3XgSIFW+ho5hmcpSa3gli5ditdffx3vvfcejhw5gs6dOyM+Ph7Xr1ue1z19+nQkJiaajoSEBAQFBeGxxx4za+fv72/WLjExERqN/dWB3IESVBca9XwLm7e+BYGhfVw11G8Qgj/XnMfs7w8V237p4tOY98tRF0YJZGZo7brDJsscaWl5Rc4PeaIRfH2UxfYhigxxHas7vF0rIaR03Pxtc/G33iUZ2hu3cWfHCYtPq6tWQeSwYnaLEhiYUoEaYwaXLNBygDEGtfgMjHNQiyNCLQwFY7Y3MJD5DeRJb+FuRYD7cUh8D7TSTMcDJnZx5yr+zMxMs0Or1VqM4euvv8aoUaPw3HPPoWHDhpg2bRqioqIwa9Ysi+0DAgJQtWpV03Hw4EHcuXMHI0eONGvHGDNrV7Wq++q224sSVBfq1LkG+g2oY/X2tyAwiCLDx589AACY9ME2u/qd+ukuV4UIAAgK8rL7tkJ4VZ8i53x9VZgzbxAEgVl8r6LIEBCowawf+5c0VEKIB+Rdu4Xc8zds329kDCnr91t9uuqT3VH9xf4QNCpjc1EAROPHjKZaCOp/8QK869g7sli+qYQnIaAWAGsboohgCIVKfNau/nTSQjtacejk38C55eSGlIzMmVsOAIiKikJAQIDpmDJlSpHr63Q6HDp0CL17m9ew7d27N3bv3m3Xe5gzZw569uxZZIv47Oxs1KxZE9WrV8eAAQNw5MgRJ/+WXIcmCLoQYwzz5g/GKy+swx/LzkChYJAkDkEw/j8gQI15CwajXftq0OkMuHDeeimneyUmZuNWUjbCq/qazp07exvr115EVrYOkZG+eOiRhggO9rKrP0myf75TdLTlbWzj+9fF6nVP4IN3t+LI4STTecaAPvExmPpFT9SqFWj2mrw8PZYtPY2ffjiM8+dSoVAI6Ni5Bl54qSV69IymAv2ElBJdkp2LGTmHNjHV6tOMMYQ/1Amh8W1xZ+dJ5P+XAqYQ4dcsBr6Na1Wq73HG/OCjXIxcw4uQ+DEYP25lGMeFDBAQAx/lTxBYiF396eUNAGxPzeLIgMSPQsHa2R0r55mQ+U2AqSCgBi24KgUJCQnw97+7cFqtLrr1+e3btyFJEsLDw83Oh4eHIykpqUj7+yUmJmLDhg1YtGiR2fkGDRpg3rx5aNKkCTIzMzF9+nR07NgRx44dQ926dZ18RyVHX4UuptEo8MtvD+Kd9zph/q/HceXyHWi8lOjZOxqDH2oATcGiodTUorfOi9M5bh46d62Bhx5ugFnfH8S/269DFI0jmAaDjPFvbcHzL7bEx591t7mF6eFDSWCCcYK2Lfn5BqvPdelaE9t3jcDxY7dw9sxtKBQC2rarhupRRctnpSTnYFD/JTh1MgWCcLcazeZNl7Bx/UU8NawJvpsVD1GkQX1CPI2pbd9iLiSoLLflnEOXnA45TwtlkB+Ce1JdY4GFwUexAhI/Ar28GhxpYAiAUugPkbV3KGHnsL+gP0e2Xe0kfhlaw0zo+Z8wbiKAglHdYVALz4Gx0p2DWNa4s8yUv7+/WYJanPu/bjjndn0tzZs3D4GBgRg8eLDZ+fbt26N9+/amxx07dkTLli3x7bffYsaMGXbF5A6UoLpJvfrB+Piz7laf9/cv+ttRcZKSsrHijzNYtvS06ZwkcVM1AL1exqyZB3HzZhbmzR9c7Cp7g0GGKDAYbFQdUCiYXYuhmjYLR9Nm4Vaf55zjiceW4+yZ2wDMSyUWluVatOAEqlX3w/sfdrF5PUKIa/k0iIKgUUHOt7HARhAQ2L6h2Skuy0jddAi3VuxE/vVk40nGENC2Pqo+3q3C1zu1hTEGBWsJhVCyhJ2xCHCeCtsr0QDBjpJVBvkIcgzDAGhx78isccHVNBjkLfBRLARjRad5kdIREhICURSLjJYmJycXGVW9H+ccv/zyC4YNGwaVSlVsW0EQ0KZNG1y4YF+pNHeh4apS4uOjKrK63hZre9gX4hxYteKcaQtSaxo0DLHZV+H1Gja07/ZTcXbtTMCB/TeLvSbnwHczDti91SohxHVEjQoh8W1sl4mSZYQOuHvrmMsyrn71B65NW4H8hOS77ThHxoHzOPfmD0jbftxNUVcuKmEIbCenDALqQGCxxbbiPA+5hucA5MPytAEZEj+JPMMnzgVbQZX2VqcqlQqtWrXC5s2bzc5v3rwZHTp0KPa127dvx8WLFzFq1Cg73ifH0aNHERFRutU2KEEtRa+82trlfYoiw0+zi68MMOSJWKjVtgfPVSoRQ55oZLOdLYsWnIBCYfubMDdHj3V/lu5vbIRUVpHDesEruqrlJLXgVPWXBkATFWY6nbJ2L9L+LlhMcX/uJBuLPF75v6XIv3nbPUFXIiphMBjCYX3RFQBwqMXXbN7u1ctrwXEHxddflaHnKyBz2mylLBk3bhx+/vln/PLLLzhz5gzeeOMNXL9+HS+99BIA4P/bu+/4qIquD+C/uXdbekICCYE0IHSkhBZ67wgWQEWKIogiilhBBewvymMHBEVAqSIgKiAdAkqHUKTXhBQCBNKT3b133j82WRKSLUm2JTlfPyvs3dm5Z7MhOTt35sy0adMwevToYs9btGgR2rVrh6ZNmxZ77P3338eWLVtw5coVxMbGYty4cYiNjTX26SyUoDrRq69FG+uh2ookcRw8kGC2jY+PBu+819liX++81xm+vuWfg5RwIwN6K3bYEkWGpMSMcp+PEFJ6orsaDT5/HtUHtQd7YJ6pulYAIqY/icChHY3HuCzj5lrTBcLvN+S4vdH0yn9iHcY84KH8BQz+MHxiKJyEGpJWjfgWVOIgi30ZFlxZM3Kng17eXfpgKylnj6ACwIgRI/DVV1/hgw8+QIsWLRATE4NNmzYZV+UnJSUVq4malpaGtWvXmhw9vXfvHiZMmIBGjRqhT58+SEhIQExMDNq2bVu2L5SN0BxUJ1KpROzYMxrPj/sLf2y4YLN+ze0QVeDlV9tCq5PwyYd7wfn95wgCA2PAtHc74ZWp1q8CNcfHRw1BYBbjkmUOTy/zc2MIIfYjuqsR+uLDqDW2LzJPX4Wcq4Mq0Bfu9WsXG5XLuXYT2pv3LHcqc6TuPoHa4wfYJ+gqRGT14KXcCq28BlppJWQkgUENBesNtTgKolB8dKwkHGmwZi4rwMBBgwau5sUXX8SLL75Y4mNLliwpdszHxwfZ2dkm+/vyyy/x5Zdf2io8m6EE1ck8PFRYtupRJCZkYN1awyKoE7E3rUoySyIIDI2bWi6OzxjDG291wKjRD2HpkhOIzS8V1aJVEEaPeQg1g73KdP6SDBgcid/Xn7cqpv4D6tnsvISQshHd1fBp29BsGynT+kokUpZzt0ysTBjzhlocB7VoeS6hyT6MUwUsla3iVpfBqgp4obqltuyTlIwSVBcRXMsLL73cFvUb+OPxoWvK3I8sczzzbAusXXMW58/fhlIpomPHEER3LD4CAgBBNT3x1rSOJfRkO0MfaYjpb+3E3dQckwulRJFh4OBI1KptXZkNQohzKf2s/xCr8PO03Ig4jEp8FHr931a09ISC9bB7PBUF55b3sihLn6RklKC6mF696yA0zAcJN9KtWmlfmCgyhIR4Y/pbO3HvXi4USgFcNpSiatDQH9//MAhRrR2zKi8xIQMrV5zGjfh0aDQKvPFWNN6fsQd5eVKx1yWKDHXq+uHr7/o7JDZCSPlpQqrDrW5N5FxJNv9bljEE9LH9glBSdgrWHQLqQsY1mBtFVYvjqBYqcRpKUF2MIDD8suIR9O+zHHm5+mLJnCAycJmDc0ChECDL3Fisv05dvyK7U+l191doXrqYiv69l+Pv7SPRKsp+SapWK+Gt17dj8aJYgAFC/qitXi+jdog3Gjb0x66d14yvy9tbjWfGtcBrb0bbZEEWIcRxaj7RHVc+XmG6AWMQ3FQI6EcJqithTISHcgkydU+CIwFF56MaLv0r2SNQCy85KULXxGUGbtXistL1SUpGCaoLatkqCLtiRuO96buwbesV4+AEY0CfvnXxwUddcfXKPfz150VkZmhRM9gTffvXxaNDfjXZpyEhlPDKS39j7/5n7BI35xwTxv2J39edN86hlQv94EtKzMC9u7nYsv1pMIFBoRDQsJE/3Nys38WGEOI6/Do3Q61n+iJh8RZAFIDC2ygLDIJahciPninVdADiGAKrBS/lX/kLrn6BjHgAIkTWHmpxDBSsR5Xampa4HkpQXVSjxtXx2+/DEXc9DadPGQpgP9Q80LiNaMNG1dF/4P09cj+f/a/FrUslieNE7E0cO5pkl1HUfXvjsO63c2bPn5Ojw5dfHMDKXx+z+fkJIeWjTbmH7MuJAAD3esFQVfe1+JygEd3g2TQcKRv+xb1/z4DrJSi83RHQrw2qD25vVR/EOQovuOJcBsAoKTXDnludkuIoQXVxoWE+CA3zsdjuwL83rFr5LwjAwQMJNklQL11KxcnYmwAMq/9/WHAMCgUzW/NUkjg2/XURiQkZCK5FoyqEuIKc6zdxY9FmpB++gMKXbLzb1Eft5wbALbSG2ed7NgmHZ5NwcM4BmYOJlaPENucSOAzTphj8wVjleF0lqcyvjVRMlKBWEpJkYfjUiJWibclOnriJaW/uwN6YosWA1WrRqoL8nAOnTqVQgkqIC8i+lIjzbyyAnKcrutiJc6QfuYBzp66iwZzn4V432GJfjDFArPgjQpynI09eAq20DByGXbAYakAljoJaGA3G6GdXVSTbocyUrfurTOgjUyXRtFkNiFb8YpBljqbNzI+GmHP4UCJ6dfsF//4TX+yxvDxLNfUIIa6EyzKufLzckJyWdAVG5pDzdLjy8QpwuXwfbCsKmd9Cpm4o8qRvjMkpAHCkIE/6Epm6xyDzO06MkJCqgRLUSmLMsy0slqViDAgL90GXrmFlOockyRgzcj202uLVBUpDEBialSNJJoTYRkbsZeQlpZacnBaQOfIS7yAj9orjAnOibP2k/AVDJSXkMmRcRbb+VUeHRVxAQR1UW99IyShBrSQiI6thwsRWMDW/veD47M97QRDKdklh29YruHEjA+UZSBFFhgGD6tHlfUJcQNqRC4bV95aIAtKOWN4NrqKT5NOQ+BGY32FJgsT3QeIXHRVWmXGuB+fp4JyubpGKhxLUSmT2nF6Y+GIUGDMkgoLAjJf93dyU+GnpEAwYFGmhF9NWLDtVrvhEkcHdXYn3P+xWrn4IIbbBtTq7tK2otPJfMNQBtUSETvrL3uGUmV4+iizdJKTrGiFd1wLpusbI1r0OST7j7NAqtIJV/La+kZLRIikb4Zzj0MFErF97Fnfv5iIgwB3Dn2iM5i2CHBaDKAqYPac3Jk1ui5+XnsCFc3egUIro2CkEw59oDC8vdbn6P34s2eq2jBkWTIgiA+eGQv0Rdfzwy4qhiKzvX644CCG2oarhZ901Rs6hCvSzf0BOxpEGWFWInYHjnp2jKZs86WfkSu/DMP5UMHKqg45vgE7/O9zEL6ESBzsxwoqLFkk5FiWoNnAjPh0jn1yH40eToVAI4JyDMYZvvz6ETp1D8PPyRxBQ3d1h8YSG+eDdGV1s2mdenh5x19Osbj/1jWj4eKtxPS4N7m5K9OlXB126hlGNPUJcSLWeLZGwZItVbf17tLRzNM4nwA9Fd1UyhYOxavYOp9T08n7kSrPy7z14Wd9wP0d6FSKrB1Fo5MjQCCk1SlDL6c6dHPTttQyJiRkADCOFBoYfcvv338CAviuwM2Y0PD1VToqy/DIztKWazP3Y443KVS2AEGJ/Kn9vVB/YDrf+OmA6L2NA9YHtoPT3dmhszqAUBiNP/t6KlhKUguuNQuZJC1GwValpDHnSErgLsx0UVeVhj0VNtEjKNJqDWk5zvz2MxIQMSCbqf0p6jvPnbmPJT7GODczGvLzVUCis/3aJqONrddt793KxY/tVbN50CRcvppYhOkJIWYU8PwjVurUw3Cm8YCr/79W6tUDI84McH5gTiEIjiCwa5uehilCw7hBZHUeFZRXO06HnMTCfnAKABB3fkL9zFCGui0ZQy0Gvl7Hoh2NWlVxaMP8oJk1uU2EvcatUIgYPqY8/Npw3mYwDhrmn/QfWg4eH5dHiO7ezMWvGHqxccRraQjVUozvUxsz3u6JDpxCbxE4IMY0pRIS/ORzVB7VDyp8HkHXOsAGHR8NQ1BjcHh6Ni0/N4ZKEtEPnkXn6Grhegia0Bqp1aw7RQ+OMl2BT7opvkaV7EjIuoeiwsuFrILD6cFd84ZTYzJFxF9ZNTwAALYAcAB72C6gSoq1OHYsS1HJITsrE3dRci+04B65fS0NOjh6SJCM+Lh1KpYCIOn6lGpV0tpdebovf152z2O7lV9pZbHMrJQs9u/2C+Li0Ygn+wQMJGNhvBVasfhT9B5a96gAhxDqMMeN2pZakH7uEa3N+hS41AxAFMMbA9RLiF25ErdG9UePRThX2gzgACKwaPJXroJVXIk9aCo4EAABDbajF0VAJT4Ixx60psBaD5S2x71MCcLNXKITYBCWo5VDan8FTJv+Ndb+dg1ZrGC2sUcMD4ye2wuRX2sLdXWmHCG2rTdtgfDuvPya/uBmiKBSabwsoFAySxPG/r/pYNfI5dcrWEpNTwLDbFWPA2FEbcP7KS/D1rfijMoRUBhknruDie4vvF/aXZOOYHc/T4cYPmyDr9Kj5RHenxWgLjHlALT4HlTAOQGb+UU+XTrwF5guRRUPih2D+Mr8IJRsAxirO4IiroFX8jkXfoeUQVNMT1a1YnW8ouQSs+fWMMTkFgJSULHz60T70770cGRl59gzVZkaPbY5tu0Zh8JD6xhqrgsAwYFB9bNn+NJ6b0MpiH4kJGfhzwwWzUyM4B3Jz9Vi5/LTNYieElB3nHNe+WQdIstmVHYlLt0F72/qKH66MMQbGvPJvrp9IqMXxsDwHVYZKHOuAaAgpHxpBLaPU1By89fp23L6dbbEt54YEtaS5m7LMcfLETbwxdRu+/6FiLERo264W2rarhbw8PdLT8uDlrYZGY/230q6dVyGb21oxH+fA5k2X8MKk1uUJlxBiAxmnr0KbYMUe9Ay4/fdhBD/dy/5BkSKUQjeoxdeQJ/0PxVfziwBkuIkfQyE0d06AFRzngK3XltEqftNoBLUM7t3LRd+ey/Dbr2csfnMVXEUx106SOH5ddQa3UrJsF6QDqNUKVK/hUarkFACys/VWT4/IytSWITJCiK2lrN1nXUOZI+v8DfsGQ0zSiJPgrlgMkbUvdJRBwbrDQ7EKKvEJp8VW0dFOUo5FI6hl8OlH+3DpYqpVq/cDAz1xMznTYiKr18vY8vdlPD36IRtF6bpCQr2t+tQoiqxU5aoIIfbBJQkZJy47OwxiJaXQFUqhKzhPB0cGGHzAmKezwyKkVChBLaWsLC2WLjlhMTllAjBocH2k3slBclKm2baAYR7nvXuWKwJUBj17RaB6dXfcumV+eoQkcYweS5eiCHEEKVeL1O3HkPLXAeTF3wIEAZ7NwlHj4Q5gKgXkHOuvZrjXC7ZjpMRajHmDofJvsOAoMmeQrdoKt3R9kpJRglpKJ47fRHaWzmI7LgOHDiSgc9cwiCKzmNDKMkdQUNX4hKtUinj7nU54bcpWk21EkaF1m2B07hLqwMgIqZp0qRm48PaPyI1LMZT75AAkGRmxl5Fx7BI8GpXu32H1AW3tEichpOqgOailpNVZWiFZtO2IJ5tYNRXA3UOJ/gPrlSc0q3DOcfhQItasPoO//riA1NQcu5+zJM9NaIm3pncEYChRVaCgMkDzFoFY9dvjFWLlLCEVGeccl2YuRe6N2/kHCj2Yv5gx62yc1f0p/b2hqu5ruwAJcRX8/nantrpZvbdCFUQjqKVUp46fVe0EgaFeZDX06m3d5eynRjazavel8tiw/hw+mBWDixfubyeqUokY/kRjfPRpD1Sr5rjCzYwxvPNeZzw8pD5+XHgcO3dchVYroUEDf4wb3xIDBkVCqTS33SAhxBYyT15B9sUEm/VX47FONuuLEFJ1UYJaSqFhPujeIxwxe66bHRmVZY7nJrTCtWtpFktRMQbEx5e/buDJEzexYtkpJCVmwtNLhYGDItG3f12IooAfFx7D1Fe2Fls9r9VKWLHsNA7sv4Htu0c7NEkFgGYPBeLr7/o59JyEkPvubD8OiIKhvml5MAZBo0RAbyoLRyonmcMOc1Bt2l2lQglqGbwzozP29ooDY7zE1eiiyNCgoT8efawhPpgZA0EwPweVc2Dr35cRdz0NoWGl2a7OIC0tF2NHbcCObVehUAiQZQ5BYPhl6UmEhHjjf1/3Mc73LCleWea4dPEu3nxtG35c/HCpz08Iqbh0d9KtS04FBlVQNWiT7hS/LCkIYKKAujNHQ+FFW2gSQsqP5qCWQdt2tbDqt8fg5qY07hIF3J8/2bRZDfyx8Umo1QqLI60FODfsQV9aWq2Ex4b8it07rwEwlKuSZW7chjQxMQNPP7Heqrqja1ZXvFqshJDyET01gGDFDwjOETi0I2pPGAhVYKGpTqKAal0fQqNvJ8G7RV37BUqIk9l6/qlxHiopEY2gllGfvnVx7vIkrFx+Ghv/vIDMTB3Cwrzx9Jjm6NkrAkL+D3y9zvrLZvoyXGL7fd05HDqYaPJxSeKQJOsWdnEOfPfNIbz/UcXeR5sQYj3fDk1wN+aUFS0ZfDs0hirABzWGdID25j3IWh1UAT4QPTR2j5MQZ+Ocgdv4Ej8V6jeNEtRy8PXV4IVJrc1uxdmkWQ2cP3/HOKJpTsOGAaWOYeGCYxAEZtXWodbYuuUKJaiEVCG+HZtA4ecJfVqW6QlxAoNvxyZQBRimIDFBgLpmNQdGaTtcknDvwDlkXzJcsfKoXxs+bRuAibQokxBXQgmqnY17rgV+XfWf2TaCYJgW0LJVUKn7P3Xips2SUwC4Y2FBFyGkchGUCtR7fwwuvPUjZK2u+HxUgUFTuzrCXn7UOQHa0N19pxH33e/Q38sCEwXDVFpJhrKaF0InD4VvdGNI/BJ00u+QkQIGLyiFvhBZGyp5R/IXSdm+T1IySlDtrH2H2hgwqB7+3nS5xETS8DOP4cNPepSpf10pphBYw9PLvqWuyuP2rWws/ikWSxbFIikpExqNAgMG1sPzL7ZGm7a0cw0hZeVRvzYafTsJSat24e7uE+D5V3xETzdUH9QOQcO6VvjL+KkxJ3H1k5XG+7xQIq67m4Grc35CxPx4MN/DAApGUxm08mIIaAgP5fcQGG0cQoijUIJqZ4wxLP55CJ5/7i/8vu48FAoBer0MxgxzPt3dlfjhp8Ho3iO81H3fSsmyauqAtQTBMLfWFZ08cRODB6xE2r08Y6KfmanFurVn8evqM5j5QVe89ka0k6MkpOLS1K6OiNeHI2TiYGiT74KJAtS1AyAoK/6vCVmrQ9zX6003ECXUnLkH8CqoEV103r6Mi8jUDYOn8k8IrIb9AiUujXPb19WnRVKmVfyfPBWAm5sSPy9/BKdPpWDp4hO4cuUu3DQKdOsRjhFPNoGXl7pM/V65cs+mcXIOjJvQyqZ92sK9e7kYMmgV0tPyio1C6/WG++/P2IPwcF88NqyRM0IkpNJQeLpBUa9ylYq6G3MKUlauyce9ul6HpsEdM9VOJHCkIk+aDzfFzDLHwbkEPd+BPGkZZP4fAAEiawO1+DREFk3TCAgppMIkqB9//DE2btyI2NhYqFQq3Lt3z9khlVrTZjXw+Re9LbbLzdXjj9/P4+yZ2xAVDNEdQtC9R7ixMkABpdL6KmHuHgrUrOmFq1fuQjYx6PrJ7J6IjCzbwofMTC1WLDuFRQuP4/KVu1AqBHTrEY7nX4hC125h5frBu/yXU0i9k2P2kyZjwOez/8GjjzekH/KEkCKyzsWZ3YzAZ9BFw+RCs+ukJGjlX6Hhb4Kx0ifwnGchSz8BEt+ffyLDKK2eb4Ne/zeU7BG4KWaDMcf8WpZ5InTyTgBZYAiEUugNxjwccu6KSubMDoX66feVKRUmQdVqtRg2bBiio6OxaNEiZ4djN0t+isV703chLS0PSqUAzgG9/l+Ehvng+x8GolPn+3OgGjepDm9vNdLT88z2KYoMPXpG4Nt5AzD9rR347dczReauhkf44t0ZnTH8iSZlivlGfDoG9luBa1fvATCMxGrzJGzZfAkb/7yI5ya0xP++6lPmxPGXpScttuEcOPPfbfx3+haaNqNLcISQ+7jZlSgc6vA0MKsW8edA5nEQWYNSx5CtnwqJH8y/V3gKgeHvOv47mBQAN8W0UvddGjK/ixz9dOj51vwjAgAJOZIb1MI4qMVXwKz7YhBiVxUmQX3//fcBAEuWLHFuIHa0YP5RvDF1m/F+4STyRnw6Hh6wCn9ufgIdOxmSVI1GgWfGtcB33xwyuxmAJHFMmBgFf383LPhxED75vx7YGxOHnFw9wkJ90L5D7WKjs9aSJBmPDlmNuOtpxUY4Cy6//7jwOEJDfTDltfZlOkdycqbV83SSkjIpQSWEFOFep6b53bLsPA9Qki9Az7dZaMWhlZdAw18EY6XfUdAanKcjSzccMq7h/osuSJZzkCd/B5knwU3xGV2JKgHNQXWsSr2TVF5eHtLT04vcXNWd29mY/tYOk4/LMocsc0x+8W/wQt/Rr78Vjcj6/sZdrEoy9tnm6NotzHjfP8AdQx9tiCefaooOnULKnJwCwJbNl3Hu7B2Lu2V9+b8DyMvTl+kcXqWoLODtXbb5vISQyqta9xZgKlPjMQx5l/3ArdrPxBMCC7Pc7AFaeS0szB/Ip4dW/qvU/VsrV5qXn5yafrE6vhZ6vtduMVRktJOUY1XqBPXTTz+Fj4+P8RYSEuLskEz6ZelJi0meLHNcupiKf/bFG4/5+GiwZcfTGPpoQ2OSWpBwenur8e7Mzvjq2352+zS8Ytkps8lxgbt3c7Fj29UynePRxxpZdY4aNTwQ1bpmmc5BCKm8RA8Naj3bz+Tj9zZGWnGJX4RKGA7GSl9uiyMJ1o29CeA8qdT9WxUDz4NWXglzyamBCK30s11iIKQ0nJqgzpo1C4wxs7cjR46Uuf9p06YhLS3NeIuPj7f8JCc5cjixyMioKaLIcPiBrU39/DRY/PMQnL04Cd/N74+P/68Hli4biovXXsKbb3cs1wipJTduZFhMrAskJWWW6RzPjm9hMcFmDHjhpdZQKCr1Zy5CSBkFDu2I2hMGgilEgAEQmOHGgKwDEZDvNILpX4kiGAKhFl8o49ndAKsW10jQyQfBrRvOLRWZXwSQYVUMeuNcWVKYzJldbqRkTp2D+tJLL+GJJ54w2yY8PLzM/avVaqjVFeOSr9W7QTFANpHIBtX0xOixzW0YlWXePmpjTVdLPD3LtglAWJgvfvhpMMaN/QOMoVhCzBjQf0A9vPJquzL1TwipGgIf7QT/3q1wZ9sx41an7vVrw79XK4geHDn66dDxP5GfwcIw6ilBZC3hrvgGAvMv03mVQg/o5DVWtZVxFDnSe3BXfFKmc5nCUZopVrZPkAkpLacmqAEBAQgIKP3+85VRk2Y1sHnTJYujkZKeo0nT6g6KyrKHh9TH7p3XLLZTKgX06lOnzOd5bFgj1Krlhc9n/4vt264YE+LQMB+8MKk1nn8hikZPCSEWKbzcEfhopxIfc1d+BZm/Aa28AZzfvr/VqdC4SDvO86DnOyHz6wBUULBOEIX6ps/JeoIhCBwpsGazTJ28CpL8FEShaWlemlmGubP3y1uZxiAw19ywxdk47LBIysb9VSYVZhV/XFwcUlNTERcXB0mSEBsbCwCoV68ePD09nRucDYwZ2xyfffqP2TaMGUZJe5cj0bO1EU82wcz3diMrU2dyFFgUGZ54qin8/ctX/Lt9h9pYu2E4biZnIjExE+7uCkTW97frFAZCSNUisFrQiC+W+BjnHFp5GfKkL8CRBkPCxwHIEFkbuClmQ2ThxZ7HmALuiu+RpX8CgOkNA+4TkSctg7vwf2V/IQ8QmB9E9IOEjRZacqiFp212XkLKqsIkqDNmzMDSpUuN91u2bAkA2LVrF7p16+akqGyndog3pr4ejf99vr/ExwumYH7+v94QRfuNFHLOcf7cHaTdy0X1QA/UqeNntr2Xlxqr1jyGRx/+FXq9XGwEWBAYmjargVemtMUXn+9H/I10eLgr0bd/XXTqHFqmxVuBQZ4IDKr4H0oIIRVLnjwPedL/Ch25Pxop8WPI0j0KT+XvEFhosecqhIegFl9FnvSpFWeSIPHYcsf7IFGIMFttqwBDsM3PXRnI3Jrx79L3SUpWYa6JLlmyBJzzYrfKkJwWeG9WF7zxdgeIIoMgMIgiM65ed3dXYtGSh/Hw0NIXiLYG5xxLfopFVPMf0LbVj+jdYxlaNFmAbp2W4M8N580+t3OXMOyMGY1BD9cvstq+WjU3TJnaDk2aVkfbqEX4YFYMfl58AvO+O4KBfVeibasfce7sbbu8HkIIsSWJX30gOS3WAhwZyNF/aLKFgCDbB2Ylzjn0csH8WnNEaOVVjgiJlNG8efMQEREBjUaDqKgo7N1ruizY7t27S1yAfu7cuSLt1q5di8aNG0OtVqNx48ZYv369vV+GRRVmBLUqEASG92Z2wYTnW2HZL6dw5r9bUCgERHeojWEjGsPDo2yLjCzhnGPK5C1YvCi22F7UscdvYuQT6/H+h93w6uumC+03eygQv6x4BLdvZePatXtQq0XUb+CPZ8f8gY1/XjRe/i88DeDSxVT06bEMu/8ZY3GklhDiOrgsI/3YJdz66wCyLyYAjMGzSRhqDI6GR5PybW3sqrTSCliewynlz01NgMBqFXtUFJpYuf5IhMhalClOU2TEQcZ1K1oaXgMpjoOB23ir09L2t3r1akyZMgXz5s1Dx44dsWDBAvTv3x9nzpxBaGjxkfsC58+fh7e3t/F+9er317Ls378fI0aMwIcffohHHnkE69evx/Dhw7Fv3z60a+e8xceMW1PbqJJIT0+Hj48P0tLSirxRVd3KFafx/DjLxaG3bB+J6I7W15Ldvu0KHn34V7NtBAF45LFGWPzzEKv7JYQ4j5ynw+WPlyP90HnDP2A5/6Jn/l73/n2iEPbKo2B2nIrkDBm6wZD5f1a1dRO/hkocXOJjmbqnIPFDsHSx2FPxh00XSUnyOWTqB1jd3lt5CYy5znvozN/fBed+S/gJauZu077zeDZmy89a/bratWuHVq1aYf78+cZjjRo1wtChQ/Hpp8Wnj+zevRvdu3fH3bt34evrW2KfI0aMQHp6OjZv3mw81q9fP/j5+WHlypWlf1E24jrffcRp5n5zyOJCI4VCwPx5patJ++PCYxAsfIfJMrB+7VncSskqVd+EEOe4/tVapB++YLgjF0qy8ic33tl2FAmLtzghsvs4z4JWWoks3YvI0j2LHP37kOSz5exUV4rGpodJ3cR3AShh+tcvg5KNsGlyCgCMBZo554MR1HCp5LQqeHDXy7y8vGJttFotjh49ij59+hQ53qdPH/z7779m+2/ZsiVq1qyJnj17YteuXUUe279/f7E++/bta7FPe6PvwCouMSEDJ0+kWKzDqtfL+OuPi1ZtJlDg0IGEIr+/TJFl4L//blndLyHEOXITbiN11wnzhY85kPL7P9BnZDsusEJ08g6k69ojR3oHer4Fer4bWnkZMvUDkaV7AZznlKlfkTWCdduVAiKrZ/oxoTE8FKvAULDrnSL/JsCwW9WzcFN8VKYYzRGYHxSsFyy/BgEqwXx98qqK2+kGACEhIUV2vixpNPT27duQJAmBgYFFjgcGBiI5ObnEmGvWrImFCxdi7dq1WLduHRo0aICePXsiJibG2CY5OblUfToKzUGt4NLScrFy+Wns3HENuTk61I2shtFjmqNlq5In40uSDFnmUCoNP6QyM7VWn0uvl6HTyVCprPshnZtrfWHo0rQlhDjHnW1Hi17WN4FLElJ3nUCNh6MdFJmBXj6AbP3zuP9rv+BPw4imnm9Dtv4luCt+LPU8WZX4JHT6DRZaMQisscXRT4XQHF7KPdDzPdDL+wDkQWChUAqPQGD2q3OtFl+AXr8DhoVSJX3IEMDgBZU40m4xkJLFx8cXucRvbpOhB793Oecmv58bNGiABg3uL66Ojo5GfHw85syZgy5dupSpT0ehBNXF6PUyDh1IwN27OQgIcEfrtsEmy0r98ft5jH/2T2Nyxzmwb28cFi08joGDIvHjksHw8FBBkmSsX3sOC+YfxaGDCeAcCAn1xvgJrTD0sYYQBGbVTlY+vmqrk1MAUChEANZdFrubWrZRDUKI42hv3oM1pcWZKECbcs/e4RSTKxXUDTUVoww93wWJH4SCmV70WRKRtYGC9cpfQFRSgs4AMLiJb1vVH2MClKw7lEL3UsVRHgqhOdwVc5GtnwxD0l7wOlj+/33goVhq1yS5IrNnmSlvb2+Lc1ADAgIgimKxkc2UlJRiI6DmtG/fHsuWLTPeDwoKKnef9kCX+O1AkmRs3ngR097cgdembMX8uUeQaiEBk2WOr784iIZ156Jf7+V4cvg69O6xDE0azMeC+UeLXVrfueMqRo/8Hbm5enB+/4qbXm/4y+ZNlzBm5O/QavUY9dR6PDvmDxw5nGhsFx+XjpkzdmNw/5Xo2i2sSHmokogiw+gxpdtG1cNTaX3jSrjql5DKRtCorPq3ymVAUJfi378NSPJZSPwkLKcQIvKk5aXunzEGd8U3ULC+xn7yH8n/0w3uivlQCB1L3bcjKVgPeChWQsWeBkMYGPwhsIbQiO/CS7nL5nNfie2oVCpERUVh27ZtRY5v27YNHTp0sLqf48ePo2bNmsb70dHRxfrcunVrqfq0BxpBtbF/9sVh3Jg/kJiYCYVCAGOGUdH3pu/Ca29G4+3pHYsNm8syx4Rxf2LN6jPFpnYlJmTgjanbcP7cbfzvqz5gjIFzjnen7QLATU4Fk2WOrVuu4PnnNmLjnxcBFN/DnsvAjfh0w9/NDIoIAoNarcD4ia1K9bWoF1kNCTcyrGobGOhRqr4JIY7n07YBbm8+ZLmhLMOnrX1qNpsi8YvWtoTMy7ZgijENPJRzIclnoZV/hcyvAdBAIXSEShgKxlx3AxHO05En/QStvAwcqflHvaASnoRafA4Co23HLXGFrU6nTp2KUaNGoXXr1oiOjsbChQsRFxeHiRMnAgCmTZuGhIQE/PzzzwCAr776CuHh4WjSpAm0Wi2WLVuGtWvXYu3atcY+X3nlFXTp0gWzZ8/GkCFDsGHDBmzfvh379u2z1cssE0pQbejggQQMGbgaer3hE3zBnwCg1Ur49KN9yMnW4YOPi17SWbniNH5ddcZs3z8uPI6evSIwcHB9xB6/idOnUizGI4oM69eeM5t8ShLH9WtpmPJae3z79UGAF01kBZFBo1FgzbrHER7ua/GchT31dDPs2WW57l716u7o0jWsVH0TQhzPp20DKP29obubYXoLHEGAe50geDSwviSdLTBWml9n5RvdFYVGcBNmlqsPR5L5HWTpnoCMqyg6wpwBrbwIOnkDPJVrILDazgqRWGnEiBG4c+cOPvjgAyQlJaFp06bYtGkTwsIMv0OTkpIQFxdnbK/VavH6668jISEBbm5uaNKkCTZu3IgBA+6XHOvQoQNWrVqFd999F++99x7q1q2L1atXO7UGKkB1UG2qc/RinDppeUX88dPPo27d+4XpO7X/CadP3TL7PFFk6NgpBH/9/RRWrTyNCc9arltqLVFkeGxYY7w1vSN+XHAMv605g/S0PAQEuGPk6GZ4dlxLBNfyKnW/ubl6RD20EImJGcVGbwv7ZHYPvPRy2/K8BEKIg2Sdj8eFN3+ArJOKL5YSBIgeGjT8ciI0tR07j1HmScjQdYY1l/hVwii4KWY4IiyXkKUbCz3/B6bLX4kQEAlP5UanL4wxxRXqoL4K+9RB/RLW10GtSmgOqo0cP5aME7E3LSanosiw+Mfjxvu3b2VbVeZJkjhi9sRBq5WgsHEBbEniuJmcicjIapg9pxcuX38Zt+69gbOXJuHdGV3KlJwCgEajwO9/jUD16h7F6qyKCsP98c+3wqTJbcr9GgghjuHRIAQNv34RPm3qF52PKgjw69QEjb6d5PDkFAAEVhMK1hOWyyhJVWqVusSvQM9jYGkHLBnnIPHDjgqrQrJnmSlSHF3it5Hjx5KsaidJHEcOJxrv5+SUpvizoX376NpgzPy8UQBWtQEMSXO1am6lisNakfX9sf/IOCz9KRY//nAcN+LToVQK6N4jHM+/2Bq9eke47Cd2QkjJ3MKDUO/9MdDeuoecq8mAwOBeNxhKv7J9mLVZXIp3kak7Ao50mErI1MJkiKyuYwNzIp28GZa3aAUABXTyJigEuppFXAMlqE5QOGcMqO4OlVqENs/yBs1eXip4eanh46NB/4H1sGXzZbOXzjk3JJ/m2gCGpHnoow2tDb/U/P3dMPWNaEx9IxqyzMFY8ZprhBDn0qVm4Pbfh3Hv4FnIuTqog/1RvV8beLeub3LbUlV1X6iq+zo2UDMEFgIP5Trk6N/K305UgGGVvQTAGxrxFaiEsU6N0dE4T4fh62Dpd4wMjjQHRFRxybBDmSkb91eZUIJqIy1allwY/0GiyBAVdb+8g5ubEsNHNMaqFaeNJaJMPW/ssy2Ml8o/m9Mbhw4m4m5qjskEdNYHXXHhwh2sXvmfyTaiyBAY6IFBD0daFX95WdpSlRDieKm7YnHtf7+BS7LxsktufArS9p+Be2Qt1PtwLJS+rrtCvTCRhcFTuQqSfAF6vg8ceRAQCqXQC4yZLn5eWQnMH5aTUwBgYKCV/MR10BxUG2kVVRPNHqphMQGTJI5nx7cscuyVV9tBoRBNPlcUGdzdlXj+hSjjsdAwH+yMGY2OnQwrZRmDsZapf4Abvvq2L6a+EY3Pv+iN5i0CS+xbVDB4eanw2+/DjTtLEUKqlrQjF3D1s9XgeqnonKD8efHZl5Nw8Z3FhscrEFGoD7X4LDTiC1CJA6tkcgoASmEgrJvpKEElDLF3OBUazUF1LBpBtaH/fdkHA/utAACTi54mv9IW9epVK3KsQcMArFn/OJ54fC1ycvTG5xZcBff0VGHthuEIDfMp8rzwcF/89fdTuHjhDnbvuo68XD0i6viiT7+6xoTTy0uNTVtH4vu5R7Dg+6NISswEALi5KTBy9EN45dW2CAvztdWXgBBSwSQu2QLTW18CkGXkXE7EvQNn4deJirhXNAKrBSUbBB3fCNMXlEWILIqK9BOXQmWmbCxmz3WMG/MHbt7MglJpGKDWSzIUooBXX2+P6e92NjlSevtWNn5ZehKrV/2H1NQcVK/ujqeeboannm4GPz9NuWOTJBnx8enQ62UEB3vB3d12O72cPXML167eg1qjQJu2wfDyqpqjFYRUJNlXknD2xW8sNxQYvFrURf1Pxtk/KGJznGchS/8MJH4ERT+MGH4XCYiEh3J5/nQA1+QKZaYm2anM1FwqM1UiGkG1sS5dw3D20iRs3ngRe2PioNPJqFvPD08+1RT+Aea/sQOqu+PV19vj1ddLt0e0tURRKHWxfUu2bb2Cj96PwfFj9/fxdXNT4OnRD2HG+13g41P+xJoQYh95SamWGwGAzJF347Z9gyF2w5gHPBTLoJPXI09aChnnAAACQqESx0AlDAezceJFSHlRgmoHCoWAwUMaYPAQx271Zy+SJOOvPy7ghwXHjIloq6iaaNg4AAvmHS02IpyTo8dPPx7Hvr1x2LrzaUpSCXFRQinmnjMl/bqoyBhTQSWOgEocAc71AGQwpnJ2WBUKh3WlG0vbJykZ/cQhZmVn6/DU8LXYueNakZJV+/bGYc9uwzamJc23lSSOC+fv4L3pu/DN3P4OjZkQYh2PxmFgShFcZ2EBlCDAp23l+MBNSrstLClAZaYci1bxO1hyUiZmf/oPhg5ahcH9V+LtN7bj/DnXvXQ2+cXN2L3LkIgWLlVlqbZqQZsVy0/j3r1cu8VHCCk7hacbqvVsBVgq/ybLqD7QuftyE0KqFvoY5UDzvjuMd97eCc7vjzru2xuHed8dwdhnm+OLr/tCoXCdzwzXrt3Db7+eKdclDW2ehH0xcRj0cH3bBUYIsZna4/oh8+QV5CXfBeSSx3Nqjx/glO1LCXEl9igLRZf4TaME1UGWLj6Bt9/YUex4wUjk0sUnoFAI+OLrvjY/99Wr93DiuGHuaPOWQYiI8LXqeatX/gdBsLwTlSVZWdpyPZ8QYj8KL3c0/OoFxC/YiNTdJwDpfpKqCvRD8Oje8O/Z0kwPhBBie5SgOoBWK2HGu7vMtuEcWPTDcUye0s7qBNKSM//dwvS3dmDnjmtFjnfvEY5PZvdAk6Y1zD4/KTEjf0vS8iWoifm1Vwkhrknh7YGIN4aj9vgByDh5BTxPB1WgHzybhoMJrnNVhxBn4rD9nFEaQTWNfvI4wKa/LuJuquV5mILA8PPiEzY55/FjyejR5WfjQqbCYvZcR8+uv+DY0SSzfXh42GaF58EDN2zSDyHEvpS+nqjW5SH4946C10N1KDklhDgN/fRxgPPn71g1t1SWDSvfy0uWOcY8/Tvy8vQlXp6XJI68PD1Gj/zd5I5XADBwUCT0+vJ/Xjx8MBHNm3yPuqHfoHP0Yvyw4BgyMvLK3S8hhBDiKLKdbqRklKA6gFIhwJoNuxhjxt2nymPXzmu4dvWe2bmjksQRdz0NO3dcNdkmumNtNG4SAFG0sMLXglu3snH1yj3cupWNkydu4vVXtyLqoR9cunoBIYQQQpyHElQH6Ng51KqFRpxzdOgUUu7z7dh2xaoRW4VCwPatV0w+zhjDLysfha+fBqKifElqAc4Nt1u3sjCo30oqQUUIIaRC4Ha6kZJRguoAbdsFo0nT6mZHIhkDNBoFnniqabnPl5sngVmRTzIG5OWZL9AdGVkNMf+MxVMjm0Glur/rjEotol49P5R1ipokcaSkZGHZzyfL1gEhhBDiQHSJ37EoQXUAxhjmLxwIlUosMUktSCbnfj8A3t7qcp8vItzH6kL6YWE+FtuFhPpg7vcDcOn6ZGzfPQrbd4/C5euTsWvfGDRuUqNcUwAWL4ot83MJIYQQUjlRguogLVoGYevOp9G8RSAAQ1JasId9aJgPVqx+FI8Pb2yTc414sqnVI6hPjrR+xNbXV4O27Wqhbbta8PHRwMdHgy07RmLS5DZlSqw5B27cSC/18wghhBBH43b6j5SM6qA6UPMWQdi9byxOxCbjwP4ESJKMxk2qo0vXMGOyags1Aj0w8cUozPvuiMldoBgDJkxshcAgz3Kdy8tLjY8+7YF3ZnTGyRMp0OkkZGfr8PjQNVY9381NWa7zE0IIIaTyoQTVCZq3CELzFkF2PceHn/RAeroWvyw9CYVCMJaLKvj7U083w8f/19Nm53NzU6Jd+1oAAL1eRo0aHkhJyTL7HIWCYeCgSJvFQAghhNiLPeaM0hxU0+gSfyWlUAj4bn5/7IwZjRFPNEZk/WqIrF8Nw0Y0xo49ozFvwQCrVvqX9dwTJ0VZnGag13NMmNjKLjEQQgghpOKiEdRKjDGG1m2C0bpNsMPP/fKUdti7Jw57dl8vthkAY4b5px990t3uI8mEEEKILdijLBTNQDWNRlCJXahUItasH4Y3p3VAtWpuRR5r2CgAS5cNxcuvtnNSdIQQQghxZTSCSuxGpRIx/d3OeP3NDjhyKBEZmVoEB3uiabMaYNaUGSCEECvlxt9CzvWbYKIAj/q1ofT3dnZIpJKhOaiORQlqFcc5x+FDidi96xry8iTUqeOLoY82hIeHymbnUKlEm+yQRQghD8o8G4eERZuRefra/YMCg2+HJqg9fgDUgX5Oi40QUnaUoFZhZ/67hfHP/IlTp1IgigyCwKDTyXjt1W14e1pHvDK1HY10EkJcVvqxS7g0YzH4A/PcIXPc+/cMMk9eQcOvXoQ62N85AZJKhYODM9vOGuWmakESmoNaVZ0/dxu9u/+CM2duATDsKqXTGS42ZGfpMOPd3fhwVowzQySEEJPkPB2ufLICXOLAgwkqAMgy9Jm5uDrHuprMhFhCW506FiWoVdSbr21HdrbO7Jaocz7bjwvn7zgwKkIIsc7dmJOQMnNgcjcSAJBlZJ25jpyryY4LjBBiE3SJvwq6cuUudu28ZrGdKDIs+uE4Zs/pZf+gCCGVivZ2Gm7/fRhZ5+IBAO71ghHQv63N5oSmHbkACKzk0dPCBIa0oxfgFkEl7Uj50CIpx6IEtQo6cijRqnaSxPHvP/F2joYQUplwzpG8ejcSl24DGIwJZPqxi0hetRtBw7si+Jm+5Z7fLmv1lpNTAGAMPE9XrnMRQhyPEtQKRq+X8femSzhz5hYUooDoDrXRvkPtUv2wl6z5oV7Q1swUAEIIeVDK+n+QuGSr4U7hHx/5P3eSf90DphQRPKp3uc6jDvIDRAGQLIxBSTJUQdXKdS5CDDg4lep3GEpQK5DVK//D9Ld24NatbCgUAjjnkCSOBg39Mff7AWjbrpZV/TRtWt2qdgqFgBYtAssUa8rNLPy89AS2b72CnBw9Iuv745lxzdGhYwhVBiCkkpKy85C4dKvFdkmrdqP64GgofT3LfK6APq2Rsv4fi+0EjQp+HZuU+TyEEOegRVIVxM9LTmD8s3/i1q1sAIaR1ILRzYsXUjGg7wocOphgVV/NHgpEy1ZBEATziaJeL+PZ8S1LHevyZafQsN5cfPT+Xvz7zw0cP5aMdb+dQf/eK/DwgFVIT88rdZ+EENd3d89JyNZcTpc57mw/Vq5zuUUEwbdjE8M8VDNqPtkdgsZ2dZ1J1UWr+B2LEtQK4O7dXLw2xfSohCxz6HUyJk3cZHVNtU9n94QgMAgmvgMEgeHx4Y0Q1bpmqWLd9NdFvDB+I/R6GXKhqQR6veHv+/bG4anha6n2GyGVUE58CpjCil8rAkNu3K1yny/ijeHwbhWZ32eh84qGvwc+1hmBw7uW+zyEEMejBLUCWP7LSWi1ktk2ssxx/twdHPj3hlV9dugUgjXrh8HbWwMAxkL9osjAGDByVFN8/8OgUl2O55xjxru7YO4pksQRsycOMXuuW90vIaRiYKJgturTg23LS9CoUO+DMYj8ZBx82zeCqmY1qGsFIKBPazSaOxm1xw+gKUXEZrid/iMlozmoFcDB/dZduhdFhgP7ExDd0bptRXv2isCFqy9h/bpz2LXjKrRaGXXq+OLpMQ+hTp3Sl4I5fCgRF86nWo5TwfDTj7Ho2i281OcghLgur6YRuLnGig0+JBmezcJtck4mCPBuVQ/ererZpD8AkGU9dHw5JPk8GHOHUngKCqGOzfonFROVmXIsSlArAL1etmpUgjEGSS7dt7tGo8CTTzXFk081LWN09126ZDk5BQBJz3H+3O1yn48Q4lq8W9eHsroPdLfTTRfQZ4Do6Qa/Ts0cG5yVsnUzoOMrAeRfteKAVv4JDKHwUCyGKEQ4NT5Cqgq6xF8BNG5aHaJo+TKVXi+jUaMAB0RUMrXK+s87ajV9NiKksmGigIjXhxsWLpV0aZ0xAAzhrw2DUIqfF46SpXseOr4MxuS0EI44ZOr7QpJpelJVxZl9bqRklKBWAGPGNi+y4MiUGjU80Le/7S5zlVaHjrUtVgYADFMRevaiUQhCKiOv5nVQf/Zz0ITkl7NjzLjSXl2zGup9OBa+7Rs5McKS6eS90PNtFlrpkaUf55B4CKnqXO8jLCkmNMwHkya3wdxvD5u91P/pZz2ReicHa349g4Qb6XD3UKL/gMhSr8Qvq5rBXhg8pD7++vMCJL3pQDkHnhnXwiExEUIcz6tpBBovmIKss3HIOh8PcMC9bjA8H4pw2UVLufrPrGrHcQWyHA9BsG6uP6k8DHNQbbuoieagmkYJagXx4SfdAQBzvz0MQWCQZQ7GGDjnUKlEfP5Fbxw8mIAJ4/4E54ZRSs45Pvv0X7RoGYTFvwxB3bq22QPbnNmf98KhAwlISckyuQvV7Dm9EBLqY/dYCCHOwxiDZ+MweDYOc3YoVpFxweq2WnkdNMIrdoyGEFIhLvFfu3YN48aNQ0REBNzc3FC3bl3MnDkTWq3W2aE5jCgK+GR2T5w6+wKmvhGNQYPr4+Eh9fHpZz1x4epL2LXzGn74/igkiUOWOXQ62Vh79OSJZPTq9jPi49LsHmdwLS/s2jsGffvXLTYFLSTUG4uWPIznX4iyexyEEFI61o9lcWTbMQ7iqqhQv2NViBHUc+fOQZZlLFiwAPXq1cPp06cxfvx4ZGVlYc6cOc4Oz6FCw3zw3swuRY7t3HEV69eeM/kcWQbu3M7BjHd3Y/HPQ+wdIoJreWHVmsdxIz4dMTHXoc2TEFHHF527hFk1R5UQQhzPC8A9q1qK7CG7RkIIARivoFv6fP7555g/fz6uXLli9XPS09Ph4+ODtLQ0eHt72zE6x3py2Fps3nQRlipMMQZcjnsZAQHujgmMEEJcCOfZkJEMBhUYgsHY/YuIOfpPoJV/tKIXDXxUZ+wXJCmRM39/F5x7IFsAJXOzad86noON/PlKl5fYQoW4xF+StLQ0VKtWzWybvLw8pKenF7lVRgf237CYnAKGxUm/rvrP/gERQogLkfhVZOveRrquFTJ1vZCh64IMXVfkST+C8zwAgFqYAkBjsS+1MNG+wRKX5SqX+OfNm4eIiAhoNBpERUVh7969JtuuW7cOvXv3RvXq1eHt7Y3o6Ghs2bKlSJslS5aAMVbslpubW4bobKdCJqiXL1/Gt99+i4kTzf+g+PTTT+Hj42O8hYRUzlWXOp313+KbN16yYySEEOJa9PIJZOoGQ8fXAri/boEjAbnSp8jSjwHnuRAEd3go/gBgeoRMyZ6CRvGy/YMmxITVq1djypQpeOedd3D8+HF07twZ/fv3R1xcXIntY2Ji0Lt3b2zatAlHjx5F9+7dMXjwYBw/frxIO29vbyQlJRW5aTSWP7DZk1MT1FmzZpWYtRe+HTlypMhzEhMT0a9fPwwbNgzPPfec2f6nTZuGtLQ04y0+Pt6eL8dpatf2srrtzeRMO0ZCCCGug/McZOufBZCLkorvAxwSP4Jc6f8AAAqhHrwUx6EWXgIQAEAFwA0ii4aH4i+4Kz9yWOzE9cjgdrmVxhdffIFx48bhueeeQ6NGjfDVV18hJCQE8+fPL7H9V199hTfffBNt2rRBZGQkPvnkE0RGRuLPP/8s0o4xhqCgoCI3Z3PqIqmXXnoJTzzxhNk24eHhxr8nJiaie/fuiI6OxsKFCy32r1aroVaryxumy+vVpw7OnLFu61B3D5WdoyGEEOvp07Jwe+sRZP53DVwvwy0sEAH920BTu3q5+9bJf4LjroVWMrTyamj4VDDmDUFQQSNMhQZTy31+Qqz14BTEkvIXrVaLo0eP4u233y5yvE+fPvj333+tOo8sy8jIyCg2RTIzMxNhYWGQJAktWrTAhx9+iJYtW5bhldiOUxPUgIAABARYtzVnQkICunfvjqioKCxevBiCUCFnJ9jF+Imt8M1Xhyy2EwSG7j3C7R8QIYRY4damQ4if9we4JKNgF5L0Y5dwc+1eBAxsh9AXB4OJYpn718obATDA4ihVHnRyDFTioDKfi1R+9tialOf/78EpiDNnzsSsWbOKHLt9+zYkSUJgYGCR44GBgUhOTrbqfP/73/+QlZWF4cOHG481bNgQS5YsQbNmzZCeno6vv/4aHTt2xIkTJxAZGVmWl2UTFaLMVGJiIrp164bQ0FDMmTMHt27dMj7mCsPQzhYW5ou+/eti69+Xze40xTmnHZwIIS7hzo7jiPtmffEH8ld83t50EExgCJ1U9tJ4HPdgOTktaGv/OtGEmBIfH19kFb+5q78P7sbGObdqh7aVK1di1qxZ2LBhA2rUqGE83r59e7Rv3954v2PHjmjVqhW+/fZbfPPNN6V5GTZVIRLUrVu34tKlS7h06RJq165d5LEKWiXL5r74qg+6dV6K1Ds5Jndw+mR2T4SG0Q5OhBDn4noJN37YaKERcOvPAwh8pBPUwf5lOo+AGpAhwJq10gKz7moeqbrKMmfUmj4BwyIlS2WmAgICIIpisdHSlJSUYqOqD1q9ejXGjRuHNWvWoFevXmbbCoKANm3a4OLFi1a8AvupENfJx44dC855iTdiEBLqg10xY9C9R7hxB6eCP4NqeuL7Hwdi0uQ2zguQEELypR0+D/29LMsNBYZbfx8u83lU4iOwrpCPFxSsa5nPQ4gjqFQqREVFYdu2bUWOb9u2DR06dDD5vJUrV2Ls2LFYsWIFBg4caPE8nHPExsaiZs2a5Y65PCrECCqxTmiYD9b9MQJXrtxFzO7ryMuTUKeuH3r0DIcoVojPIoSQKiDnegogCoBkIXmUOXKv3yzzeRSsNxhCwZGAklfxG6jFZ8GYc0vqkIqAg9t4BNXaKSgFpk6dilGjRqF169bGBeNxcXHGspvTpk1DQkICfv75ZwCG5HT06NH4+uuv0b59e+Poq5ubG3x8DFdU33//fbRv3x6RkZFIT0/HN998g9jYWMydO9eGr7P0KEGthOrU8UOdOn7ODoMQQkrEFALMTpg3NgSYouyLpBhTwkO5BFm6J8FxC0VHUw2X/pVsSH5ZKdM4z4Oe74bMk8DgDoXQFQIzf0mVVD5lLaxvqc/SGDFiBO7cuYMPPvgASUlJaNq0KTZt2oSwsDAAQFJSUpGaqAsWLIBer8ekSZMwadIk4/ExY8ZgyZIlAIB79+5hwoQJSE5Oho+PD1q2bImYmBi0bdu2vC+vXCrsVqdlUVm3OiWEkIok61wczk0puW5jEQyoPX4gAh/tVK7zyfwutPIKaKXl4EgGwCCytlCLY6BgfU0uMOGcQyv/iDxpXv4iqoL5rAIUrB/cFB9CYDQY4AiusNVpD2EeFDbe6lTPc7BTfpHykhLQCCohhBCHcm8QAreIIORcvwnIpsdImEKEf++ocp9PYH7QiJOgESeBcy0ABRizPO0pV/oYWvmnQkdk4596vgVZurPwVK4DY7T4tCqw5yIpUhxNTCSEEOJQjDGET30cTKkABNPlcUInPwKFl21HrBhTWZWc6uWjDySnD5IgIw650te2C44QYkQJKiGEEIdzj6yFhnOeh1tEfi1rxozJqtLfGxHTn0RAn/KPnpaVVvoFgKX5rxK08mpwbkVFAlLhcTvdSMkoQSWEEOIU7pG10OCzCQh8rDOU/t4Q3NRQBfmh+sPR8G5e16mx6fk/MLfy/74cSPyMvcMhpMqhOaiEEEKcIuvCDVx8ZzGkzGzjUJI2KxeJS7YieeUu1J01Gt4tnJOocuhL0bo0bUlFJTMOmdEcVEehEVRCCCEOp72VhovTFkHKygE4IHjnwiP6Bjy7XIe63m3IeVpcmrHEsJDKCURWB9b9imQQWJi9wyGkyqERVEIIIQ6X8se/kHLyIHrlwP/ZWHh1jgNT3B9Nyovzxp1lzXHzt70If+1xh8enEp5GjnTcQisRCtYJAgt2SEzEuWgVv2PRCCohhBCH4pzj9uZDEL1yUHvOdnh1KZqcAoCqdjqCp++Fjq2FlKt1eIxKYQAENITphVIMgACV8Ay00gZopdXQyXvBuTXzVklFRIukHItGUAkhhDiUnKuFlJmLwNePQRGQDSYW/zXN8jebqj7xEHRpVyFqGjg0RsbU8FD+gmz9c5D4CRgSVQmGxJQDcIOIFsiWxqHwYiqGGtCIU6ASn3BovIRUNpSgEkIIcShBqYDomwPPjjdKTE4LMAZwgUN2/wPAG44LMJ/A/OGhWAeJ74dW+g0yboDBAwrWCXnyckg4iAdX+nOkIEeaDhm3oBEnOzxmYj90id+xKEElhBDiUEwhwm+gYDY5NbYVAEn9rwOiMnF+xqBgHaAQOhiP5ehngCMe5spQ5UlfQsl6QRQaOSBKQiofmoNKCCHE4XzaRpSida7d4igtzjOglX+D5RqpIrTyMkeERBykYATV1jdSMkpQCSGEOJxHvXZWthQhsNIks/Yl8ZOwLmGWoJNj7B0OIZUWXeInhBDicAqhNZgUApnHgzFzLSWXWnDEUZqKAo6vPkDsR86/2bpPUjIaQSWEEOJwjAnQiG9YSE5FiKwlFKyTo8KyyPqi/AIEVseusRBSmVGCSgghxClU4iBoxFkwlG4qXG/U8HeRNYO7YhEYc51fVSKrA5G1huVfnzJUwkhHhEQchNvpP1IyusRPCCHEadTiaCiFHtBKy6HjewCuhcDqQCU+CQXrAsZMFcp3Ho34OrL0T+F+TdQHiRBYfSiFPg6OjNgTt8OiJkpQTaMElRBCiFMJrDY0iregwVtOOT/nEvQ8BlppjbHWqVLoDZXwGBjzKdZeIbSFu2IusvVTYJhnWpBkGIr5i6xx/sivynEvgpBKhhJUQgghVZbMbyFL/wxkfgb3d4sCJOkQcqU5cFd8C6XQs9jzlEJfeCn/hU7+DTp5OziyISAEKnF4/siv60xLILYhMw7GqFC/o1CCSgghpEriPA9ZulGQcTn/SOHaphxAHrL1E+GhWAWFEFXs+QLzg1ocD7U43hHhElKl0Ec8QgghVZJO3ggZF2C66D4HwJErfeW4oIjLku10IyWjBJUQQkiVpJWXw5rV+BL/BzK/4YiQCCH56BI/IYSQKknmV2HtGJbMr0Fgte0bEHFpMjiYjeeM0hxU02gElRBCSBVVmlX2tCKfEEeiEVRCCCGVEud50MmboZVXGrZUhRsUQi+oxZEQWCgUrDN0/HeYnoNawB0ia+qAiIkrs0dhfaqDaholqIQQQiodmSfmr9C/CsPFQsPFVK38E7TyIriJH0ElPg2dfq2FngSohOFgzN3+QROXRpf4HYsu8RNCCKlUDOWjnoaMuPwjheeZSgBk5EjTwXEbauFFMz2JEFAHGnGK3WIlhJSMRlAJIYRUKobyUdcstGLIlb6Ep+JPMFYDedJ34Lhd6HEFlGww3BQzwJi3HaMlFQWNoDoWJaiEEEIqFa28CgWX9U3jkPkZyPwc1OJoqISnoOf/gPMkAG5QCJ0gMH/HBEwIKYYSVEIIIZWKzONhdfkoJEBEIzCmgJJ1tW9gpEKjEVTHojmohBBCKhUGjV3aEkIchxJUQgghlYpC6AVAtKKlO0TWyt7hkErCsDUpt/GNmEIJKiGEkEpFJT4Fy5f4BaiEEVQ+ihAXRQkqIYSQSkVkEdCIH+TfYyW0ECCwxtCIUx0ZFqngOANkG994Sd+eBAAtkiKEEFIJGXaLqoFc/ReQcb7QI25QCU9AI04FYx5Oi49UPIYFTbRIylEoQSWEEFIpKYXeUCh7QeZnISMBgAYK1ooSU0IqAEpQCSGEVFqMMYisMUQ0dnYopIKjEVTHojmohBBCCCHEpdAIKiGEEEKIBRI4OI2gOgyNoBJCCCGEEJdCI6iEEEIIIRbQHFTHohFUQgghhBDiUmgElRBCCCHEAhpBdSwaQSWEEEIIIS6FRlAJIYQQQiyQmAzOZJv2KcO2/VUmlKASQgghhFhAZaYciy7xE0IIIYQQl0IJKiGEEEKIBTI4JBvfyjKCOm/ePERERECj0SAqKgp79+41237Pnj2IioqCRqNBnTp18P333xdrs3btWjRu3BhqtRqNGzfG+vXrSx2XrVGCSgghhBBSAaxevRpTpkzBO++8g+PHj6Nz587o378/4uLiSmx/9epVDBgwAJ07d8bx48cxffp0vPzyy1i7dq2xzf79+zFixAiMGjUKJ06cwKhRozB8+HAcPHjQUS+rRIxzXmUmQKSnp8PHxwdpaWnw9vZ2djiEEEIIsYIzf38XnNtTPROMaWzaN+e5yMx73+rX1a5dO7Rq1Qrz5883HmvUqBGGDh2KTz/9tFj7t956C3/88QfOnj1rPDZx4kScOHEC+/fvBwCMGDEC6enp2Lx5s7FNv3794Ofnh5UrV5bn5ZVLlVokVZCLp6enOzkSQgghhFir4Pe2M8fUOPJsXQbV0CeK5yVqtRpqtbrIMa1Wi6NHj+Ltt98ucrxPnz74999/S+x///796NOnT5Fjffv2xaJFi6DT6aBUKrF//368+uqrxdp89dVXZXlJNlOlEtSMjAwAQEhIiJMjIYQQQkhpZWRkwMfHx6HnVKlUCAoKQnLy/9mlf09Pz2J5ycyZMzFr1qwix27fvg1JkhAYGFjkeGBgIJKTk0vsOzk5ucT2er0et2/fRs2aNU22MdWno1SpBDU4OBjx8fHw8vICY6zc/aWnpyMkJATx8fE0ZcAF0PvhOui9cB30XrgWej/KhnOOjIwMBAcHO/zcGo0GV69ehVartUv/nPNiOcmDo6eFPdi2pOdbav/g8dL26QhVKkEVBAG1a9e2eb/e3t70g8aF0PvhOui9cB30XrgWej9Kz9Ejp4VpNBpoNLadf1paAQEBEEWx2MhmSkpKsRHQAoaR3+LtFQoF/P39zbYx1aej0Cp+QgghhBAXp1KpEBUVhW3bthU5vm3bNnTo0KHE50RHRxdrv3XrVrRu3RpKpdJsG1N9OkqVGkElhBBCCKmopk6dilGjRqF169aIjo7GwoULERcXh4kTJwIApk2bhoSEBPz8888ADCv2v/vuO0ydOhXjx4/H/v37sWjRoiKr81955RV06dIFs2fPxpAhQ7BhwwZs374d+/btc8prLEAJajmo1WrMnDnT7FwR4jj0frgOei9cB70XroXeD1IeI0aMwJ07d/DBBx8gKSkJTZs2xaZNmxAWFgYASEpKKlITNSIiAps2bcKrr76KuXPnIjg4GN988w0ee+wxY5sOHTpg1apVePfdd/Hee++hbt26WL16Ndq1a+fw11dYlaqDSgghhBBCXB/NQSWEEEIIIS6FElRCCCGEEOJSKEElhBBCCCEuhRJUQgghhBDiUihBLaOHH34YoaGh0Gg0qFmzJkaNGoXExMQibeLi4jB48GB4eHggICAAL7/8st12oqjKrl27hnHjxiEiIgJubm6oW7cuZs6cWexrTe+HY3z88cfo0KED3N3d4evrW2Ibei8cZ968eYiIiIBGo0FUVBT27t3r7JAqvZiYGAwePBjBwcFgjOH3338v8jjnHLNmzUJwcDDc3NzQrVs3/Pfff84JlhAXRQlqGXXv3h2//vorzp8/j7Vr1+Ly5ct4/PHHjY9LkoSBAwciKysL+/btw6pVq7B27Vq89tprToy6cjp37hxkWcaCBQvw33//4csvv8T333+P6dOnG9vQ++E4Wq0Ww4YNwwsvvFDi4/ReOM7q1asxZcoUvPPOOzh+/Dg6d+6M/v37FylDQ2wvKysLzZs3x3fffVfi45999hm++OILfPfddzh8+DCCgoLQu3dvZGRkODhSQlwYJzaxYcMGzhjjWq2Wc875pk2buCAIPCEhwdhm5cqVXK1W87S0NGeFWWV89tlnPCIiwnif3g/HW7x4Mffx8Sl2nN4Lx2nbti2fOHFikWMNGzbkb7/9tpMiqnoA8PXr1xvvy7LMg4KC+P/93/8Zj+Xm5nIfHx/+/fffOyFCQlwTjaDaQGpqKpYvX44OHToYtw7bv38/mjZtiuDgYGO7vn37Ii8vD0ePHnVWqFVGWloaqlWrZrxP74froPfCMbRaLY4ePYo+ffoUOd6nTx/8+++/ToqKXL16FcnJyUXeF7Vaja5du9L7QkghlKCWw1tvvQUPDw/4+/sjLi4OGzZsMD6WnJyMwMDAIu39/PygUqmQnJzs6FCrlMuXL+Pbb781bv0G0PvhSui9cIzbt29DkqRiX+vAwED6OjtRwdee3hdCzKMEtZBZs2aBMWb2duTIEWP7N954A8ePH8fWrVshiiJGjx4NXmhjLsZYsXNwzks8Toor7fsBAImJiejXrx+GDRuG5557rshj9H6UXVneC3PovXCcB7+m9HV2DfS+EGKewtkBuJKXXnoJTzzxhNk24eHhxr8HBAQgICAA9evXR6NGjRASEoIDBw4gOjoaQUFBOHjwYJHn3r17FzqdrtgnZ1Ky0r4fiYmJ6N69O6Kjo7Fw4cIi7ej9KJ/Svhfm0HvhGAEBARBFsdioXEpKCn2dnSgoKAiAYSS1Zs2axuP0vhBSFCWohRQknGVRMHKal5cHAIiOjsbHH3+MpKQk4w+hrVu3Qq1WIyoqyjYBV3KleT8SEhLQvXt3REVFYfHixRCEohcH6P0on/L823gQvReOoVKpEBUVhW3btuGRRx4xHt+2bRuGDBnixMiqtoiICAQFBWHbtm1o2bIlAMN84T179mD27NlOjo4Q10EJahkcOnQIhw4dQqdOneDn54crV65gxowZqFu3LqKjowEYFiI0btwYo0aNwueff47U1FS8/vrrGD9+PLy9vZ38CiqXxMREdOvWDaGhoZgzZw5u3bplfKxgtILeD8eJi4tDamoq4uLiIEkSYmNjAQD16tWDp6cnvRcONHXqVIwaNQqtW7c2XlmIi4srMj+b2F5mZiYuXbpkvH/16lXExsaiWrVqCA0NxZQpU/DJJ58gMjISkZGR+OSTT+Du7o6nnnrKiVET4mKcWEGgwjp58iTv3r07r1atGler1Tw8PJxPnDiR37hxo0i769ev84EDB3I3NzderVo1/tJLL/Hc3FwnRV15LV68mAMo8VYYvR+OMWbMmBLfi127dhnb0HvhOHPnzuVhYWFcpVLxVq1a8T179jg7pEpv165dJf4bGDNmDOfcUGpq5syZPCgoiKvVat6lSxd+6tQp5wZNiIthnBda1UMIIYQQQoiT0Sp+QgghhBDiUihBJYQQQgghLoUSVEIIIYQQ4lIoQSWEEEIIIS6FElRCCCGEEOJSKEElhBBCCCEuhRJUQgghhBDiUihBJYQQQgghLoUSVEIIIYQQ4lIoQSWElCg5ORmTJ09GnTp1oFarERISgsGDB2PHjh3ODs2ljB07FkOHDrXYLiYmBoMHD0ZwcDAYY/j999/tHhshhFRUlKASQoq5du0aoqKisHPnTnz22Wc4deoU/v77b3Tv3h2TJk1ydngVUlZWFpo3b47vvvvO2aEQQojLowSVEFLMiy++CMYYDh06hMcffxz169dHkyZNMHXqVBw4cMDYLi4uDkOGDIGnpye8vb0xfPhw3Lx50/j4rFmz0KJFC/z0008IDQ2Fp6cnXnjhBUiShM8++wxBQUGoUaMGPv744yLnZ4xh/vz56N+/P9zc3BAREYE1a9YUaXPq1Cn06NEDbm5u8Pf3x4QJE5CZmWl8vGBkc86cOahZsyb8/f0xadIk6HQ6YxutVos333wTtWrVgoeHB9q1a4fdu3cbH1+yZAl8fX2xZcsWNGrUCJ6enujXrx+SkpKMr2/p0qXYsGEDGGNgjBV5fmH9+/fHRx99hEcffbTU7wchhFQ1lKASQopITU3F33//jUmTJsHDw6PY476+vgAAzjmGDh2K1NRU7NmzB9u2bcPly5cxYsSIIu0vX76MzZs34++//8bKlSvx008/YeDAgbhx4wb27NmD2bNn49133y2S+ALAe++9h8ceewwnTpzA008/jSeffBJnz54FAGRnZ6Nfv37w8/PD4cOHsWbNGmzfvh0vvfRSkT527dqFy5cvY9euXVi6dCmWLFmCJUuWGB9/5pln8M8//2DVqlU4efIkhg0bhn79+uHixYvGNtnZ2ZgzZw5++eUXxMTEIC4uDq+//joA4PXXX8fw4cONSWtSUhI6dOhQ5q89IYSQfJwQQgo5ePAgB8DXrVtntt3WrVu5KIo8Li7OeOy///7jAPihQ4c455zPnDmTu7u78/T0dGObvn378vDwcC5JkvFYgwYN+Keffmq8D4BPnDixyPnatWvHX3jhBc455wsXLuR+fn48MzPT+PjGjRu5IAg8OTmZc875mDFjeFhYGNfr9cY2w4YN4yNGjOCcc37p0iXOGOMJCQlFztOzZ08+bdo0zjnnixcv5gD4pUuXjI/PnTuXBwYGGu+PGTOGDxkyxOzX6kEA+Pr160v1HEIIqUoUTs2OCSEuh3MOwHCZ3ZyzZ88iJCQEISEhxmONGzeGr68vzp49izZt2gAAwsPD4eXlZWwTGBgIURQhCEKRYykpKUX6j46OLnY/NjbWeO7mzZsXGeHt2LEjZFnG+fPnERgYCABo0qQJRFE0tqlZsyZOnToFADh27Bg456hfv36R8+Tl5cHf3994393dHXXr1i3Sx4OxEkIIsS1KUAkhRURGRoIxhrNnz5pdnc45LzGJffC4Uqks8jhjrMRjsixbjK2gX1PnLtzG1LkLziPLMkRRxNGjR4sksQDg6elpto+CJJ4QQoh90BxUQkgR1apVQ9++fTF37lxkZWUVe/zevXsADKOlcXFxiI+PNz525swZpKWloVGjRuWO48E5qQcOHEDDhg2N546NjS0S3z///ANBEIqNiJrSsmVLSJKElJQU1KtXr8gtKCjI6jhVKhUkSbK6PSGEEMsoQSWEFDNv3jxIkoS2bdti7dq1uHjxIs6ePYtvvvnGeOm9V69eeOihhzBy5EgcO3YMhw4dwujRo9G1a1e0bt263DGsWbMGP/30Ey5cuICZM2fi0KFDxkVQI0eOhEajwZgxY3D69Gns2rULkydPxqhRo4yX9y2pX78+Ro4cidGjR2PdunW4evUqDh8+jNmzZ2PTpk1WxxkeHo6TJ0/i/PnzuH37dpEqAYVlZmYiNjbWOE3h6tWriI2NRVxcnNXnIoSQqoISVEJIMRERETh27Bi6d++O1157DU2bNkXv3r2xY8cOzJ8/HwCMxeb9/PzQpUsX9OrVC3Xq1MHq1attEsP777+PVatW4aGHHsLSpUuxfPlyNG7cGIBhXuiWLVuQmpqKNm3a4PHHH0fPnj1LXWN08eLFGD16NF577TU0aNAADz/8MA4ePFhkXq0l48ePR4MGDdC6dWtUr14d//zzT4ntjhw5gpYtW6Jly5YAgKlTp6Jly5aYMWNGqWImhJCqgHGaTEUIcTGMMaxfv96qHZoIIYRUPjSCSgghhBBCXAolqIQQQgghxKVQmSlCiMuhmUeEEFK10QgqIYQQQghxKZSgEkIIIYQQl0IJKiGEEEIIcSmUoBJCCCGEEJdCCSohhBBCCHEplKASQgghhBCXQgkqIYQQQghxKZSgEkIIIYQQl/L/b1isL9LKdp8AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## t-SNE (t-distributed Stochastic Neighbor Embedding)\n",
    "# t-SNE is a nonlinear technique that is particularly useful for visualizing high-dimensional data in lower dimensions (typically 2D).\n",
    "tsne = TSNE(n_components=2, random_state=42)\n",
    "X_tsne = tsne.fit_transform(X_scaled)\n",
    "\n",
    "# Plot the t-SNE result\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.scatter(X_tsne[:, 0], X_tsne[:, 1], c=y, cmap='plasma', s=50)\n",
    "plt.title(\"t-SNE - 2 Components\")\n",
    "plt.xlabel(\"Component 1\")\n",
    "plt.ylabel(\"Component 2\")\n",
    "plt.colorbar(label=\"Class Labels\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Clustering Methods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\ProgramData\\Anaconda3\\envs\\nlp-cv-ir\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1429: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=1.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Apply K-Means with a Selected Value of K\n",
    "# Applying K-Means with a random number of clusters (for example, k=5)\n",
    "random_k = 5\n",
    "kmeans_random = KMeans(n_clusters=random_k, random_state=42)\n",
    "X_kmeans_random = kmeans_random.fit_predict(X_scaled)\n",
    "\n",
    "# Plot K-Means Clusters with Random K\n",
    "pca = PCA(n_components=2)\n",
    "X_pca = pca.fit_transform(X_scaled)\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.scatter(X_pca[:, 0], X_pca[:, 1], c=X_kmeans_random, cmap='rainbow', s=50)\n",
    "plt.title(f\"K-Means Clustering (k={random_k}) on PCA Reduced Data\")\n",
    "plt.xlabel(\"Principal Component 1\")\n",
    "plt.ylabel(\"Principal Component 2\")\n",
    "plt.colorbar(label=\"Cluster Labels\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We apply the elbow method to try to find an optimal K"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\ProgramData\\Anaconda3\\envs\\nlp-cv-ir\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1429: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=1.\n",
      "  warnings.warn(\n",
      "c:\\ProgramData\\Anaconda3\\envs\\nlp-cv-ir\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1429: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=1.\n",
      "  warnings.warn(\n",
      "c:\\ProgramData\\Anaconda3\\envs\\nlp-cv-ir\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1429: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=1.\n",
      "  warnings.warn(\n",
      "c:\\ProgramData\\Anaconda3\\envs\\nlp-cv-ir\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1429: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=1.\n",
      "  warnings.warn(\n",
      "c:\\ProgramData\\Anaconda3\\envs\\nlp-cv-ir\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1429: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=1.\n",
      "  warnings.warn(\n",
      "c:\\ProgramData\\Anaconda3\\envs\\nlp-cv-ir\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1429: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=1.\n",
      "  warnings.warn(\n",
      "c:\\ProgramData\\Anaconda3\\envs\\nlp-cv-ir\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1429: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=1.\n",
      "  warnings.warn(\n",
      "c:\\ProgramData\\Anaconda3\\envs\\nlp-cv-ir\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1429: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=1.\n",
      "  warnings.warn(\n",
      "c:\\ProgramData\\Anaconda3\\envs\\nlp-cv-ir\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1429: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=1.\n",
      "  warnings.warn(\n",
      "c:\\ProgramData\\Anaconda3\\envs\\nlp-cv-ir\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1429: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=1.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Elbow Method for Finding \"Optimal\" K\n",
    "# The elbow method helps in selecting the optimal number of clusters by plotting the sum of squared distances (inertia) for different values of k.\n",
    "inertia = []\n",
    "k_values = range(1, 11)\n",
    "\n",
    "for k in k_values:\n",
    "    kmeans = KMeans(n_clusters=k, random_state=42)\n",
    "    kmeans.fit(X_scaled)\n",
    "    inertia.append(kmeans.inertia_)\n",
    "\n",
    "# Plot the Elbow curve\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.plot(k_values, inertia, marker='o', linestyle='--')\n",
    "plt.title(\"Elbow Method for Optimal K\")\n",
    "plt.xlabel(\"Number of Clusters (K)\")\n",
    "plt.ylabel(\"Inertia (Sum of Squared Distances)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the plot, the correct number of clusters is k=3 (for Iris dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\ProgramData\\Anaconda3\\envs\\nlp-cv-ir\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:1429: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=1.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "optimal_k = 3\n",
    "\n",
    "# Apply K-Means with Optimal K\n",
    "kmeans_optimal = KMeans(n_clusters=optimal_k, random_state=42)\n",
    "X_kmeans_optimal = kmeans_optimal.fit_predict(X_scaled)\n",
    "\n",
    "# Plot K-Means Clusters with Optimal K\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.scatter(X_pca[:, 0], X_pca[:, 1], c=X_kmeans_optimal, cmap='rainbow', s=50)\n",
    "plt.title(f\"K-Means Clustering (k={optimal_k}) on PCA Reduced Data\")\n",
    "plt.xlabel(\"Principal Component 1\")\n",
    "plt.ylabel(\"Principal Component 2\")\n",
    "plt.colorbar(label=\"Cluster Labels\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cluster Validation\n",
    "Check the Silhouette Score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Silhouette Score for K-Means (k=5): 0.3450\n",
      "Silhouette Score for K-Means (k=3): 0.4799\n"
     ]
    }
   ],
   "source": [
    "# Silhouette Score for Random K-Means\n",
    "silhouette_avg_random = silhouette_score(X_scaled, X_kmeans_random)\n",
    "print(f\"Silhouette Score for K-Means (k={random_k}): {silhouette_avg_random:.4f}\")\n",
    "\n",
    "\n",
    "# Silhouette Score for Optimal K-Means\n",
    "silhouette_avg_optimal = silhouette_score(X_scaled, X_kmeans_optimal)\n",
    "print(f\"Silhouette Score for K-Means (k={optimal_k}): {silhouette_avg_optimal:.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Other Clustering Methods"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### DBSCAN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# DBSCAN (Density-Based Spatial Clustering of Applications with Noise)\n",
    "# DBSCAN is a density-based clustering method that groups points that are closely packed together, marking points in sparse regions as noise.\n",
    "\n",
    "dbscan = DBSCAN(eps=0.5, min_samples=5)\n",
    "X_dbscan = dbscan.fit_predict(X_scaled)\n",
    "\n",
    "# Plot DBSCAN Clusters\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.scatter(X_pca[:, 0], X_pca[:, 1], c=X_dbscan, cmap='coolwarm', s=50)\n",
    "plt.title(\"DBSCAN Clustering on PCA Reduced Data\")\n",
    "plt.xlabel(\"Principal Component 1\")\n",
    "plt.ylabel(\"Principal Component 2\")\n",
    "plt.colorbar(label=\"Cluster Labels\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Silhouette Score for DBSCAN: 0.3565\n"
     ]
    }
   ],
   "source": [
    "# Silhouette Score for DBSCAN\n",
    "# Since some points might be labeled as noise (-1) do not calculate the silhouette score\n",
    "if len(set(X_dbscan)) > 1:  # Ensuring that there is more than one cluster\n",
    "    silhouette_avg_dbscan = silhouette_score(X_scaled, X_dbscan)\n",
    "    print(f\"Silhouette Score for DBSCAN: {silhouette_avg_dbscan:.4f}\")\n",
    "else:\n",
    "    print(\"DBSCAN resulted in only one cluster or too many noise points, no silhouette score calculated.\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Hierarchical Clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Agglomerative Clustering\n",
    "# Hierarchical clustering groups data points in a tree-like structure by successively merging or splitting clusters.\n",
    "\n",
    "# Perform hierarchical clustering\n",
    "hierarchical = AgglomerativeClustering(n_clusters=3)\n",
    "X_hierarchical = hierarchical.fit_predict(X_scaled)\n",
    "\n",
    "# Plot Hierarchical Clustering Dendrogram (for visualization)\n",
    "linked = linkage(X_scaled, 'ward')\n",
    "\n",
    "plt.figure(figsize=(10, 7))\n",
    "dendrogram(linked, orientation='top', distance_sort='descending', show_leaf_counts=True)\n",
    "plt.title(\"Hierarchical Clustering Dendrogram\")\n",
    "plt.xlabel(\"Data Points\")\n",
    "plt.ylabel(\"Euclidean Distance\")\n",
    "plt.show()\n",
    "\n",
    "# Plot the Hierarchical Clustering result\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.scatter(X_pca[:, 0], X_pca[:, 1], c=X_hierarchical, cmap='Spectral', s=50)\n",
    "plt.title(\"Hierarchical Clustering on PCA Reduced Data\")\n",
    "plt.xlabel(\"Principal Component 1\")\n",
    "plt.ylabel(\"Principal Component 2\")\n",
    "plt.colorbar(label=\"Cluster Labels\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Silhouette Score for Hierarchical Clustering: 0.4467\n"
     ]
    }
   ],
   "source": [
    "# Silhouette Score for Hierarchical Clustering\n",
    "silhouette_avg_hierarchical = silhouette_score(X_scaled, X_hierarchical)\n",
    "print(f\"Silhouette Score for Hierarchical Clustering: {silhouette_avg_hierarchical:.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Case Study\n",
    "\n",
    "Think about the case study you want to apply these data science tools to.\n",
    "\n",
    "We are aiming for:\n",
    "- Groups of 3 students (2 or individual is also possible depending on the case)\n",
    "- Final presentation in the last course session (18th October)\n",
    "\n",
    "Pick an interesting dataset:\n",
    "- Take some time to choose your dataset\n",
    "- From Kaggle or UCI\n",
    "- Bring your own"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Requirements\n",
    "\n",
    "- Between 500 to 100k samples\n",
    "- Tabular file (csv)\n",
    "- Only categorical and/or numerical features\n",
    "\n",
    "Potential datasets (links on slides):\n",
    "- Cost of Living Index by Country\n",
    "- Red Wine Quality\n",
    "- House Rent Prediction\n",
    "- Stellar Classification\n",
    "- Sleep Efficiency\n",
    "- Healthcare Diabetes Dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Case Study Requirements\n",
    "\n",
    "One operation of each of the following:\n",
    "- Dataset Descriptive Statistics\n",
    "- Data Cleaning (e.g. checking for NaNs, column removal, etc.)\n",
    "- Model Selection, Feature Engineering, and Normalization\n",
    "- Plotting (frequency, correlation between feature pairs)\n",
    "- Supervised Learning: \n",
    "- Training a linear classifier\n",
    "- Evaluate its performance over multiple metrics\n",
    "\n",
    "Let’s simulate a Data Science team discussion:\n",
    "\n",
    "Bring your expertise and point of view!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### Presentation\n",
    "\n",
    "We Invite all groups to present and discuss their use-case with the class:\n",
    "- Show and discuss your notebook to the class\n",
    "- 5 to 7 minutes per presentation\n",
    "- Presentations on the 18th of October (next Friday)."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "nlp-cv-ir",
   "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": "3.9.20"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}