"README.md" did not exist on "9a0659abb6744ddd66b51940719d318a52092e49"
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"metadata": {},
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],
"source": [
"# IGNORE THIS CELL WHICH CUSTOMIZES LAYOUT AND STYLING OF THE NOTEBOOK !\n",
"import matplotlib.pyplot as plt\n",
"%matplotlib inline\n",
"%config InlineBackend.figure_format = 'retina'\n",
"import warnings\n",
"warnings.filterwarnings('ignore', category=FutureWarning)\n",
"warnings.filterwarnings('ignore', category=DeprecationWarning)\n",
"from IPython.core.display import HTML; HTML(open(\"custom.html\", \"r\").read())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Chapter 7: Regression\n",
"\n",
"Regression belongs like classification to the field of supervised learning. \n",
"\n",
"<div class=\"alert alert-block alert-warning\">\n",
"<i class=\"fa fa-info-circle\"></i> \n",
"<strong>Regression predicts numerical values</strong> \n",
"in contrast to classification which predicts categories.\n",
"</div>\n",
"\n",
"\n",
"\n",
"Other differences are:\n",
"\n",
"* Accuracy is measured differently\n",
"\n",
"* Other algorithms"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Example: Salmon weight\n",
"\n",
"The dataset `salmon.csv` holds measurements of `circumference`, `length` and `weight` for `atlantic` and `sockeye` salmons.\n",
"\n",
"Our goal is to predict `weight` based on the other three features."
]
},
{
"cell_type": "code",
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"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>circumference</th>\n",
" <th>length</th>\n",
" <th>kind</th>\n",
" <th>weight</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>25.5</td>\n",
" <td>85.5</td>\n",
" <td>atlantic</td>\n",
" <td>31.2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>22.5</td>\n",
" <td>62.5</td>\n",
" <td>atlantic</td>\n",
" <td>12.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>29.0</td>\n",
" <td>88.0</td>\n",
" <td>atlantic</td>\n",
" <td>34.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>32.5</td>\n",
" <td>85.5</td>\n",
" <td>atlantic</td>\n",
" <td>62.7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>24.5</td>\n",
" <td>74.5</td>\n",
" <td>atlantic</td>\n",
" <td>24.2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" circumference length kind weight\n",
"0 25.5 85.5 atlantic 31.2\n",
"1 22.5 62.5 atlantic 12.4\n",
"2 29.0 88.0 atlantic 34.8\n",
"3 32.5 85.5 atlantic 62.7\n",
"4 24.5 74.5 atlantic 24.2"
]
},
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"\n",
"df = pd.read_csv(\"salmon.csv\")\n",
"df.head()"
]
},
{
"cell_type": "code",
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"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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" <th></th>\n",
" <th>circumference</th>\n",
" <th>length</th>\n",
" <th>kind</th>\n",
" <th>weight</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>95</th>\n",
" <td>19.0</td>\n",
" <td>69.5</td>\n",
" <td>sockeye</td>\n",
" <td>18.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>96</th>\n",
" <td>18.5</td>\n",
" <td>67.0</td>\n",
" <td>sockeye</td>\n",
" <td>18.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>97</th>\n",
" <td>24.5</td>\n",
" <td>67.5</td>\n",
" <td>sockeye</td>\n",
" <td>24.7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98</th>\n",
" <td>21.0</td>\n",
" <td>66.5</td>\n",
" <td>sockeye</td>\n",
" <td>26.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>99</th>\n",
" <td>27.5</td>\n",
" <td>86.5</td>\n",
" <td>sockeye</td>\n",
" <td>43.4</td>\n",
" </tr>\n",
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"</table>\n",
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],
"text/plain": [
" circumference length kind weight\n",
"95 19.0 69.5 sockeye 18.8\n",
"96 18.5 67.0 sockeye 18.9\n",
"97 24.5 67.5 sockeye 24.7\n",
"98 21.0 66.5 sockeye 26.0\n",
"99 27.5 86.5 sockeye 43.4"
]
},
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.tail()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let us inspect the features and their distributions:"
]
},
{
"cell_type": "code",
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"metadata": {},
"outputs": [
{
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yNiMiGhL6y+JmSwee2bwPzy6azMwjCjAskBERERH5gFoQUFBS61LbwlKj3926Y50IpqdE9xibdQUFJ4pENBS4ksVnm1qwbP0uLL53Aianj2bmEQUI3mJJRERE5CMjw4IxdvRICP1MrEzN7T4akfvUgtDrNSeJRDS0uJKxzZYOfFp8iplHFEC4goyIiIjIy0RJgloQkPvDdABA48VWfLLva3y8twbNlo4+7XURGh+P0Lesv4ej10QUWHydCa5mbH/tmGVEwwsLZEREREReYt2jpqK6CQUltd32sEnC/JxrcdskPZ7ZvA9nm1p6fG96pn5Y7m/j6PeYkZWEDEPcsDxnInJMiUwQJQkzspJQVFbXb1tHWcwsIxqeWCAjIiIi8gJRkmFp67D7pLSisjqk6XVY/ZOb8OyiyVi2fpdtJVmaXud3+495giu/R15uNrQhQZxYEgUApTJBLQjIMMQhTa9z+tAUR1nMLCMavrj+k4iIiMgL1ILK7gTKqtJowpo/70d8dBhyJicDgG1iZd0Eejhx5ffI31LMCSVRgFAyE0RJRl5uNtL0OrufO8tiZhnR8MUVZEREREQeJkoSKqqbnK5OALomUl9WNeAHU65GekoMMgyxw/LWHHd+j/KqRqSnxAy734CIrlA6E9SCCtqQIKxbOgXlVY0oLDV2uwVe7zCLlR43EXkXC2REREREHqYWBBSU1LrUdmdpLW54IA7pKTHffnf4Tabc+T0KS43D8hZTIrrCHzLBmrXpKdE9+reuGrOXxf4wbiLyHt5iSUREROQFpuZ2t9oNx8JYd+7+HkQ0vPlLJvR+6mR/Wewv4yYiz2OBjIiIiMgLdBEaj7Yb6vh7EFF3QzUThuq4iah/LJAREREROSFKktPXjr4zIyvJpf6nZ+q9sin/QMbtLf7wexCRdwzVjByIoTpuInIN9yAjIiIissO6QXNFdRMKSmptGzjPyEpChiHO6Wb6akFAhiEOaXqd082c0/Q6j+9RM5hxe4uSvwcReYcvM1Lyk0ITs4xoeGOBjIiIiKgXUZJhaetA/pbiPpOgorI6pOl1yMvNhjYkyOEEUJRk5OVm2+0DgK0PTxasPDFub1Hi9yAi7/BVRq7+yU1outgKTbBakdyyh1lGNHyxQEZERETUi1pQOZz8AECl0YT8LcVYt3SK0z60IUFYt3QKyqsaUVhqtK2wmJ6pR4Yh1uMTKE+M21uU+D2IyDs8nZFfVjVgZ+mVVWi3ZCbhBkMczp1vwTOb92GkNliR3LKHWUY0fLFARkRERNSNKEmoqG5yevsM0DUBLK9qRHpKjJPbiLreT0+J7nG7jXVfGk9OoDw5bm/x5e9BRN7h2ayRcbapBVfFhmPZAzfa3m00WbD1o6P4aG8NzK0dOIsWxXLLHmYZ0fDEAhkRERFRN2pBQEFJrUttC0uNLu0zoxaEXq89P3nyxri9xRe/BxF5hyezRi0IeOvTSuwuPw39qAhoQ0bA0tYJY31zn33HlM4te5hlRMMLC2REREREvZia2z3azleG6riJaGjxZNaYmtshSTK+PnvJI8ckIhooof8mRERERIFFF6HxaDtfUWrcoiQ5fU1Ew4sns8ZXucWcIqL+cAUZERERUTeiJGFGVhKKyur6bTs9U+83mzErMW5rHxXVTSgoubLB9oysJGQY4vzmtyEiz/Fk1vgit5hTROQqFsiIiIiIulELAjIMcUjT65xuQp2m1/nVfji+HrcoybC0ddh9kl1RWR3S9Drk5WZDGxLEySfRMOLJrPF2bjGniMgdvMWSiIiIqBdRkpGXm400vc7u59ZJldhrE2ml+XLcakFld9JpVWk0IX9LMSedRMOQJ7PGm7nFnCIid3AFGREREVEvakEFbUgQ1i2dgvKqRhSWGm235UzP1CPDEOuXt+X4atyiJKGiusnpig+ga/JZXtWI9JQYv/utiGjgPJk13sot5hQRucsvC2QtLS0ICwtTehhEREQUwKwTpfSU6B639lhXMfjrRMoX41YLAgpKal1qW1hq9KtbUYnIMzyZNd7ILeYUEbnLL26xPHfuHF544QXceeedGDduHLKysgAA9fX1ePDBB1FYWKjwCImIiChQqQWh12v/LIz15u1xm5rbPdqOiIYmT2aNp3OLOUVE7lB8Bdnnn3+OZcuWwWw2Q5a7/oZApeoKwrq6OpSWluKLL77AkiVL8Nhjjyk5VCIiIiL6li5C49F2RESexpwiIncouoLMaDTi8ccfR3NzM+644w5s3LgR1113ne3zsWPH4p577oEsy9i0aROKioqUGywRERHRAImS5PT1UCNKEmZkJbnUdnqm3u8eZkDkj4ZbTiiNOUVE7lJ0Bdkrr7yC1tZW/OIXv8Cjjz4KAPjLX/5i+zw6Ohq/+c1vcM0112DdunV46623MG3aNIVGS0REROQe68bSFdVNKCiptW08PSMrCRmGOL/c6N8VakFAhiEOaXqd0w2w0/Q67utD1I/hmhNKY04RkbsULZDt2bMH3/nOd5Cbm+u03YIFC/Dqq6/i0KFDPhoZERER0eCIkgxLWwfytxT3mZwVldUhTa9DXm42tCFBQ3LyK0oy8nKz7Z4fANv5cXJP5NhwzwmlMaeIyB2KFsjOnz+PtLQ0qNVqp+3UajWuuuoqHDt2zEcjIyIiIhoctaByOCkDgEqjCflbirFu6RQfj8wz1IIK2pAgrFs6BeVVjSgsNdpWvkzP1CPDEMtJJ1E/hntOKI05RUTuULRANnLkSJw5c8altvX19YiMjPTyiIiIiIgGT5QkVFQ3Ob2tB+ia/JZXNSI9JWZITtCsY05Pie5xi5J1L5+heE5EvhIoOaE05hQRuUrRTfozMjJgMpnwySefOG330UcfobGxERMmTPDRyIiIiIgGTi0IKCipdaltYalxyE/Q1ILQ6/XQPh8iXwi0nFAac4qI+qNogeyRRx6BLMtYvXo1/vnPf6K9vb3H552dnXjvvfewatUqqFQqzJs3b9DHFEURf/vb3/CDH/wA6enpmDRpEn784x87fEJmTU0Nli1bhqlTp2LChAmYOXMmtm7dColPlSEiIiInTM3t/Tdyox0RDT/MCSIi/6HoLZZZWVl4/PHHsWHDBqxcudJWCAOAmTNnoq6uDm1tbZBlGQsWLMDNN9886GOuXLkSO3bsQHh4OCZPnoyOjg4cOHAAe/bsweOPP44lS5bY2h47dgzz5s2D2WzGxIkTkZ6ejv379+O5557DwYMHsW7dukGPh4iIiIYnXYTGo+08QZSkHqsoer8mIt/yRk7wOiciGhhFC2QAsHjxYqSkpGDDhg2orq62vX/8+HEAQGJiIhYvXowf/ehHgz7WRx99hB07diA5ORlvvPEGYmJibMeaO3cuNm7ciLvuugtjx46FLMtYsWIFzGYzXnrpJdx9990AgAsXLuCRRx7Bhx9+iNtuuw3f//73Bz0uIiIiGl5EScKMrCQUldX123Z6pt7rm0Rb+6+obkJBSa1tk+oZWUnIMMRxk2oiBXg6J3idExENjuIFMgC4/fbbcfvtt6O2thbV1dUwm80IDQ3F2LFjkZKS4rHjfPDBBwCA5cuX24pjAJCamoqZM2firbfewp49ezB27Fjs2bMHlZWVmDRpkq04BgBRUVH49a9/jblz52Lr1q0skCns5Fr3CqdXr/qHl0ZCRER0hVoQkGGIQ5pe53QD7jS9rsem0d4gSjIsbR12n5RXVFaHNL0OebnZ0IYEcfJM5EOezAle50REg+c3a20bGxuRlJSEW265BTNnzsStt96Kixcv4tixYx47xoYNG/Dhhx9iypS+j0luaWkBAKjVagDA559/DgC49dZb+7SdOHEioqOj8cUXX8BsNntsfERERDR8iJKMvNxspOl1dj+3TlitT1LzFrWgsjtptqo0mpC/pZiTZiIFeConeJ0TEQ2e4ivI6uvrsXLlShw4cAB79+7FyJEjbZ9t2bIFu3fvRnZ2Nn7zm98gPj5+UMcKDg6GwWDo8/7OnTvxySefQKvV2gpi1ts97bUHgOTkZJw/fx4nTpzg0zWJiIioD7WggjYkCOuWTkF5VSMKS422W56mZ+qRYYj1wa2VEiqqm5yuTgG6Js/lVY1IT4nhBJrIhzyRE7zOiYg8Q9ECWWNjI2bPno36+nqMGDECDQ0NPQpko0aNQkhICPbt24f58+dj+/btiIiI8Mix29rasGLFClRXV+PEiRNISEjASy+9ZLv1sqGhAQAQG2t/ObP1/aampn6PtX37drz//vsujevo0aMutSMiGu6YnTQcWCeh6SnRPW6Rsq4G8fYkVS0IKCipdaltYanR67d7kvcxO4eeweYEr3MiIs9QtEC2adMm1NfXIzs7G7/97W/7FKOeffZZLFu2DE8++ST27t2LzZs348knn/TIsc+cOYNPP/20x3uVlZXIysoCALS2tgIAQkJC7H7f+r7FYun3WKdPn8aBAwcGM1wiooDD7KThpPcT5Hy5esPU3O7RduTfmJ1D12Bygtc5EdHgKVog2717N0JDQ7F+/XpERkbabRMZGYnf/va3uOWWW/DZZ595rEAWHx+P4uJiCIKAvXv3Yu3atVizZg0sFgsWLVpk24tMpXL+B5MkSf0eKzExEZMmTXJpXEePHkVzc7NLbYmIhjNmJ5Fn6CI0Hm1H/o3ZGZh4nRMRDZ7it1impqY6LI5ZRUVFITk5GSdOnPDYsbVaLbRaLQAgJycHo0ePxpw5c/DKK6/g4YcfRmhoKICuWzHtsb4fFhbW77FmzZqFWbNmuTSu+fPn82/9iIjA7CTyBFGSMCMrCUVldf22nZ6p9/qeaOR9zM7Aw+uciMgzFH2KZWRkJEwm55tJWpnNZltByxsyMjKg1+thNptRW1uLuLg4AI73GGtsbATgeI8yIiIiIqWpBQEZhjiHT8izStPrkGGI5aSZaAjidU5E5BmKFsiuu+46nDt3Dv/5z3+cttuzZw/q6uowbty4AR9LlmW89NJLeOKJJ9DZ2Wm3TXBwMACgs7MTqampAK48zbJ3XydPnoRarcY111wz4DEREREReZsoycjLzXY4eU7T65CXm23bEJyIhh5e50REg6foLZZz587Frl27sGLFCjz99NO4++67e2yKf/nyZfzrX//CCy+8AJVKhblz5w74WCqVCgUFBfj666/xwx/+EFOnTu3xeW1tLWpqaqDVapGcnIzvfe97ePXVV1FQUIB58+b1aFtWVoYLFy5g0qRJCA8PH/CYiIiIiLxNLaigDQnCuqVTUF7ViMJSI0zN7dBFaDA9U48MQyxvuSIa4nidExENnqIFsmnTpmHu3LnYtm0bfv3rX2PNmjVITExEWFgYLBYLTp8+jc7OTsiyjNmzZ+O2224b1PFmz56Nl156Cc899xzS0tIQHx8PAKivr8eyZcvQ2dmJRx55BBqNBpMmTUJqair27NmDd955B7NnzwYAXLhwAfn5+QCABQsWDO4HICIiIvIB66Q4PSUaGYYr20NYV5Nw0kw09PE6JyIaHEULZACQl5eH9PR0vPLKKzh16hROnTrV4/PRo0dj0aJFg1o9ZvXQQw9h//792LVrF3JycjBx4kSIooiDBw/CYrFg6tSpWLp0KQBAEAQ8//zzePjhh7F69Wq89957iIuLw4EDB/DNN99g9uzZmD59+qDHREREROQrakHo9ZoTZqLhhtc5EdHAKF4gA648befUqVMwGo24ePEiQkNDMXbsWKSkpHjsOEFBQfjjH/+It956C9u3b0dJSQkEQYDBYMCsWbMwe/ZsCN3+QBk/fjzeffddbNiwAfv378fx48cxZswYLFu2DPfdd5/HxkVERERERERERMrxiwKZ1ZgxYzBmzBivHkOtVmP+/PmYP3++S+1TUlKwYcMGr46JiIiInBMlqceqiN6vB9t+KBiO50Q0lHnjmnTWJzOAiMi7/KZA1tLSArPZDEmSIMuOn66SkJDgw1ERERGRkqybSldUN6GgpNa26fSMrCRkGOL6bDrtbvuhYDieE9FQ5o1r0lGfOTePRdqYKGYAEZEPKF4g+89//oP169fjxIkT/bZVqVQ4cuSID0ZFREREShMlGZa2DuRvKUal0dTjs6KyOqTpdcjLzYY2JAhqQeV2+6FgOJ4T0VDmjWvSUZ+gbHxUAAAgAElEQVQR2iA8eMd3YbZcxpo/72cGEBF5maJrcvfu3Yuf//znqK6uhizL/f4jSZKSwyUiIiIfUgsqu5NQq0qjCflbim2TQnfbDwXD8ZyIhjJvXJOO+sy5ORmjosPsFscGczwiIrJP0RVkr776KmRZRlZWFn7xi18gOTkZISEhSg6JiIiI/IAoSaiobnI4KbSqNJpQXtWI9JRoN9vH+P2E0v3fwP/PiWgo88Y16ahPQVDhjslj8WVlAzOAiMhHFF1BdujQIYSFheFPf/oTbrzxRkRFRUGr1Tr9h4iIiIY/tSCgoKTWpbaFpUaoBQEHjze50d7/J5Hu/wb+f05EQ5k3rklHfepHRSA2MhSFpcwAIiJfUbRAJooixo4di7CwMCWHQURERH7I1NzuVrvLHaJH+/UH7v4GRORd3rgm7bXVhozw2vGIiMg+RQtkycnJqKurU3IIRERE5Kd0ERq32gUHqT3arz9w9zcgIu/yxjVpr62lrdNrxyMiIvsULZDNnTsX33zzDd566y0lh0FERER+RpQkzMhKcqnt9Ew9REnChNQYN9rLgxmeT7j/G/j/ORENZd64Jh31aaxvRuPFVkzPZAYQEfmKopv033fffTh06BCef/55VFdXY8qUKRg1ahSCgoIcficlJcWHIyQiIiIlqAUBGYY4pOl1TjeoTtPrkGGIBQC32/u7gfwGROQ93rgmHfUpSTI+2fc15udcywwgIvIRRQtkEydOBNC1F9m2bduwbds2p+1VKhWOHDnii6ER2XVy7Y9cbnv1qn94cSRERMOfKMnIy81G/pZiu5PDNL0OebnZECUZakHldvuhYDieE9FQ5o1r0lGfH++twW2T9Fj9k5uw5s/7mQFERF6maIHMYrG41V6WuWyYiIgoUKgFFbQhQVi3dArKqxpRWGqEqbkduggNpmfqkWGI7TEpdLf9UDAcz4loKPPGNemszwuX2pE2RssMICLyAUULZMeOHVPy8EREROTnrJO+9JToHrcQWffa6T0pdLf9UDAcz4loKPPGNemsT2YAEZFvKLpJPxEREZEr1ILQ67XzCaG77YeC4XhOREOZN65JZ30yA4iIvMuvCmTnz59HaWkpdu7cCQCQJAlms1nhURERERERERER0XCm6C2WVgUFBdi0aROOHj0K4Mpm/HV1dfjhD3+I+++/H08++SRGjPCL4RIREZEfECWpx4oKSZIgo+cqi95tBtLvQPpQsn8iUk7363kw1/pAvstsISIaHMUrThs3bsSmTZsgyzJUKhXUajVEUQQAnD59GhaLBa+//jqqqqqwefNmqNVqhUdMRERESrLuyVNR3YSCkloIggoL/r9xiIzQoLyqAQUltbZNrGdkJSHDEOfSJta9+x1IH0r2T0TKsV6/ladMSIgJR2SEBoeON6Gw1L1rfSA5wWwhIvIMRQtk+/btw8aNGxEeHo7ly5fjzjvvxKOPPoovv/wSAHDTTTfhhRdewJo1a7B3715s27YNDz74oJJDJiIiIgWJkgxLWwfytxSj0mhChDYIv/vFVKhUwPKXd6PSaOrRvqisDml6HfJys6ENCXI6Ke3e70D6cGfcnu6fiJRjvb5/u7UUS+6dMOA8GkhOMFuIiDxH0TW3f/3rX6FSqfDb3/4Wc+bMwciRI3t8LggCfvjDH2L9+vWQZRkffPCBQiMlIiIif6AWVD0mgjk3J2NUdBjW/Hl/n8mhVaXRhPwtxU4nh737HUgf7ozb0/0TkXKs13eqXjeoPBpITjBbiIg8R9ECWXl5OeLj43HLLbc4bfe9730PCQkJqK6u9tHIiIiIyN+IkoTyqgbbRFAQVLhj8lh8WdngcHJoVWk0obyqEaIk99vvQPpwZ9ye7p+IlGO9vo/XXRxUHg0kJ5gtRESepWiBrKWlBTqdzqW2UVFR6Ozs9PKIiIiIyF+pBQEFJbW21/pREYiNDEVhaa2Tb11RWGp0sGqjZ78D6cMZb/dPRMqxXt+DzaOB5ASzhYjIsxTdgywuLg41NTXo7Ox0+oTKy5cvo6amBrGxsT4cHREREfkbU3O77d/DtUF93nP1u719Y27H2NEjoQ0ZAUtbJ4z1zZDsrLZw9VgD/d435oH1T0TKMTW3QxvSNZfRBKtxXXKU0xyxfseV9/r7bn/fEQQV9KMiMDIs2KW+iYgCmaIFsv/6r//Cu+++iz/96U947LHHHLbbtGkTWlpacOedd/pwdERERORvdBEaRGiDkHNzMu76r2Tbe65+15GnHpyIiLAQ2+vzF1vw0T4jPt5bg2ZLh0t9DPTYAGzndM+U5B7vy5IIlcAneBP5s9HRWowZPRKiJOGx+zJs7zdebMUn+77ukyOA/UwYSJY5+o41U+6crEd0ZJjtfXuZ0vs95g4RBSpFC2SLFi3Chx9+iE2bNuH06dO466670NbWBgD45ptvcOLECbz99tv48MMPodFo8OMf/1jJ4RIREZGCRElCzs1j8eAd38Wo6DB8WdmAEWoVpmcmoaisrt/vT8/UQ5TkHrcZyZIElSBAXV+JhooiiOaLUIdHIix9GubnTMDtk5KwenMxzja1OOzDlXHPyHI8xtExYXjup9mIiwqH5eTBHuMIHz8N2uQJtnESkX8RJQk/+cH1CNGMQHlVAwpKamFqbocuQoPpmUmYn3MtbpukxzOb99lyBOibJf3lRHfW7wKy3e90z5SWkwfRsMt+pgCAShDQeuowzIeYO0REihbIrrrqKmzYsAFPPPEE3n//ffzzn/+0fZadnQ0AkGUZGo0GL774IpKTkx11RURERMOcWhCQNiYKZstlLH95NyqNJsy+1YD5OdciTa9zulF1ml6HDEPPrRpkSYLU3oJzb69F+5njPT4zH94NTUIq4mb/CmsWZeOJ9buREBPepw9Xx51hiLM7xghtEJ77aTZ0GgmnX/ulw3HEz1kFQRPGySqR31GhQ5TwP99mUndFZXVI0+uw+ic34dlFk7Fs/S40Wzrs5pGznOiu53dVfb7jSqaEJk9A/P2/gnS51Wn+MXeIKNAonnbf+973sGPHDjzwwAOIj4+HLMu2f3Q6He655x5s374dd9xxh9JDJSIiIoWpBRXW/Hm/bTL48d4anDvfgtU/uQlpevsP/knT65CXm93nCW4qQbA7ObRqP3McDe88j1HR4Zifc63dPlwlSjLycrP7jDHn5mTERYWj4Z3nnY7j3NtrOUkl8kNqQYX8LcUOi1qVRhPW/Hk/4qPDkDM52WEeAY5zwsred3t/x5VM0SSkQKUe0W/+MXeIKNAouoKstrYWSUlJSExMxDPPPINnnnkGLS0tMJvN0Gq1iIiIUHJ4RERE5EdESUJFdVOPiWizpQPPbN6HZxdNxrqlU/BlVQN2lna/xUmPDEOsnVsrRbSeOuxwcmjVfuY4LDWHcEf29ZCgGvBT4NSCCtqQIKxbOgXlVY0oLDXiG3M77pmSDMvJgy6PI3TM9ZywEvkJe5lkT6XRhPKqBtx3ayrm33mtw9u07eVEf1nW+zspiRHOM0UlYOTE22E5Wc7cISLqRdEC2eLFi9Ha2or33nsPkZGRAICwsDCEhYX1800iIiIKNGpBQEFJbZ/3zza1YNn6XciZnIw7Jo/BsgdutH1mXWnRezKqEtQwHypy6bjmQ0XQJo/HYLesto4hPSW6x+1VDRXujYOI/IOjTLKnsLQWGYa4b7/nuNDuKCccZVnv76gFwWmmBMcmYcTIGFzY+aZL42buEFEgUbRAZjQacdVVV9mKY0RERETOmJrb7b7fbOnAOwVVeG/ncehHRWBCagwW3p3udCIqmi+6dEyxxfnqEHepe63EUGocRDR4jjJpoO2seueEK6tXrd9xlimCRttvm+6YO0QUSBRdKzty5EjbUyuJiIiI+qOL0Dj9XJJkfH32Ei61XO63L3W4a39Bpw6zvx+Qp/jLOIjIff1lkrvtPMFZpkjtln7b9OiLuUNEAUTRAtnPfvYznD59Gi+++CJaW1uVHAoRERH5OVGSMCMryaW20zP1TjfUlyUR4eOnudRX+PhpkCWpz/edvXZG7NaXkuMgIteIva4762tPZlJ/HF3r9t53limXG2vReakJ4elTXTquvdwhIhquFL3Fsr29HRkZGXj99dfx5ptvIjU1FbGxsdBo7P8Ni0qlwvr16308SiIiIvIHakFAhiEOaXqd002x0/S6Hnv32KMS1NAmT4AmIdXpRtWahNQe++/IkgSVIKD11GGYDxVBNF+EOjwS4eOnQZs8wfa5PdbNtSuqm1BQ0vUggTsmj8F/T/DtOIjINfauWV2EBjOykpBhiIMKKo9lkiP2rvXgUWOhm3I/VMHqPhkQOWW282yTJVwq+wxR0x5wO3eIiIY7RQtkL774IlQqFWRZxuXLl/HVV185ba9SDezJUYHu5Nofudz26lX/8MgxZz65wyP9AMCH/+9uj/WlhMH8FkP93ImIPE2UZOTlZiN/S7HdCWmaXoe83GyHT4nrTpYkxM9ZhXNvr7U7SdQkpCJ+zirbBFWWJEjtLXbbmw/vtrUXNGF9ilOiJMPS1tFn3CdPX0TqVd9B3P2r0PB374+DiFzj6JoFgKKyOlvWaENGeCyTerN3rQuh4Yi561HIHe04/eav+2SA5UQZrlr4v06zrf1MNWSx0638IyIKBIoWyJYsWcKiFxEREblMLaigDQnCuqVTUF7ViMJSo21Vx/RMPTIMsS5PRFWCAEEThsQFL8BSc6hrFUaLCeow3bcrscb3mByqBMHhZBIA2s8cx7m31yJxwQt2x21vAt1s6cDqzcVYsyjbJ+MgItc4umatKo0m5G8pxrqlUzyWSb3Zu9ZHTvw+giJH4fRrv7SbAVKrGWfeyEPCg/n9Zoo7+UdEFAgULZD9/Oc/V/LwRERENARZJ5rpKdE9bluy7u/jzkTUOvkLHTOuzy2M3T+XJRGtpw47vR0J6CpOWWoOIXTM9bbvipKEiuomhxPts00teGL9buRMTsb9t16LOC+Ng4hc0981a1VpNKG8qhHpKTEAPJNJVnavdZWAkRNvh+VkudMM6DSdRd2ry5DwyIv9ZhvQf/4REQUKph4RERENSepek7eBTEKtVIK612uhz+fmQ0Uu9WU+VNTj+2pBQEFJrdPvNFs68E5BFTb945DXxkFErnHlmrUqLDXassfTmdT7Wg+OTcKIkTEwV+zq9/tSqxkXP3+n32yzHqu/NkREgcAv0s9isWDr1q3Izc3FrbfeiuzsbADAhQsX8PTTT+Po0aMKj5CIiIgCnWi+6Fq7lr6rTkzN7S5998Kl/tsNZhxE5BpXr1lX2w1E72td0Gjtvu/w+8wAIiK3KHqLJQB89dVX+PnPf46zZ89ClruWIVv3JautrcWOHTvw73//G88++yxmzZql5FCJiIgogKnDI11rF6br854uwv4TugfSbjDjICLXePKaHaje17rUbrH7vsPvMwOIiNyi6AqyxsZG5Obm4syZMxg/fjxWrlyJa665xvZ5TEwMbrrpJnR2dmLVqlUoKytTcLREREQUqGRJRPj4aS61DR8/zbaHD9C1n9GMrCSXvjs9U2/bt8jT4yAi13jymh0oe9f65cZadF5qQnj6VJf6YAYQEblH0QLZ5s2bceHCBcybNw9///vf8fDDD+M73/mO7fPExET89a9/xUMPPQRZlvH6668rN1giIiIKWCpBDW3yBGgSUp220ySkQps8vs8eZBmGOKTpna/mSNPrkGGIdbpv0WDGQUSu8eQ1O1B2r3VZwqWyz6C9OoMZQETkBYomZlFREbRaLZ566imn7Z588kmEh4dzBRkREREpRpYkxM9Z5XBiqklIRfycVXZXbIiSjLzcbIcT7jS9Dnm52S6tRBnMOIjINZ68ZgfK3rV+qexTdJjqET97JTOAiMjDFN2DrL6+HgaDASEhIU7baTQajBkzBpWVlT4aGREREVFPKkGAoAlD4oIXYKk5BPOhIogtJqjDdAgfPw3a5PGQJcnuig21oII2JAjrlk5BeVUjCkuNMDW3QxehwfRMPTIMsRAl2aWVKIMZBxG5xpPX7EA5utYvffEJdFPuZwYQEXmYogWy0NBQNDQ0uNTWZDIhPDzcyyMiIiIicsw64QwdMw7a5PG2960rNZxNSK0T6fSUaGQYYm3vW1eguDPRHsw4iMg1nrxmB6q/a50ZQETkOYom5/XXX4/Gxkbs37/fabt9+/bhzJkzGDdunI9GRkREROSYSlD3eu36/1Kpe7UdzCR7MOMgItd48podKEfXOjOAiMhzFE3QuXPnQpZlrFixAiUlJXbb7Nu3D8uXL4dKpcK9997r4xESEREREREREdFwp+gtlrfeeivuu+8+vPvuu3jooYcQHR0Ni8UCAHj00UdRU1MDo9EIWZaRk5ODnJwcJYdLREREXiBKUo8VGr1f+yNZEnus3Oj9moj8i9I5w8wgIvJ/ihbIAGDNmjW4+uqr8corr6Cpqcn2flFREQBAq9XikUcewZIlSxQaIREREXmDdYPriuomFJTU2jbAnpGVhAxDnNc3wB4I68bXracOd22Mbb4IdXjktxtjT+DG2ER+RumcYWYQEQ0dPiuQFRcXIzExEUlJSX0+W7BgAebNm4cvvvgCJ06cgNlsRmhoKMaOHYvMzEyEhYX5aphERETkA6Ikw9LWgfwtxag0mnp8VlRWhzS9Dnm52dCGBPlNkUyWJEjtLTj39lq0nzne4zPz4d3QJKQifs4qCJowTniJ/IDSOcPMICIaWnyWxCtWrMDixYt7vLdx40Zs374dABAcHIzJkyfjwQcfxKOPPoqHH34YU6dOZXGMiIhoGFILKruTVqtKown5W4r9pjgGdG1+bW+ia9V+5jjOvb2WE10iP6F0zjAziIiGFp+lsclkwogRPResbdy4Ef/4xz98NQQiIiLyA6IkobyqweGk1arSaEJ5VSNESfbRyByTJRGWmoMOJ7pW7WeOw1JzCLIk+WhkRGSP0jnDzCAiGnp8doulTqdDVVUV3nvvPWRmZiI4OBgAcPnyZZw5c8blfhISErw1RCIiIvIBtSCgoKTWpbaFpUZkGGK9PKL+qQQ1zIeKXGprPlQEbfJ47w6IiJxSOmeYGUREQ4/PCmS333473njjDaxevdr2nkqlwuHDhzFjxgyX+lCpVDhy5Ii3hkhEREQ+Ympud/iZIKigHxUBbcgIaIL85ylvovmia+1anK9YISLfcJYzA2nnLtF8EVAJCI5NgqDRQmq34HJjLSD3XC3GzCAi8g8+K5A99dRTsFgs+OSTT2CxWAB0Fbxk2fXlzO60JSIiIv+li9D0eS9CG4Scm5Nx52Q9oiOv7EEqSyJUgncKZaIkQd1t/5/er7tTh0e61Kc6TGf7995j7/7anWMTkfvs5cxg2rkrYuJtiJ25BCNGxtje67zUhEtln+FS2aeQWs0AemYG4N3MIyIix3xWINNoNHj++efx/PPP4/Lly+jo6MCNN96IG264AX/+8599NQwiIiJSmChJmJGVhKKyOtt7o2PC8NxPsxEXFY6WkwfRsKsIovki1OGRCB8/DdrkCZAlyWObWYuSDLWgQkV1EwpKamFqbocuQoMZWUnIMMTZPreSJRHh46fBfHh3v32Hj59mm+C2njoM8yH751J5yoSP937d77GJyH32csaR6Zl6j193siQi/NqbYTlZjgs737ySAelTETXtAURMmIGz29ag03QW4eOnQbRcQsM/10Md9h2vZB4REfXPZwWy7oKDgxEcHIyEhASMGjUKWq1WiWEQERGRAtSCgAxDHNL0OlQaTYjQBuG5n2ZDp5Fw+rVf9tnU2nx4NzQJqYifswqCJmzQE0ZRkmFp67D7dLuisjqk6XXIy82GNiTINmFWCWpokydAk5DqdNNtTUIqtMnjIXW048xfVzk8l7j7VyF6pAZfHKtHs6XD6bGJyH29c8aRNL3O4/uPyZIIqd1i9wmWtjybvRKj565G08evQJs8HheK3kJrzcGebTyUeURE5BpFCmRWhYWFSh6enDi59kdutb96lfefRjrzyR22f//w/93t9eMRuav7f6ODxf/GabgTJRl5udnI31KMCYZYxEWF2y2OWbWfOY5zb69F4oIXBn1staCyWxyzqjSakL+lGOuWTunxvixJiJ+zyu6kF4BtQitLEs6984LTc2n4e9e55ExOxjsFVf0em4jc1z1n7F3v1oK0p1ePqQS1w5wAvs2zd36DxAUvYNS9K9BhqselLz7t28ZDmUdERK5RtEBmdenSJVRVVaGlpaXftlOnTvXBiIiIiMib1IIK2pAgrFs6BZcvd8By8qDTlVlA14TRUnMIoWOuH/CKClGSUFHd5HRFCdBVqCqvakR6Sky3VWQCBE0YEhe8AEvNoa5bJ1tMUIfpvr0lajxkSUTb6Uq0fX2o/3M5eRA5k1Pw3s7jkKQr+6zaOzYRua97zpRXNaKw1Gi7pXl6ph4Zhliv3FrZ+vVh1/Ms6VqcfXstpDaz4zaDyDwiInKdogWyzs5O5Ofn4/3334coiv2251MsiYiIhg/rpDQ4OAgXK4pc+o75UBG0yeMHcUwBBSW1LrUtLDX2ufXKOkkNHTOuxzhkSfr2czWayz5zqX9zxS7E3T0B+lER+PrspX6PTUTus+ZMekp0j2tK/LYo7ekitEpQw+xmngkjHE/JBpt5RETkOkULZBs3bsS7774LoGtfssjISIxw8geEJ4iiiG3btuH999/HyZMnIYoikpKScOedd2LhwoXQaK48xaa0tBTz5s1z2NfMmTOxbt06r46XiIgoEIjmi661a3G+8ssVpub2Qbfr/YS57qs73D0XbUjf//dxdYxE5JreT4j15upMdzNA0Djej9kTmUdERK5RtED2wQcfQKVS4emnn8b8+fOhVnv3ccaiKGLx4sUoKiqCVqvFhAkTMGLECBw8eBAbNmzArl278Ne//hWhoaEAYFutdsMNN+Cqq67q09/EiRO9Ol4iIqJAoQ6PdK1dmG7Qx9JFaPpv5Ea73tw9F0tbp8eOTUTK0ySkQBY7ILVbcLmxFpAlu+2sGSC1Wxz25YnMIyIi1yhaIGtsbIRer8cjjzzik+O9++67KCoqQlpaGrZs2YJRo0YBAC5cuIDFixfjyy+/xB/+8Ac8+eSTAICjR48CAJ566inceOONPhkjERGRvxElqcfqi96vB0uWRISPnwbz4d39tg0fPw2yJA1qD7IZWUkoKqvrt+30TH2f/YlkSeyxeszea5fPJX0qmkwtMNY3u3RsIvI9d/NPlkRE3XLlDpTOS024VPYZLpV9Cqm15z5j4elT0flNY1cRzYHBZh4REblO0QJZbGwsBB+G/fvvvw8A+NWvfmUrjgFAVFQUfv3rX+Puu+/Gv//9b1uB7MiRIxAEAddee63PxkhEROQvrAWaiuomFJTU2ja3npGVhAxDnMcKOCpBDW3yBGgSUp1ubK1JSB30XjxqQUCGIQ5pep3TjfrT9Loe+xVZJ6itpw53bc5vvgh1eOS3m/NPsH3u1rlcPQH/+Ohojw367R2biHzP3fxzmBHpUxE17QFETJiBs9vWoNN0FsCVDLhQ9JbDFWaeyDwiInKdogWynJwcvP766zh27Bi++93vev14Op0OV199NcaP7/sHzdixYwEADQ0NAIDLly/jxIkTuPrqq6HVOt4XgIiIaDgSJRmWtg7kbynuU0gqKqtDml6HvNxsaEOCPFIkkyUJ8XNW4dzba+0WljQJqYifs8ojKylESUZebrbdcwNgOzfrBFiWJEjtLXbHZj682zY2QRMGlSC4dC5x969C/XkzPtpb4/TYROR77uafSxkxeyVGz12N06+tQJBuNOLnrIIkdqLttP1Cuiczj4iIXKNogeyxxx7D559/jsceewz5+fm46aabvLpJ/5/+9CeHn1VUVAAA4uPjAQDHjx9HR0cHEhMT8bvf/Q6fffYZTp8+jZiYGHz/+9/Hz372M4wcOdJrYyUiIlKSWlA5LCABQKXRhPwtxVi3dIpHjqcSBAiaMCQueAGWmkNdKzBaTFCH6b5dpTXeYxNFtaCCNiQI65ZOQXlVIwpLjbbVIdMz9cgwxPYoUKkEwWGxCwDazxzHubfXInHBC26dy/n6i8i6bpTTYxOR77mbfy5lxDu/QeKCF5DwyIsIjopHc0sbNKKMhHl5Xs88IiJyjaIFstDQUCxfvhyPPvooFi5cCLVajfDwcKhU9v+nUKVSYe/evR4fhyzLePnllwEAt99+O4ArG/Tv2rULJSUlyMrKQnx8PCoqKvCXv/wFhYWF2LZtG6Kiojw+HiIiIiWJkoSK6iantyACXZPE8qpGpKfEeOhWy66JYOiYcT1uK5IlqcfnnmAdb3pKdI/bGcVvb3e0fi5LIlpPHXZ6uyTQNQG21BxC6Jjrv73Vsv9zSRsTieuSr+xx2vvYROR77ubfhJQoNzNiHAAgIizEds37IvOIiKh/ihbI9uzZg8WLF0OWZciyjM7OTly86PixyI4KZ4P1v//7vygpKUFMTAwWLlwI4MoG/ZMmTcLLL79sK4RduHABy5Ytw759+5CXl4ff//73/fa/fft22/5n/bEel4go0DE7laMWBBSUON40urvCUqPH98vqvul912vvTRJ7b7bduzilEtQwHypyqS/zoaI++wU5O5f+jk00EMzOwXEn/w5VNyLDEDvgjLiyStV3mUdERI4pWiDbtGkTOjs7cd1112Hu3LlISEhAUFCQT8fw8ssvY/PmzQgODsb69etthbCVK1di/vz5iI2NRXh4uK19VFQUXnzxRdxxxx34v//7PzQ0NCAuLs7pMU6fPo0DBw549TyIiIYbZqeyTM3ttn8XBBX0oyKgDRkBS1snjPXNto3lu7cbrkSz47+869GuxfmKEyJfYHYOniZYDUFQ9XmARu8s7OgUATAjiIiGC0ULZMeOHcPIkSOxdetWhIWF+fTYnZ2dePbZZ/H3v/8dGo0Gv//975GVldo1qT4AACAASURBVGX7PCgoCMnJyXa/O2rUKFx33XUoLS3FkSNH+i2QJSYmYtKkSS6N6+jRo2hu7vu4dyKiQMPs9AxRknqsVOr92tF7uggNIrRByLk5GXdO1iM68sqf0+cvtuCjfUZ8vLcGugiNR8bgiz6ckSWxxyqO7q/V4ZEu9aEO03lsPEQDNVyz01MZYK8fFQAVZNs1/9h9GZh7W6ot5wDYzUJLa9dfEDAjiIiGB0ULZEFBQUhMTPR5caylpQVLly7F559/jpEjR+IPf/hDj+KYK2JiYgAAra2t/badNWsWZs2a5VK/8+fP59/6ERGB2TlY1o3eK6qbUFBSa9sIfkZWEjIMcT32u+reJmqkBkvunYCcm8difk4a4qLC0XLyIBp2FUE0X4Q6PBJh6dMwP2cCbp+UhPOXLjvcVN6VMfR3W6En+nDGugl266nDXZtkf3uOXZtkT4AsiQgfPw3mw7v77St8/DRuqk2KG27ZaS1oHapuQmG3DJielYQbDHEuF8rsZUlywkg8eEcaNMFBsNQc7JEB1pzLydZDpQKiI8P6ZGF4+jTIY693OyMA3kZJROSPFC2Q3XDDDSgpKUFLS4vPimTffPMNFixYgK+++gqjR4/G5s2bYTAY+rRbs2YNzp07h2effRbR0dF9Pq+rqwNw5amXRERE/kKUZFjaOuw+ha2orA5peh3ycrMRqhmBZ17Zhy+rGnu0SYyLwOzpKehsa8Hp137ZZ/Np8+Hd0CSkIu7+VYjTRULloDjmyhi0IUEOC1ye6MMZWZIgtbfYffqc9RxHP5gPbfIEaBJSnW7CrUlI7bP/GBENjihJsLR2Iv9VJxmwMBva0BFOi2T2siRCG4THZ4+H0NGK02+udpgB8XNWQRUcirNvPYvWmoN92sTk/BQjJ97uckZ888WnCL/uZgiaMBbJiIj8jKKp/Nhjj6G9vR3/8z//A4vF4vXjXb58GYsWLcJXX32FlJQUvP3223aLYwDw5Zdf4j//+Q8KCwv7fFZVVYWjR48iMjIS48aN8/awiYiI3KIWVHaLSlaVRhPytxRjhFpAalLfW366bjUS0PD3voUjq/Yzx9Hw97UOJ3iujsFZYcsTfTijEgS7xTGr9jPH0XJkL2RJQvz9v4ImIdVuO01CKuLv/5VtZQgReYZaEOwWx6wqjSbkv1rc7woye1mSc3My4qLC0fDO804z4NzbayGoR0CTkGK3zYWiN9F56Tzi56xynhGzV6LDVA9T0Vs497bj7CQiIuUouoKsvr4e99xzD959913s3bsXN954I0aNGoXQ0FC77VUqFZ566qkBH2/Dhg0oLy/H6NGjsXXrVtuG/Pbcf//9eOaZZ/C73/0OEydOxDXXXAOg6ymWK1euhCiKWLhwIYKDgwc8HiIiIk8TJQkV1U0OJ5RWlUYTvqxqwB2Tx+C9ncdtm1ELggozMq9Cy8mDTldDAF2TR0vNIYSOub7HZM+dMZRXNSI9JaZPkcsTfTgjSyJaTx12fo4qAaHJ6Wirq8SIiCgkLngBlpMHYa7YBbHFBHWYDuHpU6G9egI6TPW4fP4MQhINnPgSeYAoSTjkVgZE2y2U2csSQVDhzsl613Pu5EGMvOE2XNz7PiD3LIRLrWaceSMPVy1c15URNYe6btW0kxFnt62B1GZ2mJ1ERKQsRQtkS5YsgUrV9T+z33zzDQoLC22ve5NleVAFMpPJhK1btwLoehLl888/77DtunXrcN9992HPnj349NNPcffddyMzMxOhoaHYv38/WlpakJOTgx//+McDGgsREZG3qAUBBSW1LrXdWVr7/7N37+FRVff++N+zZ5JJZiYhE8iVJiFpLqLkQgQFWiVCBbG1WusXkR76lXrr8dtqvbRVOGiVqpzzwx7tOT1VrOV7yhcVrEWPFdRzgIAVaMGQm1ICJiRcQi4wIZmZZJLZa//+mMwkk7ntCUkmkPfrefqU2XvNWp+Z55k37sXaa+PR5VcjMyUOJ5o7AQCZKXGYnGBE655yVX1Yq8t9bi0Mp4Zdh5pQkp/kc3wk+ghGI2lhrS4P2iY6KQO6+Ck4v3sz7F9WIL50MeJn3ojkWx/ytHFeaMP58jfQ+dlHMORejdiMK8Kqg4j800oSdo1ABvjLkrBzrmYPkm99CNFJGehtbfQ577Q048Jf/wzzdXdAnzINhgAZIXqsA336yU4iIoqsiE6Q3XbbbQEnxEbawYMH0dPTAwD4/PPP8fnnnwdsu379ekiShJdffhlbtmzB22+/jcOHD0OSJOTm5mLp0qW44447xqx2IiKicFi6HEHPS5IGmSlxiDe6VkGbYgf+c8AQ4/qzbO1QNZZs87+6w9Ll8IxjiNHB3uNEU0uXZ6WamlovWIP34T43yTS81dwBP6NGQnRSBmIyprva2S5AdFvR8ek76Nj/Hoz5s6A1JkC2dcBWdwgQzv52wVe6EFF4QmWZ2nb6aC0kSePJjuHmXHRqNiS9AcJhR2+ba9ItOikDkt4AREW5avn0T5A72yHbOyF6rOhtP43oKVMRnZQx8D5FMC+IiMahiE6QrVu3bszGWrRoEY4ePRrWezQaDZYtW4Zly5aNUlVEREQjzxyn93s8zhCFJfOycfPcTExOGHg4zs9XzML7n57Ajn0NsPe4Jnu0pgRVY2mNvnuYAcBNc7PwyLJir3HOddiwfX8TduxrQJe9z6dWRcjQSFrP69V3z4ZTAMbYKM+xto5u7Dp0EhooWDgrE5MTBrZlcD/NTu1T7YZ+RinW5FolVroIuvgpnuPJt/0EnYf/G1AUxBWVeZ1zdrajs+JjdFZ8FPC7IKLhCZRlwdr5y4Ef/a8S3HljAT7cf3E5l3zLjwfG6bEBigJtrMlzTBEyptx4NwDA2XUOve2nED3lK9DFDTzwy50Zsn1gNRkREY0PEZ0gI3r/xVtHpS0R0UQlC4GFszNQXnHK63jaFCN++cAcJCeaYKuvQuuecsjWDmhNCTAWlmHFkmIsuiYDT7/2V5zrsMFYWAZr7d6Q45mKyqAI4bWPjiJkfL14atBx1mw4gOZ2G26am+2ZGOturHXt3dPf3lRUBmN2MS50deP3fz4CIRQsmTsNdyzIg1bSoLKuFf/3gy9g6XLAHKfHglkZmFmQjL4+Aa1egiyUgPuSKUKGqWjgM+rMaUhbvgZRCSmw11fi/O7NA3UUlsH8te9CEQI9p/4+5Nx8JJYtR1zxQjitFp/vgoiGRxYCC/xkmT8LZmV6JsTcv//qY+3YdeikVz6sWDIdN16TiV+8diDsnBO9PWj/cAMADRIXroDOmAB7Q5V3ZhWWwZBTDKetA30drTBkF0P09uDc//wneltOeGWG6O1hXhARjTOcICMiIrqMaCUJJfnJKMg0ezaljjNE4ZcPzIFZL3B64xM+m1Jba/dCn56H5KWr8Mx912LnoVNY+o1i6NPzgm5grU/P89lDRxECwmH3+3TIweOsvX8Ofv/+F5ielQDhsIVsv3xRPta8uh//cNMVsNp7sfb1v/ps3l1ecQoFmWasuedaWLv7oI/WwhAT5XeSTCNpYch2fcY+SzPSlq+BFBUT9PtJvXMVdHGTYf+yAqLb6nMuZlISL3aJRohWkjBzSJb5U5BpRkl+Ehy9TnR0O6DTSvinV/YFzYdf3Dcn7Jw7X/4G7Mc/w9Qf/As00ATPiqVPQmdKRPMbzyL51ocRf/VNOL3xZxAnrANtlq2GRseHfRERjScRnSCbPn16WO01Gg2++OKLUaqGIqn+ue+G1T5n9TsjMu4tj72nqt3luHpN7WdX43L8foguZbJQ8PR9c/DMawdwtMmCJfOykZxo8ntB5+Y4cwytW5/H1JXroCganL9gR+qy1X4nrgB4LvCGroDQSFLA9wwd56f/cHVY7f/xjmKkTDbi8Zf3BrxgPtpkwdrX/4r1D1+PHfsasGRedsDvSRECqctWw3ZkP6ISUkJ+P2e3uOqIL12Mjk/f8XuOiEaOLASevncOnvndAb+/+YJMM56+bw5koeCTyjP4xjWZqvNBUTRoOWdF8tJVaN36fOCcu3MV+iwt6PzsI8RfvVhdVmx9AVNXroM+Pdfz58G54ThzDGffeo6ZQUQ0zkR0gkxRlNCN+sXFxY1iJURERJcPraSBISYK6x++HpV1bcidGgd7fVXQVRKA66LNXl+N78yfjujoKChCxtSV62BvqHbdRmSzQGs0w1RUBkN2kd9bK7sba9WN01CN2KyrYG9QW1cVinKuwuGjrUFXkwCui+DDda2YNT0FlXVtKMydEmAVmQRJb0RcycIwvp8qxM+8ER37tgGK8POZZnAVGdEI0UoSDLE6T5btOtQ06JbJTJTkJ0EWAkcbz6M4P0l1PlTWtWLxnExsKz+O5YsKguZcn6UFzW+uhXDYEV+6CPb6yrCzwl9uMDOIiMafiE6Qvf/++wHPdXd3o62tDTt37sS7776L7373u3jiiSfGsDoiIqJLl3tCqDB3MrSShNaaclXvs9aUIznHdduke8P82KyrvG6lVIToP+99UaeRtLBWqxun50QtDNlFqttba/bAkFOM6uPtqtrvPnQSjy6/Gjv2n0BJflLAdu7PYFX9/exB8q0PITopA72tjd7nqst9bjkloovj3mi/MHey129Z7s8hrSTh0Bct+P43r8QfPlB3p8mu/nxYecsMtHfY0dDchQI/OWc9sg/t21+F6LEiOjkLuvgpOL97s6oxBmdFoNxgZhARjS8RnSDLy8sL2WbhwoW44oor8MILL2DGjBn41re+NQaVERERXR7cF5eytUNVe9nmu/pi8JMlXa8Dr3ZQO45wOoZVV2+frKq9pcsRVvtw65D0hoDniGjkDX0y7eDXjv7fuft3H4q73UtvVmB3xSlckWXGP//oOrR98Fv0nTsNXUIKkr/9Y3RV/DdEj2u/QfdvfjhZESg3mBlEROPLJbGe93vf+x7MZjM2bdoU6VKIiIguSVpTgrp2RvOYjCPp9GG1d9cVHaUN0dLFHKcPq324dQiHPeA5IhpbqYmuiSf37z4Ud7svT1+AEArsPU4AgOLsRc/JI+htaQDgnQvu3/xwsiJQbjAziIjGl0tigkyr1SItLQ11dXWRLoWIiGjcct9yNPS1ImSYispU9WEqKvPcQhmucMaJmTYjvLoK50N2OlGUO0VV+xtmZaDNYkdRbhJkEXzP03DrcF5oQ2/bSd9zF/HdEZGvQJk29Ngt138VshBYODtDVb/ufGhq6QIANLV04VyHDcbCMgBAb9tJODvbYSqc73mPv2PBDM6KQLnBzCAiGl8uiQkyq9WKEydOICoqKtKlEBERjTvuCaCa4+14cfNn+KdX9uHFzZ+hpn+/LgUSDNnF0KcH39pAn553UfvhhDuORtKqb59TjOr685hZkIyCzOCrLgoyzZiZn4xDR1pQkp/kd4P+wcKto/Pwf3tt0O/9mS6J/7QiGtdCZZosFJ82uw+dQkm++nz4cH8jRH8fQijYvr8Jxpz+HFAEOis+hiGnZCAX/B0LYHBW6NO+6jc3mBlERONPRBO5u7s74P/sdjs6Ojpw+PBh/OM//iPsdjtKSkoiWS4REdG4IwsF9p4+PP7yXqx5dT/KK06h6lgbyitOYc2r+/H4y3th6+mDImSkLlsd8MJOn56H1KVPwtl5DsJhC3tVgywU2Hr6cP6CHclLVwUfZ9lqT/+KECHrSl66Ci3nrPiPP1bh7Dkb1txzbcCL4IJMM9bccy3aO7rx9ZKpIVePuampI/XOVeiztKDzs4+CfiYiGr5QmfbUq/ugKL5tfv9+rap8ePq+OXDKAnVDnna5Y18DWs5ZkXynKwc6Kz5Cn6UFqUuf9OSCv2NDubO0z9KCntPHPH8enBvMDCKi8Smim/SXlpaqaqcoCrRaLe6///5RroiIiOjSopU0eOa1Azja5H+z56NNFjzz2gGsf/h6SHojpq5cB3t9Faw1eyDbLNAazTAVzochpxh9lhY0v7kW2lgTpq5cN6w6Ou29WHv/nADjlMGQUwRFCM+qCY0kDdTVUA1rdflA+6IyGLKLcKGrG298fATTpyXifKcDBVkGrH/4elTWtWHXoSZYuhwwx+lxw6wMzMxPRo/DiUkmPWShhFw95qamDkUI9J47A0Pu1X7PcSUI0cULlWl5mWbotJJPmy57H57asB/P3j8X6x++HofrWrH70ElPPiyYlYmS/IFbrtf+cJ5Phpzr7EWyOcGTA52ffYhJ197ilQuWv2xF4oIV/rOiP0udtg44rRakf+9piN4edO5/F/q0HGYGEdE4F9EJMkVR96+6BQUFeOihhzBr1qxRroiIiOjSIQuBmuPtAS8k3Y42WVBZ14bi3ET0nm9G9OR0JN/6kOe880Ibzpe/gc7PPoLoscJpAewN1YjNmqHqAm5oHY+8tBdL5mZjydxcJN9a7GnXbrHhQrsNyYkGDN463z1GbNZVXrd4KkJACIFJcbF45K7S/rEGJr0KcyejJD9pUB2u/66I6t+YX+3kmJo63OdjpuYhNuMKv+eI6OKEyjRJ0uCmudNw+Gir3zbN7TY8+tIeLJmbjZvmZuHR5VcP6tuVD4NzwV+GaPrPD82Boa/lHhv0qTl+s0JnTIAUHeuaBNNFYfI3/rdPG2YGEdH4E9EJsp07dwY9r9PpEB8fj9jY2DGqiIiI6NKhlSTsPOi7Wbw/1cfbUJKfhI5PtsL6+V8QnZQBSW+AcNhdG0cP2VPLWl2uej+yoXV02fuwdWcd/rj7GDJT4mCI0cHe40RTSxfmz5zqddE6mEbSDnktYegU1+CLW+2QC0z3uXAnxtTUoeYcEV2cUJmWmRKHpIRY/OGDLwK2GZw/370hF9+/+cr+vn1zIVCGAP5+667Xlk/ehu3v+z0b7g9kaTeg0UCKjoFw2BGdko3kb//YZ0xmBhHR+BXRCbKpU6cGPS+EgMS/RIiIiAKydDlUtevtkwEAsrUDUAR6WxuDtpdtwVelqalDCAUnmjtDtiMicguWEYYYXcg2bkIoOHayY8Tqcus5eQQAEPOVgoD/wAAAWuOkER+biIhGV0QnyNz+/Oc/47333sNvf/tb6HQDJf30pz9FfX09Vq5ciW9/+9sRrJCIiGh8MsfpVbWLdt92aEpQ1V5rDP4kuOHWobZdMIqQvVZ3DH1NRJeuYBlh73GGbKO2L3/UZEvybT+B1hDvee3sbEdnxcforPgIotsKAJBiTYibuYhZRUR0iYn4HmSrVq3Cu+++CwBobGzEV7/6Vc/5xsZGHDlyBD//+c9x6NAhPPvss5EqlYiIaNyRhcDC2RkorzgVsu2s6alQhAxTURmstXtDtjcVlaneRDqcOhbMygxr8/zB3BeX3SdqYa0ph2ztgNaU0L/5fzEvPokucaGypKmlC20d3Vgwa2Tzxp113Y21rk333dlSVAZDdrHXvmGOsw1D8mc+EsuWI654IZrfXAsASFu+BlEJKbA3VAXsj7daEhGNPxGdIHvrrbewbds2GAwG/OhHP0JaWprX+Q0bNuDjjz/Gr371K7z99tuYM2cObr755ghVS0RENL5oJQkl+ckoyDQH3ah/Zn4SpmclQJH7YMguhj49D44zxwK216fnqd5/LJw6CjLNXhtih0MRMoTDjrNvPedTu7V2L/TpeUhdthqS3sBJMqJLVKgsEULBh/tPYMWS6SOWN4oQEA5bwGyJzS5G6p2rIHq7g+fP0ieRtvwp1z5kUXqc3vhEiKwycpKMiGiciWgqv/POO9BoNNiwYQN+8IMfwGAweJ1PTEzEsmXL8O///u9QFAVvvPFGhColIiIan2Sh4On75qAg0/8tkQWZZqxeeQ00koSWt/8ZfZYWpC59Evr0PL/t3Rdv7hUTI1nH0/fN8TxJLlwaSev34tTNceYYzr71HCfHiC5xobLkWJMFTlmMWN5oJClotujTc6HR6kLnz9YXEJWQjKhJSTi75XkVWcXJMSKi8SaiK8i+/PJLZGdnY9asWUHbXXPNNcjIyMAXXwR+Yg0REdFEpJU0MMREYf3D16Oyrg27DjXB0uWAOU6PBbMyUZKfBEXIsDdUobuhCs1vrkXaXWswdeU62OurYK3ZA9lmgdZohqlw/qBbFcO7eFNTx8XcWtl9ojboqjfAdeFpb6hGbNZVnCgjukSpzZKRyBtFyOhuDJItGgnxpYtgr68MnT/NX0L0OdBz6u9hZNUMTpQREY0jEZ0gkyQJUVFRqtrGxcWhra1tlCsiIiK69LgvAgtzJ3vdUuRePaGRtLBWlwMAnJZmnN74M8SXLkb8zBuRfOtDnvbOC22wHtkH0/R5o1LHcCbHPPXXlKtqa60uD+v2UCIaf8LJkovJm8HZ6E90UgZ08VNwfvfmkH1FJ2VAitIH7W8wZhUR0fgT0QmyrKws1NXV4ezZs0hNTQ3Yrr29HXV1dcjOzh7D6oiIiC4t2iErEQZfIMrWDs+fRbcVHZ++g45921wXdXoDhMOO3raTiJ02Y9gTZGrqGK7B9QdtZwu8JxERXVrUZMnF5k2wbJH0hpBthtMWYFYREY1HEV3Te9NNN8HpdOKRRx6BxeL/L4muri489thjkGUZixcvHuMKiYiILg9aU4LvQUWgt7URPSePoLe1EVAEtEb/e/pEmt/6/bUbp/UT0fgULFuEwx6yDTQSopOzoDOnerftPx6TeSWMV8xFTOZViE7OAjSuyy9mFRHR+BPRFWTf+9738O677+Lw4cP4xje+gbKyMuTn58NgMKC7uxvHjx9HeXk5Ojs7kZWVhbvvvjuS5RIREY1LshBeqyiGvlaEDFNRGay1e0P2ZSoqgyJE0H1xXHuUaQO+ViOcPhQhw1QYTv3++wo05nDqJyL1QmXUWPD3+wc0MJUsDJgtvW0n4exsh6lwvk8bKdbkulW9dBF08VM8fZpKFkI3KQnxVy+GLm6yz/jOrnPo/OwjxGQXh8xaIiIaWxGdIDMajfjd736Hn//85zh48CA++OADbN++3XNeUVx7CBQXF+Nf//VfYTKZIlUqXabef/HWSJcQMUM/+y2PvRehSohouNybUNccb8fOgyc9m1QvnJ2Bkvxkz3mNpIUhuxj69Lygm0fr0/OC7onjvpjrbqyFtbocsrUDWlMCTEVlMKi82BtOHxpJC0PO8OsPOGbhfBhySqA4+6CJ1vJilWiEqc2o0RQqc2IzroThijmw//2Avzejs+JjJJYt98ofnTkNacvXICohBfb6SpzfvRmytQPx194CQ04JDFkzYG+owvld/88nbyS9EYlly5k3RETjUEQnyAAgPT0dmzZtwuHDh1FeXo6TJ0+io6MDMTExmDZtGq677jrMnTs30mUSERGNK7JQYO/pwzOvHcDRJu9tCsorTqEg04yn75sDQ0wUtJIGihBIXbYaZ996zu8kkz49D6nLVge8aFOEgHDY/L7fWrvX835Jbwx40XcxfShCVln/0FUiKsZc+iScPTZooqKD1k9E6oWbUaNBbeak3PYIzm55Ht0NVT59OM4chyI7PfnTZ2lG2vI1kKJicHrjE55+pVgTopMymDdERJewiE6Qbd68GV/96lcxZ84czJw5EzNnzoxkOTSB1D/33bDa56x+Z5QqGXmR/GwjvQrNvcptJPsdzT6JxpJW0vi98HQ72mTBM68dwPqHrwcAaCQJkt6IqSvXwd5Q7VpJYbNAazT3r6QoCrqiQSNJASenAMBx5hjOvvUcpq5cF7Dmi+lDI2kh6Q0h6ve9VVLVmFtfwNSV63Dhs48w6Wrud0o0EsLNqNEQTuakLX8qaDa687PXchZRCSlek2MAEF+6GFGTknyO+4zHvCEiGrciOkH2yiuvwGq1Ys+ePYiPj49kKURERJcMWQjUHG8PeOHpdrTJgsq6NhTmTum/1dI1+RWbdZXXrYiKEAAQZOWXjO7G2qC3NwKuiz97QzVis2b4XQF2sX24J79865e9zg9rzPoqGHNLA45NROoNN6NG0nAyR002Rk1Kgr2hyrtfjYT40kWw11cyb4iILmERTeMLFy4gOzubk2NERERh0EoSdh48qartrkNNPhee/lZZBaORtLBWl6saz1pd7re/kehjcF/BXg9rzJo90E1KQveJGl6sEl2ki82okTCczFGTjf76jU7KgC5+Cqw1e9SNx7whIhqXIrqCbPr06Th+/DgsFgvMZj7qmIiISK0LVgempcXDEKODvceJppYuAEBmSpzXMUuXY0TGk60d6trZAq8Yka0dgKSDMX82tMZJkG0XYKs7CAin6j7C5VW3RkJ0UgYkvQHCYUdv20lAEV5jKs7eERubaCJTmz0jlVH+aHR6QOOagIpOzkJ0ShYADXpbTqC3tdHn96+WJ1f6MyUmY7r38VDvZ94QEY1LEZ0ge/7553HPPffgrrvuwj333IOSkhIkJSVBr9cHfE9sbOwYVkhERDQ+/fQfShFnjPG8tnf3AlBgiB34O/Rchw3HT3UCcN3ypB20UmHo61C0pgR17YyB/8Er8caViJ6cBo02ynNMkfvQ3fQF2ne8CqelJWQf4dKaEiDFmhBfuhjxpYugi5/iOefsbEdnxcforPjIM6ZGFz1iYxNNZOa4wP89P1jaZAOA0BklhIAChMyxwXsRJn3zh0hcuAIarQ5SlN6rjejtQeehHbjwt/d9Msf3YR/er3XmVCRMzfPJlHBzknlDRDS+RHSC7Cc/+Qk0Gg0aGxvx1FNPhWyv0WjwxRdfjEFlRERE45N7I31ty1G01pQDGgmJC1fAYEyAvaEKrdXlkK0d0JoSYCwsw7UziqEIgaONFuzYdwKWLgfMcXosnJ2BkvxkyEIJeXuTImSYispgrd0bsj5TUZnfzf4VIUOfnAl7fRWsNQM1mgrLYMgpxlfufxlntzyPnhPVAfsIlyJkxJUugnn+MkQlpMBeX4nzuzcPGns+EsuWI654IZxd5+G80IbYaYUjMjbRRCYLgYWzM1BecSpou7QpRvzglhkAgJrj7dh58KQnoxbMzsDM/GRYvmIo+gAAIABJREFUuhzQSkC8UY/KulavNoNzTIICjSShu7HWtdG++3deVAZDdjGctg6c37kJUIQndxLm3Q5TYRmcne1e+40F6sPVRsHkb/xvSNExA5liu4Dk234CU6HKnCycz7whIhqHIjpBduxY8E0sh1IUZZQqISIiGv8UISAcNs9T2aRYE6b+4F+ggcbvk9OstXuhT89D8p2rMTlej8/+3oIuex8AoLziFAoyzXj6vjkwxEQFnCSThQKnU4Ehuxj69LygG1Dr0/O8NrgeqFuGcNj9Pk3OXWPqstVIvXMVWt99yW8fw6GRtIiZWgDRYw36/aTeuQoxkwrQVV2O+JIFIzI20USmlSSU5CejINMccKP+OEMUXnjwa+iTBf7p5b0+7corTmFmfhKeumcOuh1OPB6kzS/uvRaiN0TGLH0S5uuW4vTGn3n99nWmBOjiEgHAK1/99rFsNSS9AYrch9Mbf+HV7sLf/ozEsuXqcjKnmE+xJCIahyL6zxU7d+4M+39EREQTlUaSvC7e4ksXIyohBWe3vhDwgsxx5hhatzyHlMkmLJmb7XXuaJMFz7x2IOgKMq2kwSeVZ6AIgeQ7V0Ofnue3nXsizr0Kw7turd+LzsE1nn3rOUi6KCR/5xG/fQyXRpJwdsvzwcfe8jw0kgTTVV8b0bGJJjJZKHj6vjkoyPR/y/SKJVdi8qRYPPPagYCTaHmZZuh0Ep75XfA2klZFxmx9AVHmFMSXLh44tuV5aLS6/g36JVU5pZG0sH6xz6ddZ8VH6LO0IHXpk0FzMnXpk3B2noPpynnMGyKicSaiK8imTp0ayeGJiIguGYqQ0d1YO3BRppEQX7oI9vrKoKsVANeFnb2+Ckvm5uKPu49BiIEV2UebLKisa0Nh7hSfiTJZCNQcb0dxfhKOnLBg8iQ9pq5c13+b5B7INgu0RjNMhfNhyClGyzkrzrV0oCDL7OlLETK6T9Sqq7GhGrFZV43Y7UY+39kYjk000WklDQwxUVj/8PWorGvDrkNNA7dPzspEYe5kVNa1Bpz4kiQNbpo7DYePBm9z89xM2OqrVOdg/Mwb0bFvG6AIz7HYrBnoblKfFcbcUpzTSJ5N/gFAdFvR/OZapN21xpWTDdWu2zSH5KTo7YHWOIm3VhIRjUMRnSAjIiIidTSSFtbqcs/r6KQM6OKn4Pzuzareb63Zg+Rbi5GZEocTzZ1e53YdakJJfpLPe7SShOpj7SjJT8YfPvgCn/29BUvmZmPJ3Fwk31rsadduseGd7UewfV8DZl+ZgiuzE73rrin36dtvjdXlI3Z7pWfsQd/ZWI5NRPBMlBfmTvbKGPfehzsPngz43syUOCQlxOIPHwTefzgzJQ6TE4xo3VOuqh5XDj6E6KQM11MsAfQ0fg5DTnFYWTG0DzenpRmnN/4M8aWLMemab8Fw60Oec549zvo35ufkGBHR+DNmE2R33HEHNBoNfv3rXyMtLc1zLBwajQZvv/32aJRHREQ07snWDs+fJb3B51jQ99pcKzAMMb5/9Vu6HAHf5+iTPW267H3YurMOf9x9DJkpcTDE6GDvcaKppcuzKs1fX+HWOJIiOTYRuQx90qR74ixY9rizSk2bcH/n7vwEAOF0XHQfg4luKzo+fQeO5uNIu2vgIWTuCTFOjBERjV9jNkFWW1sLjUaDnp4er2Ph0GiCP2WLiIjocqY1JXj+LBx2n2NB32t07QNk73H6nDPH6QO+Tx+l9WkjhOKzCi1YX+HWOJIiOTYRBRcse9xZFaxNT69rAj/c37k7PwFA0ukvug+/7Qzq+iMiovFjzCbIXnjhBQBAUlKSzzEiIqKJThEyNJLW72tFuC4CTUVlsNbuBQD0tp2Es7MdpsL5nmPBmArno91iQ1NLl8+5BbMyPbc8DSYLgaK8KWjr6MaCWRkorzgVcpyhfSlChqmwTF2NRWWuJ15C47XiRBbCZwWKGoqQvb6z0GNzTyCisSILgYWzA+dKU0tXwOyJM0RhybxsfHNeVni/88L5cF5oQ2+b69ZOKdYEU/ENYWfF4D6CtWOmEBFdWsZsguw73/lOwGM9PT3YtWsXbr75Zq/zW7ZsgcPhwG233Yb4+PgxqZOIiGgsuS+guhtrXRs6WzugNSXAVFQGQ3YxFCHQc6oOss0C0/R50KfnuTaSVgQ6Kz5GYtnygWMB6NPzYMgpxjvbj3ht0A8ABZlmv/uPAa7bokryk7Fj3wksmTcNBZnmgJtlB+pLI2lhyClWV2P/HmA1da3YefCkZ0PvhbMzUJKf7HcSLxiNpIUhO7yxiWhsuPMlUK4IoeDD/SewYsl0rzZpU4z45QNzkJxogr2hCrYzNu9sDMCdg+fL3wAUAZ05DekrnoUuLhG9luawsuLCZx95bdAfqB0REV1aIv5PGvv27cP8+fPx2GOPoaWlxevcjh078MILL+Cmm27C/v37I1QhERHR6FCEgHDYcHrjEzj7xrOw1u5F94lqWGv34uwbz+L0xicgeqzQxSXi/O7/hz5LC1KXPgl9eh4AoLPiI59jQ+nT85B852q0nLNi+74Gr3MFmWY8fd8cyEMmzQaThYKvl6SjvaMba+65FgWZ/m9FDNaXImSkLlsdtMbUZauhCBnPb/wb1ry6H+UVp1B1rA3lFaew5tX9ePzlvbD39AWt1R9FCJVjB77YJaKRJwsFTlkEzZVjTRY4nQJP3zsHBZlmxBmi8MsH5sCsVzy52b7jVVU5mLr0SfRZWtD52UeQYk1IX/EsNLoonN74BM5sfEJdH/05ZbpyHjOFiOgyFNGnWFZXV+P++++H0+lEfn4++vr6vM7ffPPN6OnpQWVlJR588EG88847yMnJiVC1REREI0sjSTj71nMBVyw4zhzD2S3PY+rKdTBd+XU0v7kWaXetwdSV62Cvr4K1Zg8sf9mKxAUrXMcaql2r0GwWaI3m/lVoRVCEwLmWDsy+MsWzKmvBrEyU5CeFXJWllTQwxEQhzhCNHocT6x++HofrWrH70EnVfWkkLSS9IUSNMja8W4v9tc1+6zjaZMEzrx3A+oevD/s7lvTGkN8Pb4MiGltaSYN1/3kQd3/rKr+5csOsDMzsXzmq00lY//D1aG63ITnRiNMbn/Dkpui2+s3Gob9zp60Dlr9shSH3aiRc97+gi0v06kdNH+6sYKYQEV2eIjpB9tprr8HpdGLlypX4+c9/7nN+6dKlWLp0KdavX4/f/e53ePXVV/HP//zPEaiUiIhoZClCRndjbdDbeQDXJJm9vgrxM29Ex75tOL3xZ4gvXYz4mTci+daHBvUnEJt1lddtPe4VDBpJQkFWAq7Mvtpzzr0SS80ti+42UVGuC76i3CmYmZ8cVl/u/dR8a5QhhMDfT1jw509PBK3jaJMFlXVtKMydEuatllKAsYXXeSIaG7IQqDnejk+rm1F9vB1L5mbjprlZeHT5QEa1WezYtP0ISvKTcGXOZAihIDUxBvaGKp/cdFqaA2aj7HRCEQI6YwKSb/kxAFfuDO0nWB/ufSCHPomSmUJEdHmJ6ATZZ599hsTERDz++ONB2/3kJz/B22+/jX379o1RZURERKNLI2lhrS5X1dZaswfJtz6E6KQM9LY2ouPTd9CxbxuikzJgvGIezNfd4feCbPCxoZvchzPBNLSPi+lr8IMI3K81AHbsb1T1/l2HmgLumRb+2LyIJYoErSRh50HXJvdd9j5s3VmHP+4+hsyUOBhidLD3ONHU0gUhFLR12FGYO8X9zoC5KbqtfrPxjf+uw4olV3q1DZS/Q/uQ9AboM6Zj8g3f8zsmM4WI6PIS0Qmyrq4uFBQUQKvVBm2n0+mQkZGBo0ePjlFlREREo0+2dqhrZ3NtTi3pDQMHFYHe1kZojZMA3DEK1Y0tS5fD73FJ0nhdNF+w+m9HRJeWob95IRScaO4M2S5obmok18RWjAkKXCtbjTFRfpsG7ac/X6GREDXlK4HbERHRZSWiE2TJyck4efIkZFkOOkkmhMDp06eRkJAwhtURERGNLq1J3d9rWqNrA2vhsAc8N1IUIXutihj6erSY4/Rer+MMUVgyLxs3z83E5ASj57jV1uPzXlkIr1VtQghooETkcxBNREN/g6FeA76/+UCGtvOXm1KsyXVr5NWLoYub7PV7v/2GPL+//2D56+mvdBF08VM8x5kjRESXt4hOkF177bXYtm0bfvvb3+JHP/pRwHYbN26ExWLBN7/5zTGsji7G+y/eGukSxo3hfhe3PPbeCFdCROOJImSYispgrd0bsq2pcD6cF9rQ23bS91xRmetpmNAM67bJgXpcm0p3N9a6Np22dkBrSujfdLp4VDedloXAwtkZKK84BQBIm2LELx+Yg+REE2z1VWjdM6iewjIgpxhdth7IigYJJj2qj7dj18GTkCQNfvCtKzEpzrVP0Vh/DqKJxv1gjprj7dh5cGCD/YWzM1CSn+yZGBt8PjFej/9zR7HXbz6YBbMyPfscShAwFXrnps6chrTlaxCVkALR65pA7z5R49pkP8DvP1j+Du7PXl+J87s3M0eIiCaIiE6Q3X333fjzn/+M3/zmN2hoaMDtt9+OvLw8GAwGdHd34/jx43jvvffwX//1X9DpdLj33nsjWS4REdGI0UhaGLKLoU/PC7pRvz49D4acYpwvfwNQhO+57CLs2NeAr5dMhSEmaliTZIoQEA6b3ydqWmv3Qp+eh9RlqyHpjaNyUaiVJJTkJ6Mg04wz7Vb88oE5MOuF1xPm/NWDaAOeenUfDte1Ic4QhZceuR4GqRenN/4iIp+DaCKRhQJ7Tx+eee0AjjZZvM6VV5xCQaYZT987B44+Gf+y6RC67ANPq08yG7BiyXQUZJp93jtYQabZ84Rce08f/lJ5BkvmDeSmFGtC2vI1kKJi4ew6D42kxenNan7//vN3oL+YkPnDHCEiuvxEdIIsPz8fzz77LJ566il88MEH2L59u08bRVGg0+mwdu1aTJ8+PQJVUjjqn/tuWO1zVr8zSpWMH/xOiCgQRQikLlvtd2IKcE2Apd65Cn2WFnR+9pHPueSlq9Byzoo/bD+CnQdPYv3D1w+rDo0kBawBcD1J8+xbz2HqynXD6l8NWSh4+r45+EvlGSQnmvxenPqrJy/DjMN1bVgyLzus9xHRxdFKGr+TY25Hmyx45ncHsP7h67Fkbja27qzznNuxrwE3XpOJNfdci7Wv/9VvHwWZZjx93xyI/lVqz7x2AGfarSgtmILkpavRuvU5xGYXISohBZ0VHyO+dFFYv39/+RtfuhhRCSnMESKiCSqiE2QAcNttt6G4uBi///3vsWfPHrS2tnrOmc1mfP3rX8c999yDK664IoJVEhERjTyNJEHSGzF15TrYG6pdtwTaLNAazf238hRBEQK9587AkHv1wLnC+TDkFKPlnBVrNhyAtbsPR5ssqKxrQ2HulLBWkSlCRndjbdBVbIDrotDeUI3YrBmjtIpMA0NMFG6akwF7fZW6euqrsGRuLv605zhunpsJm9r3jeLnIJoIZCFQc7w96OovwDVJdriuFTfNzcIfdx+D6L9Vssveh6c27Mez98/F+oevR2VdG3YdavLcorlgVqZn5ZgCBZV1bZ6x1mw4gLX3z8HUlesg+hyw11fBkFsKe31l2L9/r/yt2YNJs7+pPn+YI0REl52IT5ABQHZ2NtauXQsA6O3thcViQWxsLOLj4yNcGRER0ehyX1zFZl0FQ3aR57gihOe80zwNybc+5DnXbrHhne1HsH1fA6zdA7ct7TrUhJL8pDDH18JaXa6qrbW63KvGkeaa2NPCWqOynpo9SL61GNdemYLJCUa07lH5vlH+HESXO60kYedB3z0R/dl96CQeXX41MlPivJ5S2dxuw6Mv7cGDdxRjbmGaV3a59xxzZYLGa6zmdhseeWkvli+6At+6Lgc9jbWu29B3b1ZVz+Dfv7/8VZ0/zBEiosvOuJggGyw6OhopKSmRLoOIiGhMDX0y2uBVCf/f5gpYuhwwxOhg73GiqaXLsxJjMEuXY1hjy9YOde1swVeLjJRw65lk0g/rfUQ0fGrzxt3OEON72dFl78NHBxrx9eKpXseHroIdOlaXvQ+fVJ3Gt67LgejrBXBxv//B+cscISKauLgmmIiIaJy7MnsyAODvjRacaO70OzkGAOY4/bD615oS1LUzmofVf7jCreeC1eH7Po2E6OQsxGRMR3RyFqCRfN5HRMOnNm/c7VInGzAtLR7SkMkvNf3kZyT4vM/e4wQASFHRAEYux8ZbHhIR0dgZdyvIiIiIyEURMjSSFssWFWDZogKc67Bh+/4m7NjX4PVEOLcFszIh929oraZf959NRWWw1u4NWY+pqAyKEJ7VbbIQ0I7w/jth1VM4H+0WG/76RQvOddhgLCyD/csKxJcuRnzpIujip3jaOjvb0VnxMTorPvL5HEQUHlkILJydgfKKUyHbunPpkbuuBgC0dXTjw/0nPDkWKLcG58v3v3kllnwt2+t9TS1dONdhQ0zWDDg722EqnK8uN0oW9t/CrnitHFOE7Do/zDwkIqJLHyfIiIiIxhn3RVd3Y61r435rB7SmBBgLy7BiSTEWXZOBNRsOoLnd5nlPQaY55P5j/vqNK70RpunzoE/PC7oxtT49D4bsInQ7+vDKnyohhIKFszNQkp+salJOLY2khSG7WF09OcV4Z/sROJ0C2/c3YcWSYujv+1fo4hJhr6/E+d2bPd+dqXA+EsuWI750MXTxk0ekVqKJSitJKMlPRkGmOehG/e5c+kvlaXx4oLF/A/4MrFgyHTdek4n/++fPfXLLnSc1x9ux8+DJQRv3D7zvqQ370dxu8/zu3U+xDJUbhivmIDZjOjSSBHt9Faw1A/nqejBKsfr84f5jRESXHU6QERERjSOKEBAOG86+9ZzPBZq1di/06XlIXroKa++fg0de2osuex8KMs14+r45QSeqAvXraKmHPvWrSL1zFc5ued7vRaF7zPMX7NBptbhrUQEefWkPyitOecY2xESN2CSZIgRSl632+x2460ldthqyLKOu/+L8k8OncNeNedDoonB64xMBv7vUZau9VtAR0fDIQsHT983BM68d8DtJVpBpxpp7rsXZczb85o9VngeKuHNjzT3X4vF/mOWVW7JQYO/p89vn4Pc9e/9cPPrSHuzY14BF12Qg8Yq5UJx9QXMjNrsYKbc9EjRfY7OLkXrnKlX5w9VjRESXH06QERERjSMaSQp4YQYAjjPH0Lr1eUxduQ4P3lEMU2w0SvKTQq7iCtSv6Lai+c21SLtrDaauXAd7Q7VrdZnNAq3RDFPhfBhyitFyzoo1G/Yh3hCN9Q9fjyVzs7F1Zx2ONlnwzGsHsP7h60f0O5D0Rv/1FJXBkF2ELlsPnHYn1v5wHirr2mDr7oVOp8PpTcG/u7NvPYepK9eNWK1EE5VW0sAQE4X1D1+Pyro27DrUNGi1VyZK8pNw9pwNT23Y7/W0XQA42mTB2tf/6pMbWkkTcMJt6Pt+cMtVqD7ejnOdvUg2J0AjSVDsna7cqK+CtWaPT44BCJqv3Q1VaHn3X5HynceC5g8nx4iILk+cICMiIhonFCGju7E26K09gGuix95Qja8VzoCAa1Is2ORYqH6dlmac3vgzxJcuRsK8271uHWq32PDO9iPYvq8B1u4+NMOGw3WtuGluFv64+xiEUHC0yYLKujYU5k4ZwVstXRefsVlXedWjCAEhBOKMMZ5jhbmTIUGBvaFK9XcXmzWDF7hEF8n9ey/Mnex1q2RPrxObBuWGP0NzQxYCNcfbg96yOfh9N8zKxDeuyYIsFAAC9oYqtG77lWsPwpk3IvnWhzzvcV5og9xthaP5eMiMsP/9ALpPHkFsxnS/+QOA2UFEdJniBBkREdE4oZG0sFaXq2prrS6HIbsIam4UVNOv6Lai49N34Ow8h+Rv/xgvvVmBL09fQFNLl89TM3cfOolHl1+NzJQ4nGjuBADsOtQUcg+04Rh6K6RGkjB0Cs69kXe43x0RjYyhD+v4jz9WYfdnoTfwH5wbWknCzoMnVY3n/T4NAFfGuXOsY982RCdlQNIbIBx2QCPhK/euh7Vmj6r+rZU7Yci6yuc4J8aIiC5vE26CTJZlvPnmm9i2bRvq6+shyzIyMjJw8803495774Ve7/2o6ZqaGvzmN79BTU0N7HY7cnNz8f3vfx+33HJLhD4BERFdzmRrh7p2tuCrLIbdr/U8AKD5nM0z+TWUpcsBADDE6HyORdJofXdEFJ7znb55IEkaZKbEwRCjg73HiaaWLp/cUJsj/tp5/f4Vgd7WRs/LmIzpvm2CYEYQEU1ME2qCTJZlPPjggygvL4fBYEBxcTF0Oh2qqqrw61//Gnv27MF//ud/IjY2FgDw6aef4oEHHoAQArNnz0ZsbCz279+Pxx9/HMePH8cjjzwS4U9ERESXG60pQV07o3lU+7X3OAO2Mcfpfdq4jw0mC+G1smTo65E2Wt8dEYVncB7EGaKwZF42bpo7DUkJsZ7jbR3dqGs8H/B9avt3C/b7Fw57yDZefTEjiIgmpAk1Qfb222+jvLwcBQUFeO2115CSkgIAOH/+PB588EEcPnwY//Ef/4HHHnsMPT09+OlPfwoA+P3vf485c+YAAJqamrBixQq88soruPHGGzFjxoyIfR4iIrq8KEKGqagM1tq9IduaispUbRQtCwUSBEyFKvstnI92iw1NLV0B29wwKwNtFrtXmwWzMj0PCnD/f83xduw8eNKzcffC2RkoyU8O+UCB4RiN746IwicLgYWzM1BecQppU4xYe/9cpEw24vDRVvzhgy8GbeSfga8VT4XTKfCbP1Zi5S1XYUH/+0IZnDdA6N9/b9tJODvbYSqcz4wgIqKAJlTqb9u2DQCwatUqz+QYACQmJuIXv/gFAOCDDz4AALz33ns4d+4cbrnlFs/kGABkZmbi8ccfBwBs2rRpjConIqKJQCNpYcguhj49L2g7fXoeDNlFqibH7D19+PDASRhyVPabU4wd+5t89h1zK8g0Y2Z+Mj7c3+hpU5BpRkl+kmdyzN7Th8df3os1r+5HecUpVB1rQ3nFKax5dT8ef3kv7D19/Rtrj5yR/u6IaHi0koSS/GTMzE/C2vvnIkavw+Mv78VTG7zz4KkN/Xng6MOdNxbgw/0nMDM/GQWZwVdvDc4bt5C/f0Wgs+JjGHJKmBFERBTQhEp+s9mMnJwcFBX5bsw7bdo0AEBraysA4JNPPgEALFy40KftDTfcAK1Wi717Q/8LFBERUTgUIZC6bHXAizh9eh5Sl632PE0tGK2kwTOvHcCmHV+g5ZwVyUtXhexXyDLqAjxFriDTjDX3XIuz52zYvq/Bc+zp++Z4JrzcYwZ6Et3RJgueee3AiK8gA0b2uyOi4ZOFgtUrr0HKZCPWvv7XoHnw7O/+itTJRiiKBmfP2bDmnmsDTpINzZvBQv3+HWeOQ5GdzAgiIgpoQt1i+corrwQ8V1NTAwBITU0FABw75noEdH5+vk9bk8mE5ORkNDc3o729HVOmTBmFaomIaCLSSBIkvRFTV66DvaEa1upyyDYLtEYzTEVlMGQXqby1UqDmeLvnwnTNhgNYe/8cV7/1VbDW7PHbr4AGa384D5V1bdh1qGnQ7VCZKMlPQkdXD978+ChmX5niOTZwa6X3mIEcbbKgsq4NhblTRnSibKS+OyK6OFpJA+gkVNa1qsqDw3WtWDDrK1izYT9+ce8crH/4+oAZFOgWbXW/f3mgTZAcZEYQEU1ME2qCLBBFUfDyyy8DABYtWgQAaGtrAwAkJfl/ZH1SUpLqCbI//elPnts7Qzly5IjasomILmsTOTvdF2exWVfBkD2w6tm9qkHNxZtWkrDz4EnP6+Z2Gx55aS+WzM3Gkrm5SL612HOuy9bj6Vfbf6wwdzJK8gf+DpSFAiEEEuJi8MhdpZ5jrrE0fscMZtehJq/+R8pIfHdEl7Lxkp3h5MHuQyfx6PKrEaWV8OhLe7Bkbja+fX0OHl1+tafN0LzxJ/TvX+t5HTttBgw5xX7aMCOIiCYqTpAB+NWvfoWDBw9iypQpuPfeewEA3d3dAICYmBi/73Eft9vtIfs/ffo0/va3v41QtUREEwOzc+BibuB1eBduli6H1+suex+27qzDH3cfQ2ZKHAwxOth7nEiM1+OZ++d5tR36tEnXRanGz7HgY6qtbaRd7HdHdKkaT9kZbh4YYnQ40ezKqeOnLF65FM5q01C/f395wIwgIqIJP0H28ssvY8OGDYiOjsZLL72ExMREAIBWq4WiKNBogv9lLFTsUTB16lRcc801quo5cuQIuroCPzmMiGiiYHZePHOc3u9xIRScaO70vM5O/8qojzncdkQUnvGUneHmgb3H6Tk2ycSMICKisTVhJ8icTieeffZZbNmyBXq9Hv/2b/+G2bNne87Hxsais7MTDocDer3vX9A9Pa7bUYxGY8ixbr/9dtx+++2q6lqxYsW4+Vc/IqJIYnZeHFkILJydgfKKUyHbLpiVGXBfn/E+JhF5Gy/ZGU4e3DArA20WO5paBibrmBFERDTWJuRaYpvNhh/+8IfYsmUL4uPj8frrr2P+/PlebZKTkwEM7EU2VKg9yoiIiCJJK0koyU8O+DQ4t4JMM0ryk0bkIjQSYxLR+BROHszMT8aH+xsh+vcZY0YQEVEkTLgJsgsXLmDFihX45JNPkJaWhs2bN3utHHPLy3M9/vnLL7/0OWe1WtHa2orExEQ+wZKIiMYtWSh4+r45AS9QCzLNePq+OZ7Nry/VMYlofFKTB2vuuRZnz9mwfV+D5xgzgoiIImFC3WLZ29uL+++/H59//jlyc3Px+uuvIzU11W/b6667Djt27MD//M//+Kwu27VrF2RZ9jlONFpueey9kG3ef/HWMaiEiC4lWkkDQ0wU1j98PSrr2rDrUBMsXQ6Y4/RYMCsTJflJI34LUyTGJKLxSU0edHT14M2Pj2L2lSnMCCJ3DAeSAAAgAElEQVQiiqgJNUH261//GpWVlUhLS8OmTZs8G/L7s3jxYrz44ovYtm0bvvGNb3gmw06ePIkXX3wRGo0Gd9999xhVTkRENDzui8zC3MkoyR/YFsC9OmM0LkIjMSYRjU/B8kAIgYS4GDxyV6nn2OD3EBERjaUJM0FmsViwadMmAEBiYiKef/75gG3Xr18Pk8mEtWvX4qGHHsIDDzyA2bNnw2g04sCBA+ju7sYjjzyCK664YqzKJyIiuihaSRryevQvQCMxJhGNT/7zQOPnGBERUWRMmAmygwcPep48+fnnn+Pzzz8P2Hb9+vUAgIULF2LTpk34zW9+g6qqKiiKgoKCAtx9991YsmTJmNRNRERERERERESja8JMkC1atAhHjx4N+32lpaV4/fXXR6EiIiKiAYqQoZG0AV9fbF+ABppBKzgGtxmJsUeyfiIiNcLNOn+viYiI3CbMBBkREdF4pAgBjSShu7EW1upyyNYOaE0JMBWVwZBd7Dk/En05bR04v3MToAiYCstgyCmGImQ4WhrQ+bcPhjX2SNZPRKRGqNyR7Z1QhAKdaRK6T9TCWsNsIiKi0DhBRkREFCGKEBAOG86+9RwcZ455nbPW7oU+PQ+py1ZD0htVTVSF7GvpkzBftxSnN/7Mq//opCz0nD4Kp6UlrLFHsn4iIjXU5o421oDmN55Fd0NVwDbMJiIiGox/IxAREUWIRpL8XuS5Oc4cw9m3nlN1Aaeqr60vIMqcgvjSxV79S7ooTLnpgbDHHsn6iYjUUJ07Wh306bnB2zCbiIhoEP6tQEREFAGKkGFvqAp4kefmOHMM9oZqKEKMTF/1VYifeSOgkbz6j828EpB0vu0DjD2S9RMRqXExWee3DbOJiIgG4QQZERFRBGgkLazV5araWqvLQ6zkCqOvmj3QTUpCdFKGd/+6KBjzZ6keeyTrJyJS42KzzqcNs4mIiAbhHmREREQRIls71LWzWdT1pZEQnZQBSW+AcNjR23YSULxXR7j7kvQGn2NaY8JAQ3dfhrgxqZ+ISA2v3AmSef6yzqcvZhMREQ3CCTI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\n",
"text/plain": [
"<Figure size 619.85x540 with 12 Axes>"
]
},
"metadata": {
"image/png": {
"height": 526,
"width": 612
}
},
"output_type": "display_data"
}
],
"source": [
"import seaborn as sns\n",
"sns.set(style=\"ticks\")\n",
"\n",
"sns.pairplot(df, hue=\"kind\", diag_kind=\"hist\");"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In contrast to our previous examples, our data set contains a non-numerical text column `kind`.\n",
"\n",
"<code>sklearn.preprocessing.LabelEncoder</code> is a preprocessor which encodes text values to according numbers:\n",
]
},
{
"cell_type": "code",
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"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>circumference</th>\n",
" <th>length</th>\n",
" <th>kind</th>\n",
" <th>weight</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>25.5</td>\n",
" <td>85.5</td>\n",
" <td>0</td>\n",
" <td>31.2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>22.5</td>\n",
" <td>62.5</td>\n",
" <td>0</td>\n",
" <td>12.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>29.0</td>\n",
" <td>88.0</td>\n",
" <td>0</td>\n",
" <td>34.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>32.5</td>\n",
" <td>85.5</td>\n",
" <td>0</td>\n",
" <td>62.7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>24.5</td>\n",
" <td>74.5</td>\n",
" <td>0</td>\n",
" <td>24.2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" circumference length kind weight\n",
"0 25.5 85.5 0 31.2\n",
"1 22.5 62.5 0 12.4\n",
"2 29.0 88.0 0 34.8\n",
"3 32.5 85.5 0 62.7\n",
"4 24.5 74.5 0 24.2"
]
},
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from sklearn.preprocessing import LabelEncoder\n",
"\n",
"df.iloc[:, 2] = LabelEncoder().fit_transform(df.iloc[:, 2]) \n",
"df.head()"
]
},
{
"cell_type": "code",
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"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>circumference</th>\n",
" <th>length</th>\n",
" <th>kind</th>\n",
" <th>weight</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>95</th>\n",
" <td>19.0</td>\n",
" <td>69.5</td>\n",
" <td>1</td>\n",
" <td>18.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>96</th>\n",
" <td>18.5</td>\n",
" <td>67.0</td>\n",
" <td>1</td>\n",
" <td>18.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>97</th>\n",
" <td>24.5</td>\n",
" <td>67.5</td>\n",
" <td>1</td>\n",
" <td>24.7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98</th>\n",
" <td>21.0</td>\n",
" <td>66.5</td>\n",
" <td>1</td>\n",
" <td>26.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>99</th>\n",
" <td>27.5</td>\n",
" <td>86.5</td>\n",
" <td>1</td>\n",
" <td>43.4</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" circumference length kind weight\n",
"95 19.0 69.5 1 18.8\n",
"96 18.5 67.0 1 18.9\n",
"97 24.5 67.5 1 24.7\n",
"98 21.0 66.5 1 26.0\n",
"99 27.5 86.5 1 43.4"
]
},
"metadata": {},
"output_type": "execute_result"
}
],
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we prepare the data for training and testing:"
]
},
{
"cell_type": "code",
"metadata": {},
"outputs": [],
"source": [
"from sklearn.model_selection import train_test_split\n",
"\n",
"features = df.iloc[:, :-1]\n",
"values = df.iloc[:, -1]\n",
"\n",
"(features_train, features_test, \n",
" values_train, \n",
" values_test) = train_test_split(features, values, random_state=42)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Without further explanation we pick a regression algorithm, more about regrssion algorithms will be discussed later:"
]
},
{
"cell_type": "code",
"metadata": {},
"outputs": [],
"source": [
"from sklearn.kernel_ridge import KernelRidge\n",
"kr = KernelRidge(alpha=.1, kernel=\"rbf\", gamma=.1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<div class=\"alert alert-block alert-info\">\n",
" <i class=\"fa fa-info-circle\"></i> Regression methods in <code>scikit-learn</code> also have <code>fit</code> and <code>predict</code> methods. Thus cross validation, pipelines and hyperparameter-optimization will be available.\n",
" \n",
"</div>"
]
},
{
"cell_type": "code",
"metadata": {},
"outputs": [],
"source": [
"kr.fit(features_train, values_train)\n",
"predicted = kr.predict(features_test)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let us plot how good given and predicted values match on the training data set (sic !)."
]
},
{
"cell_type": "code",
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"metadata": {},
"outputs": [
{
"data": {
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"text/plain": [
"<Figure size 1152x288 with 3 Axes>"
]
},
"metadata": {
"image/png": {
"height": 269,
"width": 947
}
},
"output_type": "display_data"
}
],
"source": [
"def plot_fit_quality(values_test, predicted):\n",
"\n",
" mi, ma = min(values_test), max(values_test)\n",
"\n",
" plt.figure(figsize=(16, 4))\n",
" plt.subplot(1, 3, 1)\n",
"\n",
" sns.scatterplot(values_test, predicted) \n",
"\n",
" plt.plot([mi, ma], [mi, ma], \"k:\")\n",
" plt.xlabel(\"measured\")\n",
" plt.ylabel(\"predicted\");\n",
"\n",
" plt.subplot(1, 3, 2)\n",
"\n",
" sns.scatterplot(values_test, predicted - values_test) \n",
" plt.plot([mi, ma], [0, 0], \"k:\")\n",
" plt.xlabel(\"predicted\")\n",
" plt.ylabel(\"deviation\");\n",
" \n",
" plt.subplot(1, 3, 3)\n",
"\n",
" sns.scatterplot(values_test, (predicted - values_test) / values_test) \n",
" plt.plot([mi, ma], [0, 0], \"k:\")\n",
" plt.xlabel(\"predicted\")\n",
" plt.ylabel(\"rel deviation\");\n",
" \n",
" \n",
"plot_fit_quality(values_test, predicted)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For assessing the quality of the predictions of a regression method, we can use multiple methods which we will discuss later in this script.\n",
"\n",
"For our current example we compute the average absolute difference between given values $y_i$ and predicted values $\\hat{y}_i$:\n",
"\n",
"$$\n",
"\\frac{1}{n} \\left(|y_1 - \\hat{y}_1| + |y_2 - \\hat{y}_2| + ... + |y_n - \\hat{y}_n| \\right)\n",
]
},
{
"cell_type": "code",
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"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"mean absolute error: 5.35144698789554\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"image/png": {
"height": 269,
"width": 383
}
},
"output_type": "display_data"
}
],
"source": [
"import numpy as np\n",
"\n",
"# mean abso.ute error\n",
"\n",
"abs_error = np.abs(predicted - values_test) \n",
"mean_abs_error = np.mean(abs_error)\n",
"\n",
"print(\"mean absolute error:\", mean_abs_error)\n",
"\n",
"sns.distplot(abs_error)\n",
"plt.xlabel(\"absolute error\");"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Metrics / error measures"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"When we used classification metrics (like accuracy, precision, recall, F1) high values indicated good classification performance. \n",
"\n",
"Most regression metrics turn this upside down. E.g. smaller values indicate a better regression model.\n",
"\n",
"The hyperparameter optimization functions from `scikit-learn` select configurations which yield a large score. To make regression functions work in this framework, we have to flip the sign of the error value to achieva a usable score.\n",
"\n",
"E.g.\n",
"\n",
"- an average absolute error of 0.1 is scored as -0.1\n",
"- an average absolute error of 0.2 is scored as -0.2\n",
"\n",
"In this situation the first case would be prefered: higher score indicates lower error.\n",
" \n",
"\n",
"`scikit-learn` offers the following metrics for measuring regression quality:\n",
"\n",
"### 1. Mean absolute error\n",
"\n",
"This is the metric we used before. Taking absolute values before adding up the deviatons assures that deviations with different signs can not cancel out.\n",
"\n",
"<div class=\"alert alert-block alert-warning\">\n",
" <i class=\"fa fa-info-circle\"></i> <strong>mean absolute error</strong> is defined as \n",
"\n",
"$$\n",
"\\frac{1}{n} \\left(|y_1 - \\hat{y}_1| + |y_2 - \\hat{y}_2| + ... + |y_n - \\hat{y}_n| \\right)\n",
"$$\n",
"\n",
"The name of the corresponding score in `scikit-learn` is `neg_mean_absolute_error`.\n",
"\n",
"\n",
"### 2. Mean squared error\n",
"\n",
"Here we replace the absolute difference by its squared difference. Squaring also insures positive differeces.\n",
"<div class=\"alert alert-block alert-warning\">\n",
" <i class=\"fa fa-info-circle\"></i> <strong>mean squared error</strong> is defined as \n",
"\n",
"\n",
"$$\n",
"\\frac{1}{n} \\left((y_1 - \\hat{y}_1)^2 + (y_2 - \\hat{y}_2)^2 + ... + (y_n - \\hat{y}_n)^2 \\right)\n",
"$$\n",
"\n",
"This measure is more sensitive to outliers: A few larger differences contribute more significantly to a larger mean squared error. The name of the corresponding score in `scikit-learn` is `neg_mean_squared_error`.\n",
"\n",
"\n",
"### 3. Median absolute error\n",
"\n",
"<div class=\"alert alert-block alert-warning\">\n",
" <i class=\"fa fa-info-circle\"></i> <strong>median absolute error</strong> is defined as \n",
"\n",
"\n",
"\n",
"\\text{median}\\left(|y_1 - \\hat{y}_1|, |y_2 - \\hat{y}_2|, ..., |y_n - \\hat{y}_n| \\right)\n",
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"This measure is less sensitive to outliers than the metrics we discussed before: A few larger differences will not contribute significantly to a larger error value. The name of the corresponding score in `scikit-learn` is `neg_median_absolute_error`.\n",
"\n",
"### 4. Mean squared log error\n",
"\n",
"The formula for this metric can be found [here](https://scikit-learn.org/stable/modules/model_evaluation.html#mean-squared-log-error). \n",
"\n",
"This metric is recommended when your target values are distributed over a huge range of values, like popoluation numbers. \n",
"The previous error metrics would put a larger weight on large target values. One could consider relative deviations to compensate such effects but relative deviations come with other problems like division by zero.\n",
"\n",
"\n",
"The name is `neg_mean_squared_log_error`\n",
"\n",
"\n",
"### 5. Explained variance and $r^2$-score\n",
"\n",
"Two other scores to mention are *explained variance* and $r^2$-score. For both larger values indicate better regression results.\n",
"\n",
"The formula for [r2 can be found here](https://scikit-learn.org/stable/modules/model_evaluation.html#r2-score), the score takes values in the range $0 .. 1$. The name within `scikit-learn` is `r2`.\n",
"\n",
"The formula for [explained variance](https://scikit-learn.org/stable/modules/model_evaluation.html#explained-variance-score), the score takes values up to $1$. The name within `scikit-learn` is `explained_variance`.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Some algorithms from sklearn\n",
"\n",
"- `sklearn.linear_model.LinearRegression` is a linear regression method, which only works well for target values which can be described as a linear combination of feature values.\n",
"\n",
"\n",
"- `sklearn.kernel_ridge.KernelRidge` is [documented here](https://scikit-learn.org/stable/modules/kernel_ridge.html#kernel-ridge). It combines the kernel trick from SVMs with classical least squares regression.\n",
"\n",
"\n",
"- `sklearn.svm.SVR` is an extension of support vector classification concept to regression, [you find examples here](https://scikit-learn.org/stable/modules/svm.html#svm-regression)\n",
"\n",
"\n",
"- `sklearn.neighbors.KNeighborsRegressor` extends the idea of nearest neighbour classification to regression: Search for similar data points in the learning data set and compute the predicted value from the values from the neighbourhood, e.g. by averaging or by linear interpolation. [Documentation is available here](https://scikit-learn.org/stable/modules/neighbors.html#regression)\n",
"\n",
"\n",
"- `sklearn.tree.DecisionTreeRegressor` expands the concept of decision trees to regression [is documented here](https://scikit-learn.org/stable/modules/tree.html#regression).\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## A full pipeline\n",
"\n",
"Let us now try to find a good regressor using `scikit-learn`s hyper-parameter tuning:"
]
},
{
"cell_type": "code",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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"text/plain": [
"<Figure size 1152x288 with 3 Axes>"
]
},
"metadata": {
"image/png": {
"height": 269,
"width": 947
},
"output_type": "display_data"
}
],
"source": [
"from sklearn.pipeline import make_pipeline\n",
"from sklearn.preprocessing import StandardScaler, PolynomialFeatures\n",
"from sklearn.kernel_ridge import KernelRidge\n",
"from sklearn.linear_model import LinearRegression\n",
"from sklearn.model_selection import cross_val_score\n",
"from sklearn.decomposition import PCA\n",
"\n",
"\n",
"def eval_regression(p):\n",
" score = cross_val_score(p, features, values, scoring=\"neg_median_absolute_error\", cv=4).mean()\n",
" print(\"cross val score:\", score)\n",
" \n",
" predicted = p.fit(features_train, values_train).predict(features_test)\n",
" plot_fit_quality(values_test, predicted)\n",
"\n",
" \n",
"p = make_pipeline(PolynomialFeatures(2), PCA(2), LinearRegression())\n",
"eval_regression(p)"
]
},
{
"cell_type": "code",
"metadata": {},
"outputs": [],
"source": [
"p = make_pipeline(PolynomialFeatures(), PCA(), LinearRegression())\n",
"\n",
"param_grid = {'polynomialfeatures__degree': range(3, 6),\n",
" 'pca__n_components': range(3, 13),\n",
" }"
]
},
{
"cell_type": "code",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'pca__n_components': 12, 'polynomialfeatures__degree': 3}\n",
"image/png": 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DoCKLFy/Whg0b1KVLF3300Udq3759ufN27NghSRo8eHCZsZ49eyooKEhff/218vLyXJoXAAAAuB42u0P5BUWKf327Xnj7K23bd1oHv8vStn2n9cLbXyn+9e3KLyiinAUAwANRzAIAPN6QIUMUHx+vxx9/XO+++678/f2NjgSgHO3bt9fChQu1Zs0aRUZGVjgvPT1dkhQREVHueLt27WS323Xs2DGX5AQAAABuhMVs0pxlu5SWYS13PC3DqjnLdsliNtVyMgAA4GoNjA4AAEBNKywslLe3d6ljf/zjH2Uy8Z9aoC6bMGGCU/POnTsnSQoODi53vPh4dnZ2ledKSkrSunXrnHrf1NRUp+YBAAAAFbHZ7UpJz66wlC2WlmHVgaNZ6hrejIIWAAAPQjELAPAYRUVFmj17to4dO6Z//OMfatDg//2ao5QFPMfly5clST4+PuWOFx/Pz8+v8lyZmZlKTk6uuXAAAABAJSxms7bsOeXU3K17MxQVUf6XEQEAgHuimAUAeISrV69q5MiR+uKLLyRJc+bM0UsvvWRwKgCuYLFYJFX9hQu73V7luVq3bq3o6Gin3jc1NVW5ublOzQUAAAAqYs0trNF5AADAfVDMAgA8QoMGDdS7d++SYjYrK0tXr14ttWoWgGfw9fWVJBUUFJQ7Xny8UaNGVZ4rJiZGMTExTr3vqFGjWF0LAACAGxYY4F31pGrMAwAA7sNsdAAAAGrKH//4Rw0dOlTx8fFaunQppSzgoUJCQiRVvIdsVlaWpIr3oAUAAACMYrPbNahXqFNzB94WJpvd4eJEAACgNlHMAgDcksPhkM1mK3XMbDbr73//u6ZMmcKesoAH69ixoyQpPT29zJjD4dDx48dlsVjUoUOH2o4GAAAAVMpiNisqIkSRYYGVzosMC1RURLAsZv5vCwCAJ6GYBQC4nYKCAk2ePFlz5swpM2Y286sN8HR9+/aVJG3ZsqXM2L59+5STk6Nbb71V/v7+tR0NAAAAqJLN7tCsuD4VlrORYYGaFdeH1bIAAHggnvEIAHArFy9e1PDhw7V//35J0s0336zhw4cbnApAbYqOjlbHjh21c+dOrV69WsOGDZMk5eTklHxhIzY21siIAAAAQIUsZpP8fLy0aHI/HTiapa17M2TNLVRggLcG3hamqIhg2ewOVssCAOCBKGYBAG7F399fLVu2LClmU1JSDE4EoLaZzWbNnz9fo0eP1gsvvKC1a9cqJCREycnJunDhgoYNG6aBAwcaHRMAAACoUHHp2jU8SFERwSXHi1fJUsoCAOCZKGYBAG7FbDbr9ddfV2Zmph588EGNHTvW6EgADNCtWzetWbNGCQkJ2r17t7777ju1bdtWU6dO1cMPP2x0PAAAAMAplmu246GQBQDAs1HMAgDqNIfDIZOp9H9M/fz89D//8z9q0IBfY4AnS0xMrHQ8PDxcCQkJtZQGAAAAAAAAuDHmqqcAAGCMS5cuafz48frXv/5VZoxSFgAAAAAAwLPY7PZKXwOAu+OuNgCgTjpz5oxGjRql1NRUbdmyRR06dFB0dLTRsQAAAAAAAFDDbHaHLGaTUtKztWXPKVlzCxUY4K1BvUIVFRFSMg4A7o5iFgBQJzVu3Ljkz0VFRdq5cyfFLAAAAAAAgIex2R3KLyjSnGW7lJZhLTW2bd9pRYYFalZcH/n5eFHOAnB7PMoYAFAnNWrUSO+++65atmypV199VVOmTDE6EgAAAAAAAGqYxWwqt5QtlpZh1ZxluyhlAXgEVswCAOqsNm3aaMeOHfL19TU6CgAAAADUqtOnT2vlypU6cOCALl26JJvNJofDUe5ck8mkTz/9tJYTAsCNs9ntSknPrrCULZaWYdWBo1nqGt6MghaAW6OYBQAYzmq1avLkyXr66afVq1evUmOUsgAAAADqm5MnT+qRRx7RxYsXKyxjf8lkoqQA4J4sZrO27Dnl1NytezMUFRHs4kQA4FoUswAAQ6Wnp2v06NE6efKkDh48qH//+99q3bq10bEAAAAAwDBvvvmmLly4oGbNmmnEiBFq166dfHx8jI4FAC5hzS2s0XkAUJdRzAIADOXt7a2LFy9KkrKzs7Vt2zaNGDHC4FQAAAAAYJyvvvpKDRo0UGJiotq1a2d0HABwqcAA7xqdBwB1mdnoAACA+i00NFTLly/Xr371K73zzjuUsgAAAADqvYsXLyoiIoJSFoDHs9ntGtQr1Km5A28Lk81e9ePdAaAuY8UsAMBwvXv31q5du9S4cWOjowAAAACA4Vq0aCGr1Wp0DABwOYvZrKiIEEWGBSoto+J/9yLDAtlfFoBHYMUsAKDWnDt3TmPHjlVmZmaZMUpZAAAAAPjZb3/7W/3444/avXu30VEAwOVsdodmxfVRZFhgueORYYGaFdeH1bIAPAIrZgEAtSIlJUWxsbE6c+aMTp8+rfXr18vPz8/oWAAAAABQ50yaNEk7duxQfHy8Zs6cqb59+6pRo0ZGxwIAl7CYTfLz8dKiyf104GiWtu7NkDW3UIEB3hp4W5iiIoJlsztkMZuMjgoAN4xiFgBQK/Ly8pSVlSVJSk1N1c6dO3XXXXcZnAoAAAAA6p4pU6bI399fqampmjJlikwmk/z8/OTl5VXufJPJpC+//LKWUwJAzSkuXbuGB5V6ZHHxKllKWQCewu2L2fXr12v69OkVjj/++OOaMmVKyeuUlBS9+eabSklJUX5+vsLDw/XYY49p6NChtREXAOqt22+/XfPmzdO8efO0dOlS3XnnnUZHAgAAAIA6adu2bSV/djgccjgcysvLq3C+yURhAcAzWMzma17z7xsAz+L2xWxqaqok6Te/+Y2aNm1aZrxTp04lf965c6cmTpwou92uXr16ydfXV1999ZXi4+OVnp5eqsAFANS8kSNH6re//a2aNWtmdBQAAAAAqLPef/99oyMAAADABdy+mP32228lSQsWLFDz5s0rnFdQUKBnn31WkrRy5Ur16dNHkpSRkaFRo0bprbfe0l133aUuXbq4PjQAeLjTp0/rr3/9q15++WX5+vqWGqOUBQAAAIDKRUdHGx0B9ZjNbi+1avHa1wAA4Pq5fTF75MgRNWvWrNJSVpI2bNig8+fPKyYmpqSUlaSwsDDFx8crPj5eiYmJWrhwoasjA4BHS05O1vjx43X+/HkVFhZq6dKlPFYLAAAAAG5ATk6Ovv/+e126dEl+fn5q27atgoKCjI4FD2OzO2Qxm5SSnq0te07JmluowABvDeoVqqiIkJJxAABw/dy6mD116pQuXryo/v37Vzl3x44dkqRBgwaVGRswYIAsFou2b99e4xkBoL45evSozp8/L0n65JNP9M033/A0AgAAAAC4Dl999ZUWL16sQ4cOlRmLjIzU1KlT1a9fPwOSwdPY7A7lFxRpzrJdSsuwlhrbtu+0IsMCNSuuj/x8vChnAQC4AW79DIri/WWDgoL00ksv6a677lLXrl11zz336M0331RhYWHJ3O+++06SFBERUeY8/v7+CgkJUU5OjrKzs2snPAB4qJEjR2rMmDEKCgrS6tWrKWUBAAAA4Dp88MEHGjdunA4ePCiHw1Fy/8rX11cOh0NHjhzRxIkT9d577xkdFR7AYjaVW8oWS8uwas6yXZSyAADcILcuZov3l01KStKmTZsUHh6u7t276+zZs0pISNDo0aNVUFAgScrKypIkBQcHl3uu4uMUswBw42bPnq3NmzezLxIAAAAAXIfDhw9r3rx5cjgceuyxx/R///d/2rNnjz7//HPt27dPn3zyiUaOHClJ+utf/1pyjwy4Hja7XQeOnquwlC2WlmHVgaNZstkdtZQMAADPc0OPMv7hhx9qJESrVq2u6+eKV8zee++9mj9/vvz8/CRJp0+f1pNPPqn9+/dr8eLF+vOf/6zLly9Lknx8fMo9V/Hx/Pz8Kt83KSlJ69atq1ZGAPBE6enp+vDDDzVz5sxS+8h6eXmpZcuWBiYDAAAAAPe1cuVKORwOxcfHa9y4cWXGb7rpJj3//PNq0aKFFi1apMTERC1YsMCApPAEFrNZW/accmru1r0Ziooof+ELAACo2g0Vs+Xt11pdJpPpur/Vl5CQoFOnTiksLEwNGzYsOd6mTRu9/PLL+sMf/qCPPvpIf/rTn2SxWORwOEoVB+Wx2+1Vvm9mZqaSk5OvKzMAeIrPPvtMTzzxhC5evCh/f3/98Y9/NDoSABdISUnRwYMHlZeXJ5vNJoej4m/HP/XUU7WYDAAAwHPt2bNHTZo00dixYyudN3bsWC1fvpz7VLhh1tzCqidVYx4AACjfDRWzld2Y+6WAgAAFBASosLBQ58+fLznepEkTNWhw/RG8vb0VHh5e7linTp3UokULnTlzRidPnpSvr68uXryowsJCeXt7l5lf/MjjRo0aVfm+rVu3dvrxnKmpqcrNzXVqLgC4ky1btujixYuSpDfffFPDhw9XSEiIwakA1JQrV65oypQp2rp1a5Vzi7/8RjELAABQM6xWq2655ZYqFxiYzWaFhoYqLS2tlpLBUwUGlL1feiPzAABA+W6omN23b1+ZY0VFRXryySd18OBBTZgwQQ899FCpx1n+9NNPWrdunRISEtSuXTutWLHiRiJUqlmzZjpz5owuX76skJAQXbx4UVlZWWrTpk2ZuVXtQftLMTExiomJcSrDqFGj+NYiAI80a9YspaWl6eTJk/r/2LvvqKiutQ3gzxl6EaWJgqDoCGo0MSKIxi6xBjFGSdSQWC72XmOMMZZrxXhFSVQwELHEFDCxxQLXEgsqFqIiCtI1KIrKAFJmzveHH3NFigjDDOX5rZW1MntvznlcydLjeWfvNzAwkEVZolomMDAQYWFhAAA7OzvY29uX+OU2IiIiIlK9+vXrl7uF2P3792FsbFzFiag2kysU6ONsixOXU167tndHO8gVIrQkZX9pgIiIiEpWqcJsYU/Xl23evBmRkZHw8fHBoEGDis03aNAAY8aMQbNmzTBp0iRs3LgRCxcufON7y2QyrFmzBk+fPsW3335b4s7blJQXDxONGjVCy5YtERsbi7i4uGKFWZlMhgcPHsDMzAwWFhZvnIWIqC7S0dHB1q1bIZfLy/WlFiKqWf744w8IgoBFixbh008/1XQcIiIiojqlffv2CA8PR2hoKD788MNS14WEhCA9PR29e/dWYzqqbbQkErR3aAhHO1PEJGWUus7RzpT9ZYmIiCpJouoL7tu3D40bNy6xKPuyXr16wc7ODocPH67QfYyMjHDs2DEcOXIEFy9eLDZ/8uRJZGRkwMHBAQ0bNkS3bt0AAMePHy+2Njw8HHK5HD169KhQFiKi2u769esICgoqNm5mZsaiLFEtlZycjMaNG7MoS0RERKQBXl5eEEURS5Yswfbt2yGTyYrMy2QyBAQE4JtvvoEgCPDy8tJQUqot5AoRS7xd4WhnWuK8o50plni7Qq4oX2s7IiIiKlmldsyW5OHDh2jRokW51hoaGiqPEH5TgiDA09MTW7duxfLlyxEYGAgrKysAQFJSEpYtWwYAmDRpEgCgX79+WL9+PUJDQ+Hm5qYswiYnJ2P9+vUQBAGjR4+uUBYiotrswIEDmDlzJnJyctC4cWP069dP05GISA2MjIx4JB4RERGRhri6usLb2xv+/v7w8fHBt99+iyZNmsDIyAgymQypqalQKBQQRRH/+te/0LlzZ01HphpOSyLAUF8HPjO64+rthwi/lISMzFyY1tND7452aO9gySOMiYiIVEDlhVlra2vcuXMHaWlpykJpSeLi4nD79m20bNmywveaPHkyLl26hMjISPTv3x9OTk4AgIiICOTl5WHs2LEYOHAgAMDY2BjLly/H9OnTMWHCBDg7O8PIyAjnz59HTk4OZs2ahVatWlU4CxFRbSSKIn788Ufk5OQAAL788kv07NmTfSaJ6oCOHTvixIkTePz4MczMzDQdh4iIiKjOmTNnDlq0aIHNmzcjJSUFiYmJRebt7OwwefJkDBkyREMJqbYpLLq2k5oXObK4cJcsi7JERESVp/LC7MCBA+Hn54fJkydj48aNxfq5AsCtW7cwY8YMiKJYZp+M19HX10dQUBCCgoKwf/9+REREQFdXF+3bt4eXlxf69u1bZH2fPn0QHBwMPz8/XLt2DaIowtHREaNHj8aAAQMqnIOIqLYSBAFbt27FBx98AIlEgqCgIBZlieqIKVOm4MSJE1i0aBE2btwIXV1dTUciIiIiqnOGDBmCIUOG4O7du0hISEBWVhYMDQ1hb2+P5s2bazoe1VJaEskrn1mQJSIiUhWVF2bHjBmDo0eP4saNG+jfvz/eeecdtGjRAoaGhsjOzkZ0dDSuX78OURTRqVMnjBo1qlL309XVxfjx4zF+/Phyre/QoQO2b99eqXsSEdUlZmZm2LlzJ8zMzNCgQQNNxyEiNUlKSsKwYcOwZ88edO/eHS4uLrCysoKOjk6J6wVBwLx589SckoiIiKhuaN68OQuxRERERLWAyguzxsbGCAoKwooVK3D48GFERkYiMjISgiBAFP//2AstLYwYMQKzZ88u9eUeERGp38WLF/H06VO4ubkVGecLAKK6Z/r06RCEF9+Mf/LkCY4ePar8/CpRFFmYJSIiIqqgkydPAgA6deoEfX39ImNvokePHirN9SbOnj2LLVu2ICYmBvn5+Xjrrbfg7e2N7t27V+h6d+/exZAhQzBx4kRMnjxZxWmJiIiINEflhVkAMDc3x4YNGzBv3jz89ddfSEhIgEwmg4mJCezt7dGrVy/2KiMiqmZ++uknfPHFF9DV1cXvv/+O1q1bazoSEWnQkCFDSi3EEhEREZHqTJgwARKJBAcPHoS9vb1y7E2exQRBwM2bN6sqYplCQkKwcOFC6OrqwtXVFQqFAhEREfD29sayZcvw8ccfv9H1Hj9+jKlTpyI3N7eKEhMRERFpTpUUZgtZW1vD09OzKm9BREQqkJOTg40bNyI/Px/5+fmYN28e9u/fz6IMUR22evVqTUcgIiIiqhOsra0BANra2sXGqru0tDQsWbIE9erVw+7du+Hg4AAAiIqKwpgxY/Dvf/8bPXv2hJWVVbFJODQAACAASURBVLmud/v2bUybNg0JCQlVmJqIiIhIc6q0MCuXy3Hjxg3cvXsXMpkMn376KfLz83H//n3Y2dlV5a2JiOgNGBgYIDAwEIMHD4adnR2+//57FmWJiIiIiIjUIDw8vFxj1dGuXbuQl5eHCRMmKIuyAPD222/D29sbGzZswN69ezF9+vQyr5OTk4Pt27cjICAAOTk5aNKkCVJSUqo6PhEREZHaVVlhdseOHdi2bRsePXqkHPv000+RnJyMDz74AG5ubli5ciWMjY2rKgIREb2BVq1aYc+ePWjVqhWMjIw0HYeIqom8vDyEhITgxIkTiI+PR1ZWFoyMjGBnZ4euXbti+PDhMDQ01HRMIiIiojpLJpMhKSkJbdq0Ufu9T58+DQBwc3MrNufm5oYNGzbg1KlTry3MHj58GJs2bYKlpSXWrVuHW7duYfPmzVWSmYiIiEiTqqQwu2jRIoSEhEAURdSvXx95eXl4/vw5ACA9PR0KhQLHjh1DcnIydu/eDQMDg6qIQUREpTh58iSsrKzQqlWrIuNOTk4aSkRE1VF8fDwmTZqExMREiKKoHE9PT0diYiL++usv7N69G5s3b0bLli01mJSIiIiodmndujWcnJywc+fO16797LPP8ODBA/z1119qSPY/oigiNjYWEokEzZs3LzbfrFkzSCQSxMbGQhTFMk9latCgAaZNm4YxY8bAyMgIt27dqsroRERERBojUfUFjxw5gt9++w2Wlpbw9/dHREQEWrdurZx3cXFBcHAwLC0tcevWLfz444+qjkBERKUQRRH+/v749NNPMWbMGDx+/FjTkYiomnr27BnGjRuHhIQEWFlZYfLkydi8eTMCAwPh6+uLCRMmoGHDhkhMTMSkSZOQmZmp6chEREREtYYoikW+GFeazMxMPHjwAM+ePVNDqqKePn2KvLw8NGjQALq6usXmtbW1YWpqipycHGRlZZV5rd69e2Pq1Kk8vYmIiIhqPZXvmN2zZw8EQcDGjRvx7rvvlrjG2dkZfn5+GD58OA4fPoyJEyeqOgYREZXg3r17WLduHRQKBZKSkvD111/zeCgiKlFgYCDu3buHzp07Y/PmzcVekvXt2xfjx4/H5MmTceHCBezevRsTJkzQUFoiIiKimisuLg6ff/455HJ5kfFr166hc+fOpf6cKIqQyWSQy+WQSqVVHbOYnJwcACjzJDx9fX0AQFZWVpW3MwsJCUFoaGi51kZHR1dpFiIiIqLSqLwwe/PmTdja2pZalC3Url07NG3aFImJiaqOQEREpbCxscGmTZswduxYdOjQAV9//bWmIxFRNXX8+HFoa2tj7dq1pe5cMDIywtq1a9GnTx8cPnyYhVkiIiKiCmjRogXc3Nzw008/KccEQUBBQQEyMjJe+/P6+vqYO3duVUYskURS/oP4yrP7t7JSU1Nx4cKFKr8PERERUWWovDCbm5sLQ0PDcq01NjZGWlqaqiMQEVEZ+vXrh8DAQHTv3l357WUiolclJyfDwcEBlpaWZa6zsrJCy5YtkZSUpKZkRERERLXPvHnzMHDgQAAvipiff/45HBwc8NVXX5X6MxKJBIaGhrCzs6vy3aglKXz/l5ubW+qa58+fF1lblWxsbODi4lKutdHR0WzFQURERBqh8sJs48aNER8fj+zs7DIfumQyGWJjY9G4cWNVRyAiDZErFNB66Ruzr34m9Tt27BicnJxgZmZWZLxv374aSkRENYUgCMjLyyvX2oKCArXsgiAiIiKqrYyMjIoUFZ2dneHo6FjuQqMmGBsbw9DQEBkZGSgoKIC2dtHXjIU7fvX09GBiYlLleYYOHYqhQ4eWa62Xlxd31xIREZFGqLxi0qtXL+Tm5mL16tVlrlu5ciXy8vLQo0cPVUcgIjWTK168jP87Nh3rd0Xiqy1nsX5XJP6OTS8yT+qjUCjw7bffYvTo0ZgwYQLy8/M1HYmIapgWLVrg7t27iI+PL3Pd3bt3ERsbC3t7ezUlIyIiIqr9goODy9wtWx0IggCpVAq5XI6EhIRi8/Hx8VAoFHBwcFB/OCIiIqJqSuU7Zr29vfH777/jl19+QVJSEgYMGICnT58CeNF/Ni4uDj///DMuXboEExMTjB07VtURiEiN5AoR2c/zsdT/PGKSiva+OXE5BY52plji7QpDfR1oSQQNpax7rly5gvXr1wMAzp49C19fX8yZM0fDqYioJhk0aBCuX7+OmTNnYuvWrWjUqFGxNffv38eMGTOU64mIiIhIteRyOdLS0pCTk1PshJKCggLk5eXhwYMHCA8Px8qVK9Wer1u3boiKisLx48chlUqLzB0/fhwAuCmDiIiI6CUqL8yamZnB398fU6ZMwfnz5xEREaGc++ijjwC86JVhamqKTZs2wcrKStURiEiNtCRCiUXZQjFJGVjqfx4+M7qrOdnr1eajl52cnDBv3jysW7cO3bp145dgiOiNjRo1CqGhoYiJiUH//v3RvXt3tGnTBkZGRpDJZIiOjsbJkyeRm5sLR0dHjBo1StORiYiIiGoVf39/+Pv7l7sXqiYKs0OHDkVAQAD8/f3RtWtXtG3bFgDw999/IyAgAPr6+hg5cqRyfVJSEvLz89GwYUPUq1dP7XmJiIiINE3lhVkAeOutt3DgwAHs3bsX4eHhiI2NRVZWFgwMDNC0aVP07NkTI0eOLNbzkIhqFrlCgb9j00styhaKScrA1dsP0U5qUS12zcoVIrQkAv6OTUfYxWRkZObCtJ4e+jjbor1DQ+V8TTdjxgw0btwYH330UbFeP0REr6Orq4ugoCDMnDkTFy5cwNGjR3Hs2DHlfOGOjU6dOmH9+vXQ09PTVFQiIiKiWufo0aPKU5Bex87ODv3796/iRCVr0qQJFixYgGXLluGTTz5Bp06dAAAREREoKCjAmjVrYG5urlw/evRopKamYtWqVeXuB0tERERUm1TZm3pjY2OMGzcO48aNq6pbEJGGaUkkCLuYXK614ZeS0N7BsooTvV5tPXr5+PHj6NGjB3R0dJRjgiDg448/1mAqIqrpzMzMsGPHDly6dAknT55EQkICsrKyYGhoCHt7e/To0QMdO3bUdEwiIiKiWufnn38GALi7u2Pu3LnQ09PDe++9h48++giLFy/GP//8g19//RUBAQFQKBQYP368xrKOGjUK1tbWCAgIwOXLl6Grq4sOHTpg0qRJ6Ny5s8ZyEREREVVHKi/MLly4EPb29uV6IFyxYgViYmIQHBys6hhEpCYZmbkqXVfVavLRyyUpKCjAihUr4O/vjzFjxmDFihWajkREtVDHjh1ZgCUiIiJSo5s3b8LAwADffPMNjIyMAABSqRRnzpyBjo4ObG1tMWvWLBgZGWHDhg348ccfMWXKFI3l7dWrF3r16vXadeHh4eW63rRp0zBt2rTKxiIiIiKqdlTeTDE0NBQnT54s19qIiAhERUWpOgIRqZFpvfIdXVnedVVJrlDg6u0H5T56Wa4Q1ZSs4v744w/4+/sDAAIDA7Fv3z4NJyIiIiJSP7lCUeZnIqKa5tmzZ7C1tVUWZQGgZcuWuHfvHp4+faoc++yzz6Cvr4+wsDBNxCQiIiKiN1SpHbMJCQnKo1VelpqairVr15b6c6Io4t69e7hz5w4sLCwqE4GINEiuUKCPsy1OXE557dreHe003ru1Jh69/Doffvghjh49iv3796Nfv35wc3PTdCQiqoE6d+4MQRCwd+9e2NraKsfehCAIOHv2bFXEIyIqVeHz5d+x6Qi7mIyMzFyY1tNDH2dbtHdoqPHnTyKiijI0NIQgFP39q/A5LS4uDh06dAAA6Ovro1mzZkhMTFR7RiIiIiJ6c5UqzDZt2hTnz59HdHS0ckwQBKSlpSEwMLDMnxXFFzvR3N3dKxOBiDRISyJBe4eGcLQzLXMXqqOdabUpcta0o5dfRxAEbNiwAZ06dcLnn38OiUTlByEQUR2QkZEBQRBQUFBQZOxNvPrikIioqskVIrKf55fYpuLE5RQ42pliibcrDPV1WJwlohrH1tYW8fHxyM7OhqGhIYAX7+FEUUR0dLSyMAsAz58/L/IcR0RERETVV6UKs4IgYNmyZdi1a5dyLDQ0FBYWFujWrVuZP2doaAhHR0cMHTq0MhGISMPkChFLvF1L7dta+EKsuuxWqElHL79KFEWcO3cOXbp0KTJuYGCAMWPGaCgVEdUGO3bsAABYW1sXGyMiqq60JEKpz6DAi/YUS/3Pw2dGdzUnIyKqvK5du+LGjRtYvHgxli5dCmNjY7Rr1w4A8Ntvv2H48OHQ1dVFVFQUEhISYG9vr+HERERERFQelSrMAkDbtm2xatUq5efQ0FA0bdq0yBgR1V5aEgGG+jrwmdEdV28/RPilJOURcr072qG9g2W1KcrWtKOXX5aXl4cvv/wSe/bswZo1a/Dpp59qOhIR1SIuLi7lGiMiqi7kCgX+jk0v89QW4EVx9urth2gntag2z3VEROXx2Wef4eeff8ahQ4cQHh6OiIgItGjRAp06dcKFCxcwdOhQNG/eHGfOnAHwopBLRERERNVfpQuzrwoLC4OeXuk7zR4/fgxTU1Med0dUixS+5GonNS9yZLFcIRaZ17SaePRyIT8/P+zZswcAsGjRIrRp06bI0VVERKq2cOFC2NvbY/z48a9du2LFCsTExCA4OFgNyYiIXjzXhV1MLtfa8EtJ1e7ZjojodczNzfHDDz9g0aJFSE1Nha6uLoAXfx/08vJCbGwsYmNjAQA2NjaYPHmyJuMSERERUTmpvBmhjY0NTE1NsWXLFgwaNAh5eXlF5r/55ht06dIF33//PftfENUyWq/0N60uBdmXFR697GhnWuL8y0cvVycTJ05E27ZtAQCDBw9GmzZtNJyIiGq70NBQnDx5slxrIyIiEBUVVcWJiIiKysjMVek6IqLqpnXr1ggJCcG+ffuUYw4ODjh48CBmzZoFT09PzJ8/H/v27UODBg00mJSIiIiIykvlO2bz8vIwceJEnDt3DgAQHx8PR0dH5fyDBw+QkZEBX19fXL16FVu2bOHuWSJSm5p09PLLDAwM8MMPP+DPP//E2LFj+fsmEalUQkICfv7552LjqampWLt2bak/J4oi7t27hzt37sDCwqIqIxIRFWNar/STmiqyjoioumrcuHGRzxYWFpgwYYKG0hARERFRZai8MBsUFISzZ8/C0tISX331FVq0aFFkfteuXTh79iyWLFmCU6dO4aeffsKIESNUHYOIqFTV/ehlURRx/fp1tGvXrsi4jY0Nxo0bp6FURFSbNW3aFOfPn0d0dLRyTBAEpKWlITAwsMyfFcUXv3e6u7tXaUYiopfJFQr0cbbFicspr13bu6NdtfziHREREREREdU9Ki/M7t+/H9ra2vjhhx/QsmXLYvNaWlro1q0bvvvuOwwdOhS//fYbC7NEpBHV8ejlnJwczJo1C4cPH8bevXvh6uqq6UhEVAcIgoBly5Zh165dyrHQ0FBYWFigW7duZf6coaEhHB0dMXToUHVEJSIC8OI5rr1DQzjamSImKaPUdY52puwvS0TVXufOnSEIAvbu3QtbW1vl2JsQBAFnz56tinhEREREpEIqL8wmJSXB3t6+xKLsy1q1aoWmTZsiNjZW1RGIiGqshQsXYv/+/QAAb29vHDlyBNbW1hpORUR1Qdu2bbFq1Srl59DQUDRt2rTIGBFRdSJXiFji7Yql/udLLM462pliibcrd8sSUbWXkZEBQRBQUFBQZOxNsN0NERERUc2g8sKsvr4+FApFudbq6OjwwZGI6CXz5s3Df//7X6Snp2Pw4MGwtOQODyLSjLCwMOjpsS8jEVVfWhIBhvo68JnRHVdvP0T4pSRkZObCtJ4eene0Q3sHSxZliahG2LFjBwAU+VJu4RgRERER1S4qL8w2a9YMUVFRiIuLK9Zf9mVJSUmIjY1F69atVR2BiKjGsrGxQUBAAG7dugUvLy9NxyGiOszGxuaN1l+6dAkdO3asojRERCUrLLq2k5oXObJYrhCLzBMRVWcuLi7lGiMiIiKimk/lhdnBgwfj2rVrmDZtGjZt2lRicTYpKQlTp06FKIpwd3dXdQQiohpBLpcrj39/mbOzM5ydnTWUiojofxISErBjxw7Exsbi+fPnxU5FkcvlyM3NRXp6OmQyGW7evKn2jPv27cOCBQtKnZ84cSJmzZqlxkREpAlaEskrn1mQJaKabfbs2fDw8EC3bt0geeX3OCIiIiKquVRemP34449x4MABXLlyBe7u7nj77bfh4OAAQ0NDZGdnIy4uDlevXoVcLke7du0wcuRIVUcgIqr2nj17hilTpuDatWs4dOgQmjRpoulIRERFJCUlYfjw4ZDJZBDFFzvPBEFQ/vurNHX0enR0NADgvffeg5mZWbF5ns5CRERENdGhQ4dw+PBhmJqaYtCgQRg8eDDatWun6VhEREREVEkqL8xqa2tj69atWLlyJX7//XdcvXoVV69eLfIiTxAEDBgwAEuXLoWurq6qIxARVWuiKGLs2LE4d+4cAGD06NH4448/YGhoqOFkRET/ExAQgMzMTDRq1Agff/wx9PX1sWbNGnTv3h1ubm74559/cPDgQSQmJqJz584IDAzUSM7CXbqrVq2ClZWVRjIQERERqdrkyZOVz1rBwcHYuXMnmjVrBg8PD7i7u79x2wkiIiIiqh5UXpgFABMTE6xevRqzZs3CqVOnkJSUhCdPnkBfXx/NmjVD165d0bRp06q4NRFRtScIAubPnw9PT0/k5+fDzc0N+vr6mo5FRFTEuXPnIJFIsHXrVjg6OgIAAgMD8fTpU3h6egIAJkyYgAkTJuD8+fM4fvw43Nzc1J7z1q1bsLCwYFGWiIiIapXp06dj+vTpuH79Og4cOIDDhw8jPj4eGzduxMaNG+Hk5AQPDw/0798f9erV03RcIiIiIiqnKinMFrKyssLw4cOr8hZERDWSi4sL1q5dCx0dHXz44YeajkNEVMzDhw9hbW2tLMoCQJs2bXDmzBnk5+dDR0cHenp6WLZsGfr164e9e/eqvTCbnJyMZ8+eoUePHmq9LxEREZG6tG3bFm3btsWCBQtw8eJFHDhwAEeOHMGlS5cQGRmJ5cuXo2fPnhg8eLBGviRHRERERG9GoukARES1XV5eHh4+fFhs3NPTk0VZIqrWTE1Ni3y2s7NDQUEBEhMTi4zZ2dkpe72qU+E9zc3NsXz5crz//vto164d+vXrBz8/P+Tm5qo9ExEREVFVEAQBLi4uWLZsGc6cOYNt27Zh2LBh0NbWxrFjxzB9+nRNRyQiIiKicqjUjtnOnTtDEATs3bsXtra2yrE3IQgCzp49W5kYRETV1qNHjzB+/Hg8e/YM+/btg5GRkaYjERGVi7m5OdLS0oqM2dnZAQBu374NqVSqHDcyMkJqaqpa8wH/6y8bEhKCBg0aoEOHDrCyssL169fh6+uL06dPIygoqMzj4kNCQhAaGlqu+2mi+ExERET0quvXryMiIgKXLl1CdnY2ALA9DhFVKblCAS2JpNTPRERUfpUqzGZkZEAQBBQUFBQZexOCIFQmAhFRtZWXl4chQ4bg7t27AICZM2di69atkPDBlYhqgHfffRcHDx7EoUOHMHDgQACAVCqFKIo4ffq0ckwmkyEhIQFmZmZqz1hYKB0wYABWrlwJQ0NDAEBKSgqmTJmCK1eu4D//+Q+++OKLUq+RmpqKCxcuqCUvERERUUXdvHkTBw8exOHDh3H//n2IogiJRAJXV1d4eHigb9++mo5IRLWQXCFCSyLg79h0hF1MRkZmLkzr6aGPsy3aOzRUzhMRUflVqjC7Y8cOAIC1tXWxMSKiuk5XVxeTJk3CvHnzIAgC2rdvzy+jEFGNMWLECBw4cADz589HeHg4Vq1aBScnJ1hZWWHfvn2wtbVF69atsXPnTuTk5MDJyUntGX19fZGcnAw7Ozvo6uoqx5s0aYLVq1fjww8/xN69ezFnzhzo6OiUeA0bGxu4uLiU637R0dHIzMxUSXYiIiKi14mLi1N+Ua6wlYQoipBKpRg8eDA8PDxgZWWl4ZREVFvJFSKyn+djqf95xCQV3Yx14nIKHO1MscTbFYb6OizOEhG9gUoVZkt6iVXeF1tERHXByJEjkZiYCCcnJ36DmYhqFCcnJ0yfPh2bN2/GsWPH4OPjAwCYNGkSvvnmG2zatAkAlLs1pkyZovaMenp6RY5Uflnr1q3RqFEj3L9/HwkJCWjZsmWJ64YOHYqhQ4eW635eXl7cXUtERERqMXjwYNy5cwfAi+ctCwsLDBo0CB4eHmjTpo2G0xFRXaAlEUosyhaKScrAUv/z8JnRXc3JiIhqtkoVZomI6H9ycnIAAAYGBkXGFy5cqIk4RESVNnnyZPTu3Rvnzp1Tjn3yySeQSCTYvn07UlNTYW9vj+nTp6N9+/YaTFoyCwsL3L9/X/n7MxEREVFNcfv2bejr66NPnz4YPHgwunbtCi0tLU3HIqI6Qq5Q4O/Y9FKLsoVikjJw9fZDtJNacNcsEVE5Vaowu2/fPpWEGDJkiEquQ0SkKffu3cO4ceNga2uLLVu2sI8sEdUarVq1QqtWrYqMeXp6wtPTU0OJXpDJZFizZg2ePn2Kb7/9FtraxR9rU1JSAACNGjVSdzwiIiKiSlm5ciX69u0LY2NjTUchojpISyJB2MXkcq0Nv5SE9g6WVZyIiKj2qFRh9osvvlBJv0QWZomoJnv06BEGDRqEBw8eICoqCv/5z38we/ZsTcciIqrVjIyMcOzYMWRkZODixYvo3LlzkfmTJ08iIyMDDg4OaNiwoYZSEhEREVVMaa0WsrKyYGRkpOY0RFQXZWTmqnQdERG9UKnCbJs2bUoszD558gSpqakAgCZNmsDR0REmJiZ4/vw54uLicPv2bQiCgHfeeQfW1taViUBEpHHm5ub44IMP8MMPP0BbWxsWFhaajkRE9EbWrl0LQRDwr3/9C6ampsqxNyEIAubNm1cV8Uq9n6enJ7Zu3Yrly5cjMDAQVlZWAICkpCQsW7YMwIueuEREREQ11T///IOgoCCcOnUKiYmJEEURN2/eRFpaGubMmYOxY8eid+/emo5JRLWQaT09la4jIqIXKlWYDQkJKTb28OFDeHp6onHjxli9ejU6depUbM2NGzcwe/ZsJCYmYt26dZWJQERULSxZsgTp6en49NNP8d5772k6DhHRG/nhhx8gCAKGDRumLMwWjpWHKIpqL8wCL3rgXrp0CZGRkejfvz+cnJwAABEREcjLy8PYsWMxcOBAtWYiIiIiUpXTp09j9uzZkMlkEEURAJTPZykpKcrnoClTpmDq1KmajEpEtYxcoUAfZ1ucuJzy2rW9O9pBrhDZY5aIqJwqVZgtybfffou0tDSEhIQU60dW6K233sL333+PDz74AOvWrYOvr6+qYxARVZmsrCwYGhoWKVhoa2vj+++/12AqIqKKGzJkCARBQL169YqNVWf6+voICgpCUFAQ9u/fj4iICOjq6qJ9+/bw8vJC3759NR2RiIiIqEKSkpIwffp05OTkYMCAARg0aBC+++47REdHAwCaNWuGDz/8EKGhofDz80Pbtm3Rs2dPzYYmolpDSyJBe4eGcLQzRUxSRqnrHO1M2V+WiOgNqbwwe/LkSUil0lKLsoWaN28OBwcHREREqDoCEVGViY+Px5gxY+Dh4YFZs2ZpOg4RkUqsXr26XGPVka6uLsaPH4/x48drOgoRERGRymzduhU5OTmYOXMmJk6cCODFiSaFzM3NsWrVKrRo0QI+Pj7YvXs3C7NEpFJyhYgl3q5Y6n++xOKso50plni7crcsEdEbUnlh9vnz55DL5eVam52drTyKhYiourtz5w6GDBmCJ0+ewMfHB46Ojjwik4hqrdOnT6Nr167VftcsERERUW105swZ1K9fH97e3mWuGzNmDAICAhAVFaWmZERUV2hJBBjq68BnRndcvf0Q4ZeSkJGZC9N6eujd0Q7tHSxZlCUiqgCVF2abN2+OGzdu4PLly+jQoUOp68LCwpCUlARnZ2dVRyAiqhL29vZo27Yt/vrrL+jp6SEvL0/TkYiIqoy3tzcsLS0xaNAgDB48GG3atNF0JCIiIqI649GjR3B0dISWllaZ67S0tNCkSRPcunVLTcmIqC4pLLq2k5oXObJYrhCLzBMRUflJVH3BTz75BKIoYtKkSdi3b1+xwkVWVhaCg4Mxd+5cCIKAzz//XNURiIiqhLa2NrZs2QJXV1f89ttvGDJkiKYjERFVGWtrazx8+BBBQUH46KOP8MEHH2Dbtm24f/++pqMRERER1XomJia4d+9eudampaWhQYMGVZyIiOoyLYnklc8syBIRVZTKd8wOGzYMZ8+exaFDh7Bw4UIsXrwYNjY2MDQ0RFZWFlJTUyGXyyGKIsaNGwc3NzeV3v/Jkydwd3fHgwcPEBMTU2w+Pj4emzZtQmRkJJ48eQI7Ozt4enpi1KhRkEhUXqcmohosNzcXenp6RcZMTU3x66+/8mhPIqr1wsPDceXKFezfvx9HjhxBbGwsNmzYgP/85z/o2LEjPDw80K9fPxgbG2s6KhEREVGt0759e4SHh+PPP/9E//79S1136NAhPHz4EH369FFjOiIiIiKqqCqpRK5fvx5LliyBtbU18vPzkZCQgJs3byIxMREFBQWQSqXYtGkT5s2bp/J7L126FA8ePChx7tatWxg2bBgOHjwIa2trdOvWDf/88w9WrFiB+fPnqzwLEdVct27dQq9evXD48OFicyzKElFd8e677+Lrr7/G6dOnsX37dnh4eMDQ0BAXLlzAV199ha5du2LmzJn473//C7lcrum4RERERLXG6NGjIYoiFi9ejH379iE3N7fIfEFBAX799VcsWrQIgiBg1KhRGkpKRERERG9C5TtmgRdFixEjRmDEiBFISEhAYmIiMjMzYWJiAnt7e9ja2lbFbXHgwAEcOnSom5Tq4wAAIABJREFUxDlRFDF//nzIZDKsXbsWHh4eAIDHjx9j9OjR2L9/P95//33069evSrIRUc1x/vx5fPbZZ8jKysL06dPx+++/s7ciEdVpEokE7733Ht577z3k5eXhxIkTOHToEE6dOoUjR47gyJEjMDU1xdmzZzUdlYiIiKhWcHZ2xvTp0+Hr64uFCxcqC7AA4O7ujpSUFDx//hyiKGLMmDHo0qWLhhMTERERUXlUSWH2Zc2aNUOzZs2q+jZIS0vDsmXL8O677yIqKqrYro0zZ84gJiYGLi4uyqIsAJiZmeGbb77BiBEjEBwczMIsEcHBwQGWlpbIysqCIAhIS0tjYZaI6P/p6uqib9++aNGiBaRSKX744QdkZ2cjIyND09GIiIiIapXJkydDKpXC19cXsbGxyvE7d+4AAGxsbDB58mR89NFHmopIRERERG+oSguzMTExOHXqFOLj4yGTyeDr64usrCz8+eefcHd3h66ursrutWjRIuTl5WHNmjUYMGBAsfnTp08DQIk9bTt06ABzc3NERkZCJpOxVxpRHWdmZobAwEBMmTIFmzZtQqtWrTQdiYioWoiLi8PBgwdx6NAhJCYmKsednZ2LfPGNiIiIiFSjb9++6Nu3L5KTkxEbGwuZTAYDAwM0a9YMUqlU0/GIiIiI6A1VSWH26dOnWLRoEcLCwgC8OEa48LiV5ORkLFq0CL6+vti2bRscHR0rfb/du3fj9OnTWLx4MZo2bVrimsJvFjo4OJQ4b29vj0ePHiEuLg7vvPNOpTMRUc0hl8uhpaVVZMzBwQFHjhyBRFIlrbiJiGqM5ORkHDp0CAcPHlTuzhBFEc2bN4eHhwfc3d1hbW2t4ZREREREtZutrW2VtQYjIiIiIvVReWE2Ly8PY8eOxY0bN2BoaIjOnTvj77//xsOHDwG8eJFnYmKCtLQ0eHl5Yd++fZV6mZeYmIh169ahc+fOGDVqVKnrHjx4AACwtLQscb5wPD09vcJZiKjmuXLlCqZNm4Zt27YVO66YRVkiqsuCgoJw8OBBXL9+HcCLZzgzMzMMHDgQHh4eaNeunYYTEhERERERERER1SwqL8zu3LkTN27cgLOzMzZu3AgzMzOMHDlSWZht3bo1wsPDMWnSJFy6dAn+/v5YsmRJhe4ll8uxYMECSCQSrFy5UrkrtyQ5OTkAAH19/RLnC8ezs7Nfe9+QkBCEhoaWK2N0dHS51hGR+v3555+YPHkycnNzMWbMGBw6dAjm5uaajkVEVC2sXr0aAKCnp4devXrBw8MD3bt3L3bCABERERFVTuvWrSt9DUEQcPPmTRWkISIiIqKqpPLC7IEDB6CtrQ0fHx+YmZmVuMbY2Bg+Pj5wc3NT9n6tiICAAFy5cgUrVqx47a7bwpeIZRVvAUChULz2vqmpqbhw4UL5gxJRtWRvbw8dHR3k5uZCJpMhMTGRhVkiov/n7OyMwYMHY8CAATA2NtZ0HCIiIqJaSxTFcq8VBKHE9W9yDSIiIiLSHJUXZuPj4yGVSmFlZVXmOisrKzRv3hx3796t0H1u3bqFTZs2oWfPnhg+fPhr1xsYGAAAnj9/XuJ84biRkdFrr2VjYwMXF5dy5YyOjkZmZma51hKRejk6OmLz5s1YvXo1tm/fjmbNmmk6EhFRtREcHKzpCERERER1wv79+4uNKRQKLF++HJGRkfDw8MCwYcPg6OiIevXqITc3F3FxcQgJCcGePXvQo0cP+Pj4aCA5EREREb0plRdmBUFQHhv8OgqFArq6uhW6z4YNG5Cfn4/8/HzMnTu32HUBKMe//PJLNGzYENHR0UhPT0eLFi2KXa/wqOXSetC+bOjQoRg6dGi5cnp5eXF3LVE1IYpisV3z77//Pnr16gVtbZX/dkhEVGvExMTg1KlTiI+Ph0wmg6+vL7KysvDnn3/C3d29ws9zRERERAS0bNmy2FhwcDAiIyOxYMECjB49usicnp4e2rRpgzZt2sDR0RFff/01AgMDMWXKFDUlJiIiIqKKkqj6gvb29khJSUFKSkqZ65KSkhAbG4vmzZtX6D6FvWDPnDmD/fv3F/mn8PiWws/Z2dnKh9zY2Nhi1xJFEXfv3oWWllaJRVsiqvnOnDmDQYMG4dGjR8XmWJQlIirZ06dPMXXqVAwZMgTffvstQkJCcOzYMQBAcnIyFi1ahPfffx8xMTEaTkpERERUu+zZswcWFhbFirKvGj58OBo1aoTQ0FD1BCMiIiKiSlF5Ydbd3R1yuRwLFizAkydPSlzz5MkT5W7WAQMGVOg+wcHBiImJKfGfwn6yhZ+bNGmCbt26AQDCwsKKXevy5ct4/PgxnJyc2EONqBbas2cPRo4ciWvXrmH8+PHIy8vTdCQiomovLy8PY8eOxfHjx2FgYIDevXujYcOGynlRFGFiYoK0tDR4eXnh3r17GkxLREREVLukpqaiUaNG5VprZmaG9PT0Kk5ERERERKqg8sLsyJEj0a5dO0RGRmLgwIGYM2eOcvdsYGAgFi9ejH79+iEqKgpSqRSjRo1SdYQSubi4oGXLljhz5gx+/vln5fjjx4+xdOlSAMCYMWPUkoWI1Mvc3BxyuRwAcPfu3dfu6CciImDnzp24ceMGnJ2dcfz4cfj5+aFJkybK+datWyM8PBzOzs7IzMyEv7+/BtMSERER1S6WlpaIjY3Fs2fPylyXlpaGmJgYNG7cWE3JiIiIiKgyVF6Y1dXVRUBAAHr27InHjx/j4MGDePDgAURRxNq1a/HLL7/g6dOncHZ2xvbt26Gnp6fqCCWSSCRYuXIlDA0NsXjxYnh6emLq1Kno378/YmJi4Onpid69e6slCxGVTP7//aFL+1xRffv2xYIFC/D222/j4MGDFT5CnYioLjlw4AC0tbXh4+MDMzOzEtcYGxvDx8cH2traOH36tJoTEhEREdVevXv3Rk5ODubMmQOZTFbimocPH2LatGmQy+UYNGiQmhMSERERUUVUSWPF+vXrY8uWLbh+/TrCwsIQFxcHmUwGAwMDNG3aFD179oSLi0tV3LpMb7/9Nn755Rf4+voiIiICd+7cQdOmTTF79mwMHz5c7XmI6AW5QoSWRMDfsekIu5iMjMxcmNbTQx9nW7R3aKicr4ypU6fC29sb+vr6KkpNRFS7xcfHQyqVwsrKqsx1VlZWaN68Oe7evaumZERERES13/jx43H06FH89ddf6NOnD3r06AGpVAoDAwNkZ2cjOjoaJ0+eRE5ODhwcHF7bi7aqnT17Flu2bEFMTAzy8/Px1ltvwdvbG927dy/3NeLj47Fp0yZERkbiyZMnsLOzg6enJ0aNGgWJROV7S4iIiIg0QuWF2V27dqFFixZwdXVF27Zt0bZtW1Xf4rVu3rxZ6pxUKoWvr68a0xBRWeQKEdnP87HU/zxikjKKzJ24nAJHO1Ms8XaFob5OuYqzx44dw+7du7Ft2zbo6OgoxwVBYFGWiOgNCIKAnJyccq1VKBTQ1dWt4kT0MrlCAa2XXlC++pmIiIhqNgsLCwQFBeGLL77A1atX8ccff0AQ/vd3YlEUAQC9evXC8uXLYWxsrKmoCAkJwcKFC6GrqwtXV1coFApERETA29sby5Ytw8cff/zaa9y6dQujRo2CTCZDhw4d0K5dO0RERGDFihW4du0afHx81PArISIiIqp6Ki/MbtmyBTKZDCdPnoSJiYmqL09EtYyWRCixKFsoJikDS/3Pw2fG679l+/333+Pf//43RFHE4sWLsXr1alXHJSKqM+zt7XHr1i2kpKQU6S37qqSkJMTGxmrky3h1kTpOmSAiIqLqoVmzZvjpp59w6dIlnD59GgkJCZDJZDAxMYG9vT369OmDt956S6MZ09LSsGTJEtSrVw+7d++Gg4MDACAqKgpjxozBv//9b/Ts2bPMU1hEUcT8+fMhk8mwdu1aeHh4AAAeP36M0aNHY//+/Xj//ffRr18/tfyaiIiIiKqSyguzT58+hVQqZVGWiF5LrlDg79j0UouyhWKSMnD19kO0k1qU+bI5Pz9f+a3hEydO4PHjx6X2RSQiorK5u7vjxo0bWLBgAfz8/NCgQYNia548eYK5c+cCAAYMGKDuiHWOqk+ZICIiopqhY8eO6Nixo6ZjlGjXrl3Iy8vDhAkTlEVZ4EU7MW9vb2zYsAF79+7F9OnTS73GmTNnEBMTAxcXF2VRFgDMzMzwzTffYMSIEQgODmZhloiIiGoFlZ931rp1ayQmJiIjo+xCCxGRlkSCsIvJ5VobfinptS+Zp02bBg8PD7i6uuLgwYMsyhIRVcLIkSPRrl07REZGYuDAgZgzZw5SUlIAAIGBgVi8eDH69euHqKgoSKVSjBo1SsOJa7/ynjKhqaKsXKEo8zMRERHVPqdPnwYAuLm5FZsrHDt16lSFr9GhQweYm5sjMjISMpmssnGJiIiINE7lO2ZXrlyJcePGYcSIERg3bhzat28PS0tL6OnplfozBgYGqo5BRDVERmauytYJgoD169dDS0uLvQ6JiCpJV1cXAQEBWLBgAU6cOIGDBw8q59auXas8ocDZ2Rnr168v81mPKk/Vp0yoNhuPVyYiIqqLRFFEbGwsJBIJmjdvXmy+WbNmkEgkiI2NhSiKRXrkviw2NhYAiuy4fZm9vT0ePXqEuLg4vPPOO6r7BRARERFpgMp3zM6cOROCICAxMRFff/01Bg8ejM6dO6NDhw4l/uPk5KTqCERUg5jWK9+L/FfXhYaGYunSpcXWGRgYsChLRKQi9evXx5YtW/Drr79i0qRJ6Nu3L7p06YLevXtj7Nix2LFjB4KDg9GwYUNNR631VH3KhKoUHq88d+MpLN56Dicup+DanYc4cTkFi7eew9yNp5D9PB9yhaiWPERERKQ+T58+RV5eHho0aFDi38O1tbVhamqKnJwcZGVllXqdBw8eAAAsLS1LnC8cT09PLzNPSEgIvLy8yvVPdHR0eX+ZFbZ+/XrY2NjAxsYG69evLza/dOlS5fyWLVuKzc+fP185v3PnzmLzU6ZMUc6HhoYWm//888+V80ePHi02P2zYMOX82bNni833799fOR8VFVVsvmvXrsr5uLi4YvMdOnRQzv/zzz/F5h0cHJTzJe2GLpyzsbEpNieTyZRzJRX0//nnH+V8hw4dis3HxcUp57t27VpsPioqSjnfv3//YvNnz55Vzg8bNqzY/NGjR5Xzn3/+ebH50NBQ5fyUKVOKze/cuVM5P3/+/GLzW7ZsUc6X9G6M/+/x/z3+v8f/915V2//fq2lUvmP2zp07b7S+cLcFEdU9coUCfZxtceJyymvX9u5oB7lChAARa9aswebNmwG8+ObsZ599VtVRiYjqtLZt26Jt27aajlHnqfKUCVUp7/HKPjO6qy0TERERqUdOTg6Ask/C09fXBwBkZWXB2Ni4zOsUri3tGtnZ2WXmSU1NxYULF8oOTVTLvdpORMF370RE1Y7KC7NhYWGqviQR1VJaEgnaOzSEo51pmUczOtqZor3Di2/IiiKQlJSknNuxYwdGjBgBHR2dKs9LRFRbLVy4sNLXEAQBK1euVEEaKk1FT5moKtX5eGUiIiKqehJJ+Q/iK2tjhpaWFgCUetRxIcVr+tfb2NjAxcWlXHmio6ORmZlZrrVENcHL7UXORt1Tjj94nF1knoiINE8Qq3jLanR0NBITE5GZmQlTU1NIpVI0a9asKm9ZrXh5eeHChQtwcXFBcHCwpuMQVTuFRyCWttvG0c4US7xdYaivo3yAzMnJwdChQ2FhYQE/Pz+YmJioOzYRkcpp8pmhVatWEAShxBdmhS/IXjcnCIJajoTTJE3+Nyosgi7eeu61a5dP6KK2Iuj6XZHlOvmil1MTzB7JFiZERFQ31JV3QZmZmejYsSMsLCxw5syZEtd06dIFjx49wsWLF0v9u/uQIUMQHR2NQ4cOoUWLFsXmZ86cicOHD8PPzw9ubm4qyV5X/htR3VCRd2tERFQ+VfHMoPIds8CLb7Dt2bMH27ZtU/aJeJlUKsX06dPx/vvvV8XtiagG0ZIIMNTXgc+M7rh6+yHCLyUhIzMXpvX00LujHdo7WBb7Vp+BgQF27dqF+vXrK79ZS0REFTdmzJgSxy9fvoxr167BxMQEbm5ucHR0hImJCZ4/f464uDgcOXIEDx8+RM+ePdGzZ0/1hq5jKnLKhDpUx+OViYiISD2MjY1haGiIjIwMFBQUQFu76GvGgoICZGRkQE9Pr8wvVDds2BDR0dFIT08vsTD78OFDAKX3oCWq69hehIioZlF5YVYURcyePRtHjhyBKIowMDBA06ZNYWRkBJlMhoSEBNy5cwfTp0/HuHHjMHfuXFVHIKIaprDo2k5qXuRlslwhIjg4GBKJBKNGjSryM2ZmZmrNSERUmy1YsKDYWFRUFIKDg+Hq6oqNGzeifv36xdbMmTMHs2bNwqlTp+Dl5aWOqHWaXCFiibfra78Jr85jyqrb8cpEREQ1UWGP1coqq9drVRAEAVKpFFFRUUhISIBUKi0yHx8fD4VCAQcHhzKv07JlS5w8eRKxsbHo1KlTkTlRFHH37l1oaWmVWLStjeQKBbReOib61c9EL2N7ESKimkflhdlff/0Vf/75J4yNjfHll1/C3d29SO/HvLw8/P7771i9ejW2b98OZ2dn9OjRQ9UxiKgGevkvGvn5+ViyZAl+/PFHaGtrw97eHl26dNFgOiKiumXjxo3Q0tLCt99+W2JRFnjx8m/t2rXo0aMH/Pz88N5776k5Zd1SkVMmqpJcoUAfZ9tyHWXcu6Md+1oRERGVokOHDpW+hiAIuHnzpgrSvJlu3bohKioKx48fL1aYPX78OAC89r1ft27dEBAQgLCwsGJfyr58+TIeP34MFxcXGBsbqzZ8NfNyj9Cwi8nK57w+zrZo79CQz1JUIi2JBGEXk8u1NvxSklpP1yEiopKpvDD7008/QRAE+Pn5FfuWGwDo6upi+PDhsLKywvjx47Fjxw4WZomomIKCAly+fFn575s3b2ZhlohIja5evYqWLVu+9oQCExMTtGjRotb3l60uyjpl4uV59WSpnscrExER1TSiKFaLa1TE0KFDERAQAH9/f3Tt2hVt27YFAPz9998ICAiAvr4+Ro4cqVyflJSE/Px8NGzYEPXq1QMAuLi4oGXLljhz5gx+/vlneHp6AgAeP36MpUuXAii99UZtUVaP0BOXU9gjlMrE9iJERDWLyguz8fHxsLe3L7Eo+7Lu3bujadOmuH79uqojEFEtYGBggO3bt2PQoEFwdXXFhg0bNB2JiKhO0dXVVfbzKotcLsf9+/dhZGSkhlRU6NXj7DT1gq46Hq9MRERU04SFhWk6QoU1adIECxYswLJly/DJJ58o3wdGRESgoKAAa9asgbm5uXL96NGjkZqailWrVmHo0KEAAIlEgpUrV+Lzzz/H4sWL8euvv6Jhw4a4cOECnj59Ck9PT/Tu3Vsjvz51YY9Qqgy2FyEiqllUXpjV09ODpJx9DwwMDJCRUfb590RUd9nY2ODgwYOwtraGIPBlLhGROr311ls4c+YMdu/eXWSXw6u+++47PHr0CP3791djOqouqtvxykRERDWRjY2NpiNUyqhRo2BtbY2AgABcvnwZurq66NChAyZNmoTOnTuX6xpvv/02fvnlF/j6+iIiIgJ37txB06ZNMXv2bAwfPryKfwWq9aY9YtkjlCqD7UWIiGoelRdmu3TpgkOHDiEyMhJOTk6lrktISMDt27fh5uam6ghEVMOIoogtW7agffv2xf7SVtP/gkpEVFN5e3vjzJkzWLFiBa5fvw53d3dIpVIYGBggOzsb0dHR+PXXX3H8+HHo6elh4sSJmo5MGlKdjlcmIiKqrR49eoT4+HhkZmaiV69eUCgUyM7OrjZ9V3v16oVevXq9dl14eHipc1KpFL6+vqqMpVYV7RHLHqFUGWwvQkRU86i8MLtgwQJERkZiypQpWL16NXr27Flsze3btzFjxgzUq1cP8+bNU3UEIqpBnj9/jvnz5+O3336DqakpDh06BDs7O03HIiKq8zp16oSvvvoKK1euRGhoKEJDQ4utEUURBgYGWLt2LVq1aqWBlFSdVJfjlan6eNMdQ0REVFxYWBj8/PwQHR0NABAEATdv3kRKSgqGDBmCjz/+GHPmzIG2tspf8dEbKKtHbOStNHgNaIP3O9kBEF76mf/9uViRHqH8c5YKsb0IEVHNovKntu+++w5t2rRBeHg4Jk2aBGtra7Rt2xb169dHTk4O4uLilA+TlpaWmDVrVrFrCIKAX375RdXRiKgaysjIwKlTp5T/vnnzZqxdu1bDqYiICHhxLF2nTp2wfft2/PXXX0V6zjZu3Bh9+vTBuHHj0LhxYw2mJKLqpqI7hoiIqKjNmzfDz88PoihCEARoaWlBLpcDAFJTU5GdnY2goCDcvn0b27Ztg5aWloYT112l9YhtbGGE5eM7w8rcCFdiHiD8Usl/Ltpbm+DanYelXP1/Xu4Ryj9nqRDbixAR1SwqL8z+9NNPyl6QoigiNTUVqampJa598OABHjx4UGycvSSJ6o7GjRsjICAAw4cPx7Bhw7BixQpNRyIiopdIpVKsWrUKAJCTk4PMzEzUr18fenp6r/lJIqqLytoxdOJyinLHhqG+Dl8OEhGV4dy5c9i8eTOMjY0xd+5cDBw4EBMnTsSVK1cAvDjdZPXq1Vi+fDnOnj2LPXv24NNPP9Vw6rqptB6x9Qx1sHx8Z+jraWPuxlNl/rk4ql8rhF1MQmZ2fpn36t3RDgVyBb70+wvRifxzlv6H7UWIiGoOlRdmC1/cERGVV8eOHXH06FFIpVJ+MYOIqBozMDCAgYGBpmMQUTVW2o6hQjFJGVjqfx4+M7qrORkRUc3y448/QhAErFu3rsTerRKJBEOGDIG5uTm8vb3xxx9/sDCrIaX1iB3QxR5W5kYlFmULvfzn4v+xd+fxUVf3/sffM0N2goaQsMRE0JDY2kjYQQVksYItckVrXS7ugMoPcwW0t1ZEROtC6EM2L7JUhVKvS6HYgkslBpA1GAOIMSEWTAICCQQM2SDznd8f3BkzSSaZrJOZvJ6Ph48H8z1nvnMmjMzJ+Zzz+Uwa9zO9/rf9Ll/HXiP0ox2HawRla7sf2ifKiwBA29fsgdlbb721uW8JwEcYhqHFixdr4sSJio6Odmrr3bu3h0YFAACA5uDqxFB1WblFysguUEJsFxYLAcCFjIwMdevWrdagbFXDhg1Tjx49lJOT00ojQ22q14g1m00aO7Snvso66fb34o2DL9fne/NqDbraT8KWV1Rq9aZMt+7H9ywAAG1TswdmAaA2586d0+OPP65PPvlE//jHP7RhwwaFhIR4elgAAABoJq5ODNUmZW+uU5o9AICzkpIS9ejRw62+nTt3VmFhYQuPCHWpWvtVkmK6hiri0iCt3viNW8+3fy+++njdNULf+udBnSurO91x1fsBAIC2h8AsgFZx6NAhpaSkSJIyMzO1atUqPf744x4eFQAAAJpT9RNDTe0HAO1VZGSkDh8+rMrKSnXo4Hr57vz58zp8+LAiIgjCeYrVMDR6YLRS0/Md14IDL/6dNeZ7sa4aoYeP/djg+wEAgLbFXH8XAGi6vn376pVXXpEkTZkyRdOmTfPwiAAAANDcqp8Yamo/AGivrrvuOpWXl2vZsmV19lu6dKlKSkp07bXXttLIUJ3FbFZiXKTiY8Ic10rLKyU17nuxrhqhfM8CAOD9CMwCaDW//e1vtXHjRs2ZM0cWi8XTwwEAAEAzsp8YcseoATGOE0AAgJqmTJmiwMBALV26VL///e/1xRdfqLy8XJJ09uxZpaen66mnntLy5csVEBCgBx980MMjbt+shk1zJg9xBGdzTxSr4EyZRg1ovu9FvmcBAPANBGYBNLvKykotWbJEJSUlNdoSExM9MCIAAAC0tNpODNUmPiZMiXERTieAAADOLrvsMi1atEghISFav369Jk+erMzMTEnSkCFDdM899+jDDz+Uv7+/XnnlFfXq1cvDI27fLGaTggP9lJw0XPOmXqsRfaO0L7tAfeOb73uR71kAAHwDgVkAzaqoqEj33HOPXnrpJSUlJckwDE8PCQAAAK2k+omh6uJjwjRn8hBO8QCAG4YNG6YNGzbo7rvvVrdu3WSz2Rz/hYWF6dZbb9W6des0duxYTw8V+inlcEJsuGbc3V9jBsU0+/ci37MAAHi/Dp4eAADfsnXrVn3xxReSpI8++kj/+Mc/NGHCBA+PCgAAAK2h6omhjOwCpezNVVFxhcJCAzRqQIwS4yJkNWyc4gGAeuTl5Sk6OlpRUVF69tln9eyzz6qkpETnzp1TcHCwQkNDPT1EuFC1Rmxzfy825/2shuE01uqPAQBAyyAwC6BZTZgwQenp6Vq5cqVmzZqlW265xdNDAgAAQCuqemIoMS7Ccd1+eoegLADU77HHHlNZWZk++OADXXrppZKkkJAQhYSEeHhkaKjm/l5s6v3sgdsDOYXanJbnCOyOHhitxLhINlABANDCCMwCaLD6dlXOnj1bY8eO1dChQz0xPAAAALQB1U/dsMgLAO7Lzc3VZZdd5gjKwvs19/diY+5nNWwqLb+guSt2KSu3yKktNT3fkQo5ONCP720AAFoI+SkAuM2++/JATqEWrP1S/70kVZOmzdO+7JNO7R06dCAoCwAAAABAI3Xq1Enl5eWeHgZ8jMVsqjUoa5eVW6S5K3YRlAUAoAURmAXgFvuuylkLt2r2Gzv1r+0HtW75M0r5+zJNfny2Zi3cqtLyC47gLAAAAAAAaJxHH31UR48e1SuvvKKysjJPDwc+wGoYysg+6TIoa5eVW6SM7ALWdwAAaCGkMgbgluq7Kgtytqnk1GFJ0vGDm5Te4xeau0JKThruyWECAAAAAOD1KioqlJiYqLfeektr165V7969FRERoYCAgFr7m0wmvfbaa608SngTi9mszWl5bvVN2ZvrVL+d6XtZAAAgAElEQVQWAAA0HwKzAOplNQwdyCl02lXZ/epxKin8t4pPZumyxNsU3Plyx67KhNgupL0BAAAAAKCRXnnlFZlMJtlsNp0/f14HDx6ss7/JxO/gqF9RcUWz9gMAAA1HYBZAvWrbVWkyW9TruodVVpSn0K7xjuvsqgQAAAAAoGmmTZtGsBXNLiy09hPXje0HAAAajsAsgHqVlJQofXeq5BfrdL2Df7BTUFZiVyUAAAAAAE01ffp0Tw8BPsZqGBo9MFqp6fn19h01IEZWw0Y2NAAAWoDZ0wMA0Lbl5eVpwoQJSv3bn1SU91W9/dlVCQAAAAAA0LZYzGYlxkUqPiaszn7xMWFKjIsgKAsAQAshMAugTi+99JIyMzMlSd/velvny87U2d++qxIAAAAAAABth9Wwac7kIS6Ds/ExYZozeQjrOgAAtCBSGQOo04svvqh9+/bp6NGj6jv6flUGXeqyr31XJQAAAAAAANoWi9mk4EA/JScNV0Z2gVL25qqouEJhoQEaNSBGiXERbqUwthqGLGazy8cAAMA1ArMA6hQWFqa33npLp04X6eqERM1dsUtZuUU1+lXdVUm6GwAAAAAAgLbHvmaTEBvutLnefkq2rjUd+5rPgZxCbU7LcwR1Rw+MVmJcJGtCAAC4gcAsAIczZ84oMzNTQ4cOdbreu3dv9dbFCXhTd1UCANDcduzYoWXLlikrK0sXLlzQ1VdfrcmTJ2v48OGeHhoAAADQJlU/4Vr/KVmbSssv1LphPzU937FhPzjQj7UhN3DqGADaLwKzACRJOTk5uu+++3TixAlt2LBBV199dY0+TdtVyYQTAND81q1bp9///vfy9/fXkCFDZBiGdu/ercmTJ+v555/Xb3/7W08PEQAAAPB6FrPJZRY1ScrKLdLcFbuUnMTmyLpw6hgAQGAWgGw2m6ZPn64jR45Ikh588EGlpqYqKCio1v4N2VXJhBMA0FJOnDihOXPmKDQ0VH/9618VFxcnSdq/f78eeOABvfjii7rhhhvUtWtXD48UAAAA8F5Ww9CBnEKXQVm7rNwiZWQXKCG2C2s9teDUMQBAkjiuBkAmk0mLFi1SaGioAgMD9cwzz7gMyjaEfcI5a+FWzX5jp1LT87XvUIFS0/M1+42dmrVwq0rLLzhO3AIA0BBr167V+fPndf/99zuCspJ0zTXXaPLkyaqoqNC7777rwRECAAAA3s9iNmtzWp5bfVP25hJUdMHdU8f8/ADAtxGYBSDpYh3Z5cuXa8OGDRo/fnyz3JMJJwCgJW3btk2SNGbMmBpt9mtbt25t1TEBAAAAvqiouKJZ+7U3VsNQRvZJt08dc4gBAHwXgVmgHTp58qSys7NrXB8+fLh+8YtfNMtrMOEEALQkm82mnJwcmc1mXXHFFTXae/bsKbPZrJycHNlsvv0dYzWMOh8DAAAATRUWGtCs/dobTh0DAOyoMQu0M19//bXuv/9+WSwWbdy4UV26dGmR12nohDMxLqJFxgEA8E1nz57V+fPn1blzZ/n7+9do79Chg8LCwnTq1CmVlJSoY8eOHhil+6yG4VTDvfrj2p9DHXcAAAC0PKthaPTAaKWm59doM5tNiukaquDADiotr9SoATHMQ13g1DEAQOLELNCulJWVadKkSfrhhx+Un5+vRx55pEVPETHhBAC0lLKyMkmqsyZ6YGCgJKmkpMRln3Xr1mnSpElu/ZeZmdm8b0JyZIw4kFOoBWu/1K/u+i9FRUUpJjpaCxYsqHH69bnnnlNUVJSioqK0ZOnrNeq4v73sFf1qZF9FRUXpzbferpGRYtq0aY7nr1+/vsZ47rvvPkf7p59+WqP99ttvd7Tv2LGjRvvYsWMd7fv376/Rfv311zvav/vuuxrt/fr1c7QfP368RntcXJyj/dy5czXa7W1RUVE12s6dO+doq1qT2O748eOO9n79+tVo/+677xzt119/fY32/fv3O9rHjh1bo33Hjh2O9ttvv71G+6effupov++++2q0r1+/3tE+bdq0Gu1/+ctfHO1PPfVUjfZly5Y52ufOnevUZjUMLViwwNE+Pzm5xvPnzp3raF+2bFmN9qeeesrR/pe//KVGO589Pnu1ffYkOX32FixYUKOdzx6fvZb67AFwn8VsVmJcpOJjwhzXQoP9dMeYOK38w41aPGukXvl/w7R41kglxIYTlHWBU8cAAIkTs0C7EhQUpPnz5+v+++9Xx44d9dhjj8lkarnJMhNOAEBLMddzmrSqujYhHT16VHv27GmOITWY1bCptPyCUz3246ecg8jVT8MWnilztG3fd0xll1zm8v7/3HZYDz/o/D1f/Wfhzslc+K6qp6537D/muH7ydKlTOwAAgNWwac7kIZq7Ypd+LD2veVOGqmt4iL7KOqnVG78he0s96jp1XB2njgHAtxGYBdqZMWPGaP78+Ro4cKBiY2Nb7HWYcAIAWlJwcLAkqaLCddaF8vJyp761iYqK0qBBg9x6zczMTBUXFzdglHWzmE1OQVlJCvCzOP786a7vlXpsp9Nz8vf/4PjzwJ931VdFfiouvVDr/U+cLlVGdoESYrs4Xu9MlSwVG7cfVq+rC1k4a6eqbww49sOPjraUvXmatXCr5kweouBAPz4bAABAFrNJwYF+Sk4arvKKSp2vtGrWwq1Oc1lJSk3PV3xMGPOIaqqeOq7+M6sqPiaMcl8A4ONMtpbMYwpNmjRJe/bs0aBBg7RmzRpPDwftTH5+voKCghQeHu6xMdQ2Sa8qPiZMyUnDW3FEANA2MWdoGJvNpn79+qmiokL79+9Xhw7O+w0rKyuVkJAgPz+/WlNLNkZz/h1ZDUMHcgo1+w3nwOsdY+I0adzP3P7+XLMpU+9tznbZb2T/yzTj7v4qKbugOct31npPFs7aL+ZpANAymNe1ffwdNR3ziIarLWNOVczLAaBhqmcBa4msYC0xZ/D6vGVWq1WrV6/WLbfcooSEBA0aNEgPPvigUlNTa+1/+PBhzZgxQyNGjFCfPn00fvx4rVmzRka1+l2At0tLS9PNN9+syZMn6/z58x4Zgz3NTdUaJFXZJ5zV698BAFAfk8mk2NhYWa1WHTlypEb74cOHZRhGrTX12gKL2azNaXlO18xmk8YO7amvsk7WucglSVm5Rfoq+6TGDr1c5joWbex13N/650GX98zKLdLcFbtY/GlHrIahjGz3PmcZ2QXM1QAAgAPziMareup43tRrNbL/ZUqMi9DI/pdp3tRrlZw0nKAsALjB/t1yIKdQC9Z+qWeW7dCCtV/qQE6hU3tb5fWpjH//+99rw4YN6tixo4YOHaoLFy5oz5492r59ux5//HFNmzbN0ffbb7/VPffco3Pnzqlfv35KSEjQ7t279cILL2jfvn1KTk724DsBms/x48d15513qry8XKdOndKcOXP00ksvtfo4qk44M7ILlLI311FzZNSAGCXGRZA6EQDQaMOGDdP+/fv12Wef1UjP/9lnn0mSRowY4YmhuaWo2DkNc0zXUEVcGqTVG79x6/mf783TjLv7K6ZrqI5USUNblb2O+7ffu7dwlhDbhe/ldqC2jQGupOzNJZ0eAABwYB7RNPa5dkJsuNPPxh5EYC4OAHWrK/uAt6TT9+oTs5s2bdKGDRvUq1cvffLJJ1q+fLnefPNNrV+/XqGhoVqyZInjBIXNZtNTTz2lc+fO6dVXX9U777yjJUuW6JNPPlF8fLz+8Y9/6JNPPvHsGwKaSbdu3TRjxgxJUnh4uP7jP/7DY2OpOuGccXd/zZt6rWbc3d+p3h0AAI0xceJEBQQEaMWKFfr6668d1w8cOKCVK1cqMDBQd999twdHWDd70NQuOPDinsnqAVtX7P3sz6vNqAExOnuuQrkn6q+Nm7I3l+/ldqShnzMAAAA75hFNVz3VJvNwAHCPxWxymRJe8o6sYF4dmP3www8lSbNmzVKXLl0c13v37q3x48fLMAxt375dkrR9+3ZlZWVp0KBBmjBhgqNv586d9dxzz0kSNSXgUx577DHNmDFDmzZt0uDBgz09HCacAIBmd9lll+l3v/udzp07pzvvvFMPPfSQHnroId11110qKSnR888/79E663WxGoZGD4x2ulZaXimpZsDWFXs/+/Oqi48JU2JchPZ8c1yGG2l86ls4s1Yr/VH9MbxLQz9nAAAAdswjAACe4Cvp9L06lfGiRYt05MgR9ezZs0ZbSUmJJMlisUiStm3bJkkaM2ZMjb79+vVTeHi4vvzyS507d04dO3ZsuUEDLeD7779X9+7d5e/v77hmMpk0c+ZMD44KAICWd88996hHjx5auXKl0tPT5e/vr379+unRRx/V0KFDPT08lyxmsxLjIhUfE+b4hSL3RLEKzpRp1IBopabn13uPUQNiVPRjea2nYavWcc+uJ42xnauFM3vZgQM5hdqclucoSzB6YLQS4yIpS+CF7BsD3P2c8XcMAADsmEcAADzFV9Lpe3Vg1t/fX3FxcTWuf/755/r4448VHBzsCMTm5ORIUq39JalXr146deqUvvvuO/Xp06flBg00s9TUVD366KMaP368XnnlFZlMTHYBAO3LyJEjNXLkSE8Po8Gshk1zJg9xpOAxDJs+3nlEk8b9zClgWxv7aVhJmjt5qMs67pJN1/XpoY93fV/veGpbOPOF2i2oqbaNAbWp+jkDAACQmEcAADzLF9Lpe3Uq46rKy8v1+OOP6+abb9Yjjzyi8PBwLV++3JHi+OTJk5KkiIjaJwT264WFha0zYKAZZGRkaNKkSfrxxx+1du1avf32254eEgAAcJPFbFJwoJ+Sk4Zr3tRrNbL/Zco7UawzxeV69uEhio8Jq/V5VU/DSnXXca+6cFYX+8JZ9eCqL9RuQe3sGwPc/ZwBAADYMY8AAHiKL6TT9+oTs1UdO3ZMn3zyidO1rKwsDRw4UJJUVlYmSQoMDKz1+fbrpaWl9b7WunXrtH79erfGlZmZ6VY/oDH69OmjCRMmaP369erevbv69+/v1G41DKfartUfAwAAz7IHNBNiw51OFFgNQ8lJw5WRXeDyNKz9ufXVca9+Mre6qgtnzqdlDR3IKXS7dktCbBcCtF6k6sYAdz5nAAAAds0xj2DNCgDQUL6STt9nArPdunXTrl27ZDabtWPHDr344ouaN2+eSktLNWXKFEet2frSvBqGUe9rHT16VHv27GmWcQNNYTKZNH/+fHXs2FEzZsxQZGSkJGrBAQDgbWoGVy8+rhmwtf1fu/vf441dOPOV2i1wzfXGgIZ/zgAAQPvS2HkEa1YAgMbylXT6PhOYDQ4OVnBwsCRp3Lhx6t69u+6880698cYbuu+++xQUFCTpYsrj2tivh4SE1PtaUVFRGjRokFvjyszMVHFxsVt9gfocPXpUUVFRTteCgoL08ssvOx5TCw4AAN9R32lY9+/TuIUzX6jdgvo11+cMAAC0Pw2ZR7BmBQBoqsZmBWtLfCYwW11iYqJiYmL0/fffKy8vT5GRkcrMzFRhYaGuvPLKGv0LCgokua5BW9XEiRM1ceJEt8YxadIkTteiWWzcuFFJSUl65plndP/997vs524tuOSk4S00UgAA0FY1NADXnLVbSFcHAADQvrFmBQBoKl8oy+O1gVmbzab58+frhx9+0Pz589WhQ8234u/vL0mqrKxU7969tWXLFuXk5Gjw4ME17vXvf/9bFoul1qAt4GmbNm3SlClTJEnPPvusYmNjdf3119foRy04AADQXJqrdgvp6gAAAMCaFQCguXh7WR6v3aJuMpm0efNmbdq0Sdu3b6/RnpeXp8OHDys4OFi9evXSsGHDJEmbN2+u0Tc9PV2nT59W//791bFjxxYfO9BQI0eOVJ8+fSRJ0dHR6tq1a639GloLrq3/AwUAADynau2Wuthrt7gKypaWX9CshVs1+42dSk3P175DBUpNz9fsN3Zq1sKtKi2/4PjlCQAAAL6JNSsAQHPz1rI8XhuYlaQ77rhDkvTCCy/o+PHjjusnTpzQjBkzVFlZqbvvvlsBAQEaNGiQevfure3bt+u9995z9D19+rTmzp0rSXrggQda9w0AbgoKCtKqVas0ceJE/fOf/1Tv3r1d9qUWHAAAaC722i2ugrNVa7fUxt10dd7yyxMAAHC2adMm/fa3v1X//v01aNAgTZ06Vfv372/SPXft2qWrrrpKGzZsaKZRoq1wZy0qNNhP18RGyGoYTterP0bz4OcMAK3Pa1MZS9K9996r3bt3a8uWLRo3bpz69esnq9Wqffv2qbS0VCNGjFBSUpIkyWw2649//KPuu+8+zZ49Wx988IEiIyO1Z88enT17VnfccYdGjRrl4XcEXHT69Gl17tzZ6Vr37t21ePHiep/bnLXgAABA+9aU2i2u0tWZzSbFdA1VcGAHlZZX6lD+GdLVAQDghRYvXqwlS5YoJCREQ4YM0Y8//qgtW7boiy++0Ouvv64RI0Y0+J5HjhzRrFmzZLORTcMX1bcW1b1LiOZNGaqu4SHKyD5JGYwWRLkRAPAcrw7M+vn56X/+53/017/+VevWrVNaWprMZrPi4uI0ceJE3XHHHTJXOcp8zTXX6P3339eiRYu0e/duHTp0SJdffrlmzJih3/zmNx58J8BP3n33XT3zzDN66623dN111zXouc1VCw4AAMCusbVbqqerCw3207hre2ns0J6KuDTIcb3gTJmyvz/NnAQAAC/y9ddfa8mSJYqKitI777zjKLmUmpqqadOm6emnn9Znn32moKCgeu70k7S0ND3xxBMqKChoqWHDg+pbswoN9tO8KUMVGNBBsxZurbG5LzU935GtJTjQj7ljE9jLjdSW2YafMwC0PK8OzEqSxWLRpEmTNGnSJLf6x8bGatGiRS08KqBx/vznP2v27NmSpClTpmjjxo3q2bOn28+vWgvOVcpA6adacAAAAO5qTO0We7q6qqcfvso6qdUbv6ly8jZa1/WJYsMYAABe5M0335QkTZ8+3RGUlaQbbrhBEydO1HvvvadNmzbptttuq/deZ86c0dKlS/XXv/5VktSjRw8dO3asZQYOj6lvzWrctb3UNTyk1qCsnb0MRnLS8JYerk9zt9wIP2cAaBleXWMW8DXjxo1TZGSkpIupiy0WS4PvUb0WnNlsUs/unfTzXp3Vs3sn/ezyumvBAQAANJew0IAapx+eXb5Tqen52neoQKnp+Xp2+U7NWrhVpeUXmJ8AAOAltm3bJpPJVGtZsDFjxkiStm7d6ta91qxZo9WrVysqKkpvv/22Bg8e3KxjRdtRfc3Kzmw2aezQnvoq62SdBw2ki0HDjOwC5o2NZDUMZWTzcwYAT/L6E7OAL+nevbtWrVqlFStWKDk5WSEhIQ2+R9VacD8UligkqIM6hfxUw8NqGDLJJDMnUgAAQAuyp6uL7BzM6QcAAHzIyZMndfbsWXXr1k2XXHJJjfYrrrhCkpSdne3W/bp166Y//OEPuvPOO+Xv768PPvigWceLtqPqmlVGdoFS9uaqqLhCvaMvVcSlQVq98Ru37pOyN5dMcI1UvdxIXfg5A0DLIDALeNC5c+fUsWNHp2v9+vXT//zP/zTpvhazSVbDpu5dQpSRfVKb0/Ic6QJHD4xWYlwk6QIBAECLsqeru7x7pwadfkiI7cIcBQCANsxeAzYiovaAjf36qVOn3Lrfb37zm2YZ17p167R+/Xq3+mZmZjbLa6Lh7PO8hNjwGkE/exmM+rjbD7Xj5wwAnkVgFvAAm82mVatWafHixfrwww91+eWXN+v9rYZNpeUXaq0XkZqer/iYi+mMgwP9WPgEAAAtxmrYFBYaqD/vPehWf3bl181qGE61fqs/BgCgsWbOnKmDB+v/vr7xxhs1YsQISVJQUFCtfQICLmbtKi0tbb4BuuHo0aPas2dPq74mGq+2OUxYaEAtPWtytx9qx88ZADyLwCzgAS+99JKWLl0qSXrwwQe1YcOGGidnm8JiNtUalLUjXSAAAGgN9g1g7MpvGnumkwM5hWRCAQC0iGPHjunw4cP19isoKJDZzU1BhmE0dVgNEhUVpUGDBrnVNzMzU8XFxS08IjSEvQxGanp+vX1HDYhh/tNI/JwBwPMIzAIecNNNN2nFihU6f/68goKCVFZW1myBWath6EBOIekCAQBAm9Fcu/Lb44lRMqEAAFrDO++843bfb7/9VpJUUVH7hir79eDg4KYPrAEmTpyoiRMnutV30qRJnK5tY+xlMOJjwupc04qPCSPDShPwcwYAz/PtVQygjerfv79effVV3Xbbbfrggw9c1mVpDIvZrM1peZIks9mknt076ee9Oqtn904yV1usS9mbywIeAABezlrtNEr1x55m35XvDvuu/Jr3uHjtQE6hFqz9Us8s26EFa7/UgZxCp3Zf5G4mFOZ0AIDWEhkZKUkqLCystb2+GrSAK1bDpjmThyg+JqzWdvuGNF+e+7UGfs4A4FmcmAVaQXl5uQIDA52u/eY3v9Htt98uk6n5F9HKz1t1x5g4jR3aUxGX/lTzpeBMmT7eeUQf7Tis4tILpAsEAMCLeUt626buym/PJ0bJhAIAaIs6d+6s8PBwHT9+XOfOnauRAey7776TJMXFxXliePBiFrNJwYF+Sk4arozsAqXszXXMcUcNiFFiXESbmeN6M37OAGrTHjNUeQqBWaAF2Ww2vfbaa9q4caP+/ve/1/hlpSWCspI07fY+ujQ0QF9lndTqjd9UmVxFa9K4n+nGQTF6dvlOt9MKAgCAtsXbgpX2XfmuTn5W3ZVffbzunhhNThreImP3pKqZUOqTsjeXdHMAgFYzbNgw/f3vf9fnn3+u8ePHO7V99tlnkqQRI0Z4Ymjwcva5YEJsuNPcxn56sy3MbZuLJ4Mg7ennDKBu3rLp25cQmAVaUFJSkv72t79Jkh5//HGtXLlS5haeYFkNQ2azSbMWbnW5UDv7ocF6fspQFRSV8Q8rAABeyNuClY3dlc+JUbmd4YRMKACA1nTXXXdpw4YNSk5OVmJioqKjL5YtSE1N1fr16xUREaFf//rXTs+xn6Tt0aOHgoKCatwTqKp6gNKX5nhtKQjiyz9nAPXztk3fvoLALNCCrr/+ekdg9ty5cyotLa1xara5WcxmPb+y7oXaeat2KzlpuLqFh7ToWAAAQPPz1mBlY3blu3NiNDTYT+Ou7aUrojo53cNX0i65m+GETCgAgNaUmJiohx56SCtXrtT48eM1ZMgQlZSUKC0tTR06dFBycrL8/f2dnnPzzTdLklavXq3Bgwd7YtiAxxEEAdCWeNumb19BYBZoQXfccYe+/fZbVVRU6LnnnpOfn1+Lvl7DF2rDfWLBEgCA9sTb09s2dFd+XSdBu3cJ0bwpQ9U1PERfZZ1Uyl7fSrtkNQyNHhit1PT8evuOGhDj1e8VAOB9nnzyScXGxmrNmjXauXOnQkJCdMMNN2j69Om6+uqrPT08oE0iCAKgrfDWTd++gMAs0IwqKyvVoYPz/1azZ89usVqy1Xn7Qi0AAHBPe0pv6+okaGiwn+ZNGarAgA51lnDw5hMHFrNZiXGRio8Jq/OX5fiYMOZ1AACPuPXWW3Xrrbe61TcrK8utfi+//LJefvnlpgwLaJMIggBoS4gleA5H5YBmYLVa9fzzz2vq1KkyDMOprbWCsnbtaaEWAID2qr2kt7WfGK3NuGt7qWt4iOat2l3viQNvXtCyGjbNmTxE8TFhtbbbg8/2lNAAAABomxoaBPHmOSwA70AswTM4MQs00YULF/Tggw8qJSVFkjR//nz97ne/89h42stCLQAA7VV7Sm/r6sSo2WzS2KE99VXWSZ8/cWAxmxQc6KfkpOHKyC5Qyt5cR7rmUQNilBgX4dV/xwAAAO0JQRAAbQmxBM/gxCzQRH5+foqNjXU8zsrKktVqbfVxWA2brIahUS5OlVRnX6gFAADepWqwsi729LbeHrCr7cRoTNdQRVwapJS97ePEgX3sCbHhmnF3f82beq1m3N1fCbFdnNoBAADQthEEAdBW1JWhqjpiCc2LwCzQDJ555hmNGjVK06dP18qVK2WxWFr19a2GTaXlF/Tprlz1bUcLtQAAtFftKb1t1ROj86Zeq5H9L1Of3hcDku3txIHFbK72mLkcAAC+xlqtRFb1x/BeBEEAtCXtbdN3W0IqY6CBbLaLk6KqtWMtFovefPNNdejgmf+lLGaT5q7YpWOF59Q3PkKzHxrsst5a1YVa/jEFAMA7tbf0tlVPjCbGRTiuc+IAAAD4Cvvc7UBOoTan5TnmdqMHRisxLtKn5nbtlasyHdXZgyAA0NLsm77nrthFLKEVEZgFGuD8+fN65pln1KVLFz311FNObZ4KyloNQwdyCh3/cD67fKeenzJUyUnD9VX2SX2+N8+nF2oBAGivXAUr7TvrffG7vuqJ0fZUaxcAAPg2eya02hbGU9PzHQvjwYF+zGe8HEEQAG1Je9v03VYQmAXc9OOPP+qBBx7Qrl27JEnx8fGaMGGCh0d1cYFyc9pP9dV+KCzRjNe2aNzQXho79HLNuLu/o+3suYr/ew7/kAIA4Cvaa3pbThwAAABfYc+E5mpOk5VbpLkrdik5aXgrjwzNjSAIgLamPW769jQCs4CbgoODFRgY6Hi8ffv2NhGYlWrWTSsuvaD3Nmfrg88PKaZrqIIDO6i0vFKdOwVo7pRrPTRKAACA5sWJAwAA4O2qZ0JzJSu3SBnZBUqI7cK8xssRBAHQFrXXTd+eQGAWcFOHDh30+uuva8KECbrjjjv06KOPenpIDq7qphmGTUd++NHxuFePy1prSAAAAC2OEwcAAMDbVc+EVpeUvblkAvEhBEEAoH0iMAs0wCWXXKKPP/7Y6eSsp1FfDQAAtGecOAAAAN6ueia0pvZD22Y1DKegbPXHAADfRmAWqEVZWZlmzZqlsWPHavz48U5tbSkoK1FfDQAAQOLEAQAA8F6uMqE1th/aJvthiQM5hdqclufI9DJ6YKTRrrAAACAASURBVLQS4yI5TAEA7QSBWaCa48eP64EHHtD+/fv18ccfq2fPnkpISPD0sOpEfTUAAAAAAADvQya09sFq2FRafqHWtbvU9HzH2l1woB9/vwDg4wjMAtUEBgaquLhYklReXq5PP/20zQdmqa8GAAAAAADgfciE1j5YzCaXByokKSu3SHNX7FJy0vBWHhkAoLURmAWqufTSS/XWW2/p1ltv1ZNPPql7773X00NyC/XVAAAAAAAAvA+Z0Hyb1TB0IKewzsC7dDE4m5FdoITYLvw9A4APIzAL1CI2NlY7duxQaGiop4fSYNRXAwAAQEuyGobTnLP6YwAA0DBkQvNtFrNZm9Py3OqbsjeXk9EA4OMIzKJdKy4u1qxZszR9+nT94he/cGrzxqAsAAAA0FLsC8IHcgq1OS3PsWA8emC0EuMiWTAGAKAJyITm24qKK5q1HwDAexGYRbt15MgR3X///Tp06JDS09O1adMmRUSwIw0AAACozmrYVFp+odYUi6np+Y4Ui8GBfiwcAwDQBGRC801hoQHN2g8A4L3IN4V2q7KyUsePH5ckHTt2TJ9++qmHRwQAAAC4ZjWMOh+3JIvZ5LLunXSxJtrcFbtYPAYAAKjGahgaPTDarb6jBsQ4TkkDAHwTgVm0W7GxsXr99dcVFBSkxYsX65577vH0kAAAAIAa7ItzB3IKtWDtl3pm2Q4tWPulDuQUOrW33Osbysg+6TIoa5eVW6SM7AIWEwEAAKqwmM1KjItUfExYnf3iY8KUGBfBRjcA8HGkMka7NmrUKO3evVvh4eGeHgoAAABQQ1tIIWwxm7U5Lc+tvil7c53q4gEAAODinG7O5CEuM5DY53RWw0ZgFgB8HCdm0S6cPn1a06dPV2FhYY02grIAAABoq9pKCuGi4opm7QcAANCeWMwmBQf6KTlpuOZNvVYj+1+mxLgIjex/meZNvVbJScNbdKMdAKDt4MQsPMpqGLKYzS4fN4fMzEw98MADysvLU15ent59910FBAQ062sAAAAAzc1qGDqQU+h2CuGE2C4ttpgXFure/NndfgAAAO2NfZ6WEBvulGHEXgaCoCwAtA+cmIVHtGadrB9++EH5+fmSpL179+qLL75otnsDAAAALaWhKYRbajHPahgaPTDarb6jBsRQYxYAAKAO1Q+lEJAFgPaFE7Noda1dJ2vUqFF65pln9Kc//UlLlizR6NGjm3xPAAAAoDW0hRTCFrNZiXGRio8Jq/P0bnxMGPVlAQAAAACoAydm0eo8USdr6tSp+vzzz/XLX/6y2e4JAAAAtLS2kkLYatg0Z/IQxceE1dpu31zJaVkAAAAAAFzjxCxaVUvXyfrhhx+0ePFiPffcc/L393dcN5lMioqKavS4AQAAgNZmTyGcmp5fb197CuGWSoVnMZsUHOin5KThysguUMreXBUVVygsNECjBsQoMS6iRV8fAAAAAABfQGAWraqhdbIakgrtq6++0kMPPaQTJ07o/Pnzmj9/vkwmFoYAAADgnaqmED6Uf0YxXUMVHNhBpeWVyj1RLOP/Tqe2Vgphe9A1ITbc6fXsp2QJygIAALhmNQyn+rLVHwMA2gcCs2h1LVUna/fu3Tpx4oQk6b333tODDz6on//853U+hwkRAAAA2jKrYdOLj16r0opKhYUGOq4XnCnTxzuP6FBukZ6cNKBVT6tWny8TkAUAAHDNPk87kFOozWl5jqwjowdGKzEukqwjANDOEJhFq2upOllTp07VN998o82bN+uNN96oMyjLhAgAAADeIsC/gzKPnNafPzxYJX1wtCaN+xmnVQEAANowq2FTafkFzV2xq0Zpt9T0fMXHhGnO5CEKDvRjPgcA7QSBWbSqlqyTZTKZ9Oqrr+rkyZOKiYmpYwxMiAAAAND2NWTeCgAAgLbHYjbVOpezy8ot0twVu5ScNLyVRwYA8BRytqJVVa2TVRd7nSxXgdEjR47otddek81mc7oeGBhYZ1D24hjcmxARlAUAAIAnMW8FAADwXlbDUEb2SZdzObus3CJlZBc4MqEAAHwbgVm0Oqth05zJQ1wGZ+07/11NRrZv365f/epXmj9/vt588003Xs9w+jMTIgAAALR1zFsBAAC8m8Vs1ua0PLf6puzNZbMdALQTpDJGq7OYTQoO9FNy0nBlZBcoZW9ulVpZMUqMi6gzhfEHH3ygM2fOSJJeeuklTZgwQeHh4TX6Va8jG+Bv0f/7TWKDJkSJcRGNf6MAAABAIzV0IY95KwAAQNtTVFzRrP0AAN6PwCw8wh50TYgNd1pEsu/0r2uH2EsvvaRDhw7p6NGjWrVqlcugbPV6XD/v1VkSEyIAAAB4B+atAAAA3i0sNKBZ+wEAvB+BWXiUxWyu9rj+lB2BgYFatWqVrFarevTo4eK+NetxlZZXSmJCBAAAAO/AvBUAAMB7WQ1DowdGKzU9v96+owbE1JlBEADgO6gxizbt22+/1fvvv1/jeteuXV0GZV3V48o9UayCM2UaNSDarde2T4gAAACA1mZfyHMH81YAAIC2x2I2KzEuUvExYXX2i48JU2JcBEFZAGgnCMyizfr00091yy23aObMmdq2bZvbz3NVj8swbPp45xH1jWdCBACAt1u6dKni4+Nd/lfbxi7Am7CQBwAA4P2shk1zJg9xOaeLjwnTnMlD2GQHAO0IqYzRJhmGoUWLFqmkpESSNGPGDG3fvl3+/v5uPd9Vna2PdhzWjYNiNPuhwZq3aneNU7WS84SIBS4AANqmzMxMSdKNN96owMDAGu0xMTGtPSSg2dkX8qqX6LBj3goAANC2WcwmBQf6KTlpuDKyC5SyN1dFxRUKCw3QqAExSoyLYC4HAO2M1wdmrVar3nnnHa1fv17//ve/ZbVaFR0drZtvvlkPP/ywAgKc6y0dOHBAS5cu1YEDB1RaWqrY2Fjde++9Gj9+vIfeAWpjNpu1cuVK/epXv5Kfn5/efPNNt4Oykus6W8WlF/Ts8p16fsrQ/5sQnVTK3jwmRAAAeJlvvvlGAQEBeu2119Shg9dPaQEXbCzkAQAAeDn7XC0hNlyJcRGO6/ZTsszlAKB98epVLKvVqscee0ypqakKDg5Wnz591KFDB+3bt0+LFi3Sli1b9PbbbysoKEiStH37dk2dOlWGYWjgwIEKCgrSzp07NWvWLOXk5OiJJ57w8DtCVd26ddPq1avVrVs3XRrmnO7DahiymGvPxG2vx5Wanl9r+w+FJZrx2haNG9pLvxnTW4lxkVWey4QIAIC27uzZszp69Khj7gf4Gnuw9UBOobbvO6a4y8M06OfdNOPu/k59JOatAAAA3qL6WibzOABon7x6Jev9999Xamqq4uPjtWLFCnXt2lWSdPr0aT322GP66quv9Prrr2vmzJkqLy/Xk08+KUn685//rCFDhkiScnNzNWnSJC1btkw33nijfvGLX3js/bRnGRkZKisr09ChQyX9tBh1ZWy8AgM66Kss55OtowdGKzEustYTAlXrcdWW8k26eHJ236ECTbr5Z9We27gJUfVAcV2BYwAA0DT2NMZXX321h0cCND+rYVNp+QWn9MUf7/peZrNJMV1DddXlYbr/11crMMCrf5UDAAAAAKBd8urI0fr16yVJTz/9tCMoK0mdO3fWc889J0nauHGjJGnDhg06deqUxo8f7wjKShfrj82aNUuStGbNmlYaOapav369Jk6cqIcfflhHjhxxLEadOlumigtWzVq4Vc8u36nU9HztO1Sg1PR8zX5jp2Yt3KrS8guO0wJV2etxxceE1fKKzvW4msL+/AM5hVqw9ks9s2yHFqz9UgdyCp3aAQBA87EHZoOCgvS73/1OI0eO1DXXXKNbbrlFa9askWEYHh4h0HgWs6nWmrKGYdORH37Ux7u+15zlOzlhAQAAAACAF/LqbdZhYWG64oordM0119Ro69mzpyTp5MmTkqRt27ZJkkaPHl2j78iRI2WxWLR169aWGyxqVVJSohdeeEEVFRWqqKjQE088oXXr1umLjGMad21PzVq41eWp16zcIs1dsUvJScNrtFnMphavx1XbaQa71PR8R/A3ONCPhTMAAJrRN998I0latWqVIiMj1adPHxUUFOjgwYN64YUXlJaWptdee01mN7JXrFu3zrHZrz72gDDQUqyGoQM5hS7nv3ZZuUXKyC5QQmwX5pkAAAAAAHgRrw7MLlu2zGXbgQMHJF2sUypJhw4dkiTFxcXV6NuxY0dFRkbqhx9+UGFhobp06dICo0VtQkJCtHLlSt12222Kjo5WcnKy9h0q0ICfd9VXWSebtChlf5wQG67EuAjH9eaqx+XqNEPVsbkKHAMAgJ/MnDlTBw8erLffjTfeqJkzZzoCpPfee6+eeuop+fn5SZK+/fZbPfroo/rkk0+0du1aTZo0qd57Hj16VHv27GnaGwCaicVs1ua0PLf6puzNdZrjAgAAAACAts+rA7Ou2Gw2LVy4UJL0y1/+UpJUUFAgSYqIqH3xIiIiwu3ALCcrmlffvn319ttvq0+fPurUqZNWb/xGiXGRWr3xG7eeX9+iVPVar81xqoDTDAAANJ9jx47p8OHD9fazz+fee+895efn19hwd9VVV+kPf/iDpk2b5nZgNioqSoMGDXJrnJmZmSouLnarL9BYRcUVzdoPAAAAAAC0HT4ZmP3Tn/6ktLQ0denSRQ8//LAkqaysTJIUGBhY63Ps10tLS+u9PycrGm/nzp3q3r27I9W03bBhwxx/rrhgldS2F6U4zQAAQPN55513GtQ/ODi41iwokjRixAhZLBYdPnxYpaWlCg4OrvNeEydO1MSJE9163UmTJjEHRIsLCw1o1n4AAAAAAKDt8LnA7MKFC7V8+XL5+/vrtddeU+fOnSVJFotFNptNJlPdpxYNw6j3NThZ0TirV6/W7NmzdcUVV+jDDz9UaGhorf0C/CyS2v6iVFsOHAMA0F75+fnpkksu0enTp1VeXl5vYBZoS6yGodEDo5Wanl9v31EDYmQ1bGRlAYAGshqGU2at6o8BAACAluQzgdnKyko9//zzevfddxUQEKDFixdr4MCBjvagoCD9+OOPqqioUEBAzUBeeXm5pIs1T+vDyYqGy8vL03PPPafKykplZ2drzpw5+tO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\n",
"text/plain": [
"<Figure size 1152x288 with 3 Axes>"
]
},
"metadata": {
"image/png": {
"height": 269,
"width": 947
},
"output_type": "display_data"
}
],
"source": [
"warnings.filterwarnings('ignore', category=DeprecationWarning)\n",
"from sklearn.model_selection import GridSearchCV\n",
"\n",
"search = GridSearchCV(p, param_grid, scoring=\"neg_median_absolute_error\", cv=4, n_jobs=4)\n",
"\n",
"search.fit(features, values)\n",
"\n",
"\n",
"print(search.best_params_)\n",
"eval_regression(search)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Exercise section\n",
"\n",
"- Play with the examples above and try different algorithms, metrics and pipelines.\n",
"\n",
"\n",
"## Optional exercise\n",