{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tree-based methods"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Random Forest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>Sepal.Length</th><th scope=col>Sepal.Width</th><th scope=col>Petal.Length</th><th scope=col>Petal.Width</th><th scope=col>Species</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>5.1   </td><td>3.5   </td><td>1.4   </td><td>0.2   </td><td>setosa</td></tr>\n",
       "\t<tr><td>4.9   </td><td>3.0   </td><td>1.4   </td><td>0.2   </td><td>setosa</td></tr>\n",
       "\t<tr><td>4.7   </td><td>3.2   </td><td>1.3   </td><td>0.2   </td><td>setosa</td></tr>\n",
       "\t<tr><td>4.6   </td><td>3.1   </td><td>1.5   </td><td>0.2   </td><td>setosa</td></tr>\n",
       "\t<tr><td>5.0   </td><td>3.6   </td><td>1.4   </td><td>0.2   </td><td>setosa</td></tr>\n",
       "\t<tr><td>5.4   </td><td>3.9   </td><td>1.7   </td><td>0.4   </td><td>setosa</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllll}\n",
       " Sepal.Length & Sepal.Width & Petal.Length & Petal.Width & Species\\\\\n",
       "\\hline\n",
       "\t 5.1    & 3.5    & 1.4    & 0.2    & setosa\\\\\n",
       "\t 4.9    & 3.0    & 1.4    & 0.2    & setosa\\\\\n",
       "\t 4.7    & 3.2    & 1.3    & 0.2    & setosa\\\\\n",
       "\t 4.6    & 3.1    & 1.5    & 0.2    & setosa\\\\\n",
       "\t 5.0    & 3.6    & 1.4    & 0.2    & setosa\\\\\n",
       "\t 5.4    & 3.9    & 1.7    & 0.4    & setosa\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "Sepal.Length | Sepal.Width | Petal.Length | Petal.Width | Species | \n",
       "|---|---|---|---|---|---|\n",
       "| 5.1    | 3.5    | 1.4    | 0.2    | setosa | \n",
       "| 4.9    | 3.0    | 1.4    | 0.2    | setosa | \n",
       "| 4.7    | 3.2    | 1.3    | 0.2    | setosa | \n",
       "| 4.6    | 3.1    | 1.5    | 0.2    | setosa | \n",
       "| 5.0    | 3.6    | 1.4    | 0.2    | setosa | \n",
       "| 5.4    | 3.9    | 1.7    | 0.4    | setosa | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  Sepal.Length Sepal.Width Petal.Length Petal.Width Species\n",
       "1 5.1          3.5         1.4          0.2         setosa \n",
       "2 4.9          3.0         1.4          0.2         setosa \n",
       "3 4.7          3.2         1.3          0.2         setosa \n",
       "4 4.6          3.1         1.5          0.2         setosa \n",
       "5 5.0          3.6         1.4          0.2         setosa \n",
       "6 5.4          3.9         1.7          0.4         setosa "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "library(randomForest)\n",
    "\n",
    "data(iris)\n",
    "head(iris)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ploting data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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CJN+v1XjWFohRoeGF1DAAEENifALHabE2I9AggggAACwwvsqGkYutsP9/oWP9Q/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yWU6Q0XGLkw3QVSViP63WoW51kwsyfjZz\n00vEri2jFY6U9tJjTDKtNnnxPpPTmcrPmdrPK5YEAQhAoFwCmTJI7aMc9eVar7uDYWVpmrSP\n9DdJzfgkCEAAAhBocQJqjZi1vLpmlcCwg9b1LaI/S5YIatCq9mkh7CSj1lFkf/IvYX2v21Qt\nOTouxxZL62jFQjIT4SN6/FatLR8sEWs+A17/JbHQ766ZFEuOndWlP1vKIGny/mKByv+QDqR9\nY82o0tNkgJYrEfvhHh3T5grYQI8kqeCJRWInKP/9vjZQHAkCEIBAaxIYrV/491sTC0cNAQhA\nAAIQgAAEIAABCLQigdFakFqRCccMAQhAAALlEdCD/hOeGH5MtdgGV2pF92v681yxiMblD07X\n4HFq9VHPtYLJA8XpUZ4QbtNr/nRcji2W7tOKN9zEc7G65WkQhn+UiNVjR6HD608QC3WFM5Ni\nybET/LzQTcM9+K4rFqj8K3Qgg3doRpWerqafJ0vEXtKrY7pFAXeHcKPqMrNIrHviXefugIoj\nQQACEIBALQi4O55/Nb5ci8JaqAyeQWqhk82hQiBjBPS9zyANdRqk4TQGacjYp4XDgUB2CXTr\n0HwjaLPsHmL1R3aoNjWcQ6ovoiW3xCC15GnnoCGQCQJqRckf5ttDV7fyMN936/jrMcz3QyqX\nYb4z8anhICCQPQIYpBLndAmtW1vylFQ+AQxS+ayIhAAE0kfAXc2+riGyn9ZUF/FWU7wo1l3J\nVFePMDfqi2KjWL8radQXxUYMPGLdqC+KjXmVeFFsu16p0fXGXLajvihWXR9z50H7L/WiWI+A\nlxv+W3XwlBfFihsJAhCojgAGqTpubFWCAAapBBxWQQACTUXAI9ZpiOqmSIurlttJC5RRW7/e\nYi2pq4zYZRSzmmTjOFpaSQErjBak9X5m2Dcfy6mrB2CaImmUwVGTL2qmSp6SIAABCFRLoKUM\nkoYFzY0F6vFAK9Foo+NVCz+r22GQsnpmOS4IQAACEIAABCCQfQKZMkijjWJ3u86nm+or1Q+y\n/3/AEUIAAhCAAAQgAAEIQAACWSMwWkvPLTrgF6o46Meq2IZNIAABCEAAAhCAAAQgAAEIjCuB\n0QzSV8a1duwcAhCAAAQgAAEIQAACEIBAAwmM1sWugVVhVxCAAAQgAAEIQAACEIAABMaXQD0M\nUocOiWG+x/e8sncIQAACEIAABCAAAQhAoAoCo3WxK1TkR5X5cWlBKR7u1EOZuiyPdLeSdJx0\nqESCAAQgAAEIQAACEIAABCDQNAQqNUj/qyM7aZSje1Tr/zVKDKshAAEIQAACEIAABCAAAQik\njkClXey+oyN4S9pLWkp6W/q+tKr0P9Lr0tXShRIJAhCAAAQgAAEIQAACEIBAZgn42aI+6azE\nEdoMXZRYXk/zA9JGiTxmRyfAi2JHZ0QEBCAAAQhAAAIQgEA6CbTUi2KTp2B+LfiZoxsTmQ9r\nfp3E8r2a/6+0ayKPWQhAAAIQgAAEIAABCEAAAk1BoJIudm/qiF6RVkscmQ3SslJy1LqntLx6\nIoZZCEAAAhCAAAQgAAEIQAACTUGgEoPkA/LgCx7FbhMvKN0/PMnleXYBaUvJzymRIAABCEAA\nAo0mMFU7dDfvaWXs2DGO9Ta1Sh78aE1pfck9L2qVFlRBG0i+AVnpb3et6rCiCjKvxWtVIOVA\nAAIQyAKBdXUQfg5pUHqf5C/px6RZkgdmeEkakjyIA6l8AjyDVD4rIiEAAQgUIrBhCBPu0Ar/\nBkXq8aiqOxUIVl5uXSI2t63KqDr5Od0f6o0XvkEYlduu38uuv2h5kapLzZm3znNCaJs9t9yu\n1zT/Tcmv2GhE+qR4PaUdxbx0DTDhRi3bCJIgAAEImECmnkGq5pRuq42ukFaJNvZdsuek+Ivz\nNM23R+uYlEcAg1QeJ6IgAAEIFCKg3yWbkT1kIu7Vb9E70iPSN3Uh3+aBgz6f2OgLw3le5xjH\nehtv6zKCf+MqTTIq3X8PYXJvCH9UWS9Kb0qXSKspr+cJFViNSdJosd3Ph7CeyrhKZc2QnpN+\nL020+TpF5dY7HSguYvgD8XpM+zWvO6Sd+0PoeFc7d4sSCQIQgEBLG6QVdP4XLfA/4DtnNkpu\nft9acksTqXwCGKTyWREJAQhAIElALyjvejGE/XURP6QL93wdp7x2GYywzLA877z8OC+7DJeV\ne+l5ch+jzct0TZBheahAuTY1NkkdfxmtkJHruy+V/9C2swqUe5fyOt2q9LGR29UsZ/VhM/m3\nAvs3r89q/z2Pa2+VvlOxZhWkIAhAIDUEWtog+YvwkBKnQj9UuZakY0vEsGokAQzSSCbkQAAC\nECiHgLp/uTXFLRuFTI/zVpqpgn44LM8Xi3MZLit8opwdz42ZeF8I3yux/0u1rl0tLrnndOdu\nVnpuqlar1eaWEuV+UYau55rSxYxp7a9D2Fhd6IvxekV161AdwnZj2gsbQwACWSCQKYM02l2f\nlXXGtkqcNQ/C4JYi3S0bkdqVE7ccuX80CQIQgAAEIFBvAmvpZ0kX6ZO6iu9o+wkhTI9+nzxf\nLE3SCpd189qaObdY1Mj8Xo3uuvXI7Dk5/hkd9O+tX6p+15zs0jN6vqdDBmnTjuJhW+t39y/J\nV20UD61qzUQ9k7V9T/FN3aFkZbVwPaxzEOpp1IpXgTUQgAAE6kBgNIPkrgY/lXwnK067aMYq\nlt7RiguKrSQfAhCAAAQgUEMCavGZqZaMUsnrBz2YkFIutsTgBrn1bkWqILWrq9lM3z0tkqJd\nDw9yVCRmRLbqMKh6uuGpWNG5ch1QpzTo7n2jlF3vOoyye1ZDAAIQqAOB0QzSW9rnhyX1Q86l\no/T3JqmQAdKdruAHNu+RnpJIEIAABCAAgXoTuDWE+9TK8Zz2s2SBfekaP1xqs3HL8MpL1X2u\nV/GFGkZchssKtw7Hlvu34zYN5KompN2KtPZcpII63w5h9kPllqg4/ZZ6gIlL1Uq0W5HNzpc5\nGvBvcp1S7w0hnK/mr1+KiTuJ5Kf/KmO6u9ZXyCu/HJYhAAEINDeB36r69XwgtLnpVF97nkGq\nnh1bQgACrU1ArSw9/9bgczJBbv1JPi8zqOV91brT9YoQuYu45HnneV0y1tu6jB49T1Tx8Nnb\nDZuZC/PKdPn/lRa0SztEqjC1/04dOLTtUwXKPVV5uRH61A2ubmmxYWP3Hd0ATbLy/FuSB5Do\nkYkiQQACEGCY7/h/wHeN3O84fmnsfPEKphUTwCBVjIwNIAABCMwhsIIu1NX8s6L6ex2rC/er\npVOkjXUB3zlDUZvPiczNuzXH6xzjWG/jbV1GUFnVpPaDhw3L3jJfNkr/kH4gedCH7ktU4mg9\nNgrtVM9L9aiFaAHV9Scq60rpPGl3tRzlzNF+hTaqcd4OehZKbLZSHU7Tvs3rd9LS5vW49jW1\nxvujOAhAoDkJdKva+m4ImzVn9cde62VVxNmS7ijlQMTN++52d7jk7gmkyghgkCrjRTQEIACB\nfAIaMaD9VxpuWybH5qH7VV3Yn6SgafmBw3le5xjHehtvW/A1FgU2L5q1vX4Cr9V+1d3c71Sa\ncL8ivygV6p9WtJC8FR58Yn+V9bDqKmPUqed8e65Q3vvy4uq5uKpa3s6QXo94Pa2d+fd+cj13\nStkQgEBTEehWbVvWIPlOkbsqGMB/pOlSbJAu1LzzH5BKjBKktaR8AhikfCIsQwACEIAABCAA\nAQg0C4FMGaRK72r9XmfJXeu2lDxwgwdkiNPHNfMzaQ1p7ziTKQQgAAEIQAACEIAABCAAgWYh\nUKlB2k4Hdoz0zwIHqG4K4TDpTWnTAuvJggAEIAABCEAAAhCAAAQgkGoClRgk9zVeWHqkxBGp\nf3R4MIorEcYqCEAAAhCAAAQgAAEIQAAC6SNQiUF6S9V/QdqoxGHYRLmLnR4mJUEAAhCAAAQg\nAAEIQAACEGguApUYJB/Z5dI+0tek+aVkWkgLf5EWlK5KrmAeAhCAAAQgAAEIQAACEIBAFgnY\nBD0lebQ6P2vkFqVnJY9gp+FSc/kna0qqjACj2FXGi2gIQAACEIAABCAAgfQQyNQodtVgfY82\nOl7qlWyUYtkgfV3qkEiVEcAgVcaLaAhAAAIQgAAEIACB9BBoeYMUnwoboRUkv6F8yTiTaVUE\nMEhVYWMjCEAAAhCAAAQgAIEUEMiUQeocA1AP6/14pDEUw6YQgAAEIAABCEAAAhCAAATSQaBc\ng+Thvf1uI7cYeZjvmyR3sSNBAAIQgAAEIAABCEAAAhBoKQK76WjfluJnjTy1SSo13LdWkyog\nQBe7CmARCgEIQAACEIAABCCQKgKZ6mLXPgra1bT+PGmCdJ10jPSitIp0hmQYJAhAAAIQgAAE\nIAABCEAAAi1B4Bc6SrcYfStxtF2aPzHK/0win9nqCdCCVD07toRAWggso4p8RNpJWiItlcpI\nPdbUcbg3w3bSfCWOyTf93LvhY9IWEjfxBIEEAQhAoAEE/H1rz7BZA/Y17rvwi2FnSG15NfGP\nlSH8JC+fxeoIYJCq48ZWEEgDgam6Dr9MFdF34oR+zUtBg9h0uZXdL84mVU9gwxB6HtDmYjuf\nnnvtENeOWVo+RMrvAbGzYp9V/qDeY67YNp+DN7Ts71cSBCAAAQjUl0BLGaTbxPKpAjznV54N\n0qkF1pFVOQEMUuXM2AICaSCwmAzRMyFsoAvy2/WdOCQNStdKK+tCvudBVbJUi0cajiGtddhY\nZkhcPz07hCcitrM0PU1aoE/m57RExXcfNkTfljl6KYp9S9OjpE5tHw5OxDILAQhAAAK1J9BS\nBulf4vdEAYa+c6cfnnB+gXVkVU4Ag1Q5M7aAQAoIdJwcwuq6iH9X34c2R0m9quUpbu34aQoq\n2mxVUK+Fnv+G8FmZmyTTeP4esW238XF3RrXSdb0VwhF5/OPYc5Xv1qSwarNBoL4QgAAEmogA\nBkknC4NU2/9YDFJteVIaBBpBoGe4u9cFRS7MfYF+jNTjgW1IlRHwc0RqDXq2BNv/kUHq9k26\nz4QwWSa1r0TsOhjVyvgTDQEIQKBSApkySPl9uCuFQTwEIACBViWwjB41kknytXyx5HW9i+vP\npGIR5BckoBFUF5PpWbLgyuHMTTtkUP08rGLXlZnqKhH7Pp2nzjVKBLAKAhCAAAQgMIdAOS+K\nnazoA+ZsMTwTD9qwYoF1jvCzSxYJAhCAQFYJvDN8YG9qslSRY/QYAe7eNaSLfVIFBPTuvXdk\ngNQoNGKMoLiUHFu/o0963YEl0hsyUIPqhkeCAAQgAAEIjJ2An0HyD0+lOmTsu26pEuhi11Kn\nm4PNDoGe6SH8WN+P8fMu+dPPqxvYhJuzc7wNOxK1utlYXl6ErQfCWM3d5n4ubaZYGaBHi8R6\nsAaPahc+J5EgAAEIQKA+BDLVxW60FqTfiOFiVXC8pYpt2AQCEIBAkxHo/aEGBzglhC3V2rF9\nXt3P1PLJam0f+nHeChZHJ/CSHnU9IYT//UIIN+tHd4XEFvI74Vv68/9kPsPvpef1LNKNIXxC\nRulaxS6SiLUv2lNx/S9oxieEBAEIQAACEIBAkxCgBalJThTVhMBIAu1qxXBrx+66EP+jLtyP\nlT6kYahzI6d9Y2Q8OWUSmKDniq7UIBdi+TW1EJ0srr+S1lLLUae7N26bKEctTh5SfSE5ooMV\nc4p0uLSsYrtloMJ7E7HMQgACEIBA7QlkqgWp9ngosRoCGKRqqLENBNJDYBtdtGtEtYlPS9M1\neMDpqtoG6ale09bEAwl9Vt0Ur5eeE9tHtOyeDUtL+UmGKuyvmDsUK1M06X4tHyotJJEgAAEI\nQKC+BDBI9eXbkqVjkFrytHPQEIAABCAAAQhAIBMEMmWQfHeOBAEIQAACEIAABCAAAQhAAAIi\ngEHi3wACEIAABCAAAQhAAAIQgEBEAIPEvwIEIAABCEAAAhCAAAQgAIGIAAaJfwUIQAACEIAA\nBCAAAQhAAAIRgdHeg5RFUAvroBaUeiS/hd2vY/eQsSQIQAACEIAABCAAAQhAoMUJtEoL0no6\nz3+W9PLB8Jr0hPSw9Ixkk/SYdIJUzUtxtRkJAhCAAAQgAAEIQAACEMgCgVZoQfJb7A+LTtZT\nmt4q2STZGLklya9dX1b6ovRx6RvSGRIJAhCAAAQgAAEIQAACEIBApgh8Ukejt6mHy6X1SxxZ\nm9ZtJd0pOX5zqZGJ9yA1kjb7ggAEIAABCEAAAhCoJYFMvQeplmDSWJbfZu/uc37eqJzk55Pe\nko4vJ7iGMRikGsKkS50h3QAAQABJREFUKAhAAAIQgAAEIACBhhLIlEHK+jNIa+tfw13qesv8\nF3ldcf+WlioznjAIQAACEIAABCAAAQhAIEMEsm6Qnte52kDqKvOcuQXJpsoDOJAgAAEIQAAC\nEIAABCAAgRYjkHWDdKrO52rSedImJc6tn0HaUrpCmiRdKJEgAAEIQAACEIAABCAAgRYjkPVR\n7Dwa3eLS4dJHpGclD+39quRnjSZLi0jLSVOl2dKB0s0SCQIQgEAzEZimynoUTo/K+aT0B2m6\nNNa0gwr4lDS/dIfkcsvttqzQgsk357aQ1pL6pFukB6VGJr/WYXvJ06elq6UZUqHk34htJP9m\nPCpdJ42VgYogQQACEIAABMaPwAra9ZmSDZJHqUvqHS37B+9X0jLSeKR9tVPXab7x2Dn7hAAE\nmp7AJSF0DMrDSKtI80leDn8fw5Hp+7A7+s6corJWisrs7leZ+42h3PU1bo6+c9sGQljhXT3y\nOVNl6fuv50pNbVbqnWzODguhXcZsskzOKqrDRM13+tUP/i5OponqoX2yMlTXxWaFsLJiu3Qj\nretF5e2UDGQeAhCAQIsTyNQgDa14Ln0H0EZoZcnvQUpDwiCl4SxQBwg0J4HrZS5kXk6RyZgt\nDUXTEzXttkm6qorD0s2abt08Wlnb3xmV6XJfk76ovHaX+7kqyl1dxk3lflom48VEufdrfh2Z\nlZ7/qky3VNUxdRytXcgQnaN9DkR16NP091KH6hW+Gu1cXa+7xG5JGaProzgzmCF9R8dvgxc+\nWMeKUjQEIACBZiKAQWqms9UkdcUgNcmJopoQSBmBbXWhrov1CxIX8L6Ij2UTkDMzW1ZY73PV\nuqJyX0iUFZfp6Z5a1+OWnwpTzw0h7KgWqMEC5b6hvCkyI+GQCgutJFytV0F1Txqe5HGdoDp0\n+LjckqVuhW4te6xAXb3NN83gWcV1SCQIQAACrU4Ag9Tq/wF1OH4MUh2gUiQEWoDAFSGsqgv1\n5EV+/vwKWh8urozFBLXy/LCIMXD5j0ruFhd2qKBcPw+qutxRotxfa92EJyoos9LQ/9N7wGXC\n8hnFy25Reo9N2hdkfi5Tjzu1EsXr8qevKjbXirRFpZUgHgIQgEAGCWTKILkvNmkuAferv0/6\n8tysqub8zJPfqaSLjLLkh55JEIAABColsFwIbhQpldbzymmlIkauG5wwPH7CyDXDOStp0iWD\nEDYqFlEgf3nlqduax2Uolryud+lia8ee37myePUUL8c/iWv4uPQd3q7YtUv8Rnp8n8XVVc+x\nJAhAAAIQyBKBziwdTA2OZQmVsbbk6VjSdG28u9RVZiHux+7Rp0gQgAAEKiHw1vDYM6U2ec4r\n3ywVMXKdB3h4sYQ5cHH9Mjvh+ZHbFs3xTSMlj28gX1cweV2XBkuw76hHmv2Kquxnh0p0i3ve\nBsl1fW24rsXq4ceV3vRvaHRcxeLIhwAEIAABCDQ3gVoZpEop0MWuUmLEQwACJnCQrvVlZh7X\nRX1+FzAvuytc7hmk/SvD1aaW9HVUbqFnhVyuBzTo0vowsbJy/czOYdq2UF2dt7UGaug6o7Iy\nK4rWjaseua/kABHJutyjOrgbYFhH+pHG81F3u94i9f2b8ts91PdCEgkCEIBAqxPIVBe7Vj+Z\naTl+DFJazgT1gEDTEeh+I4Q1dVHvlo/kxf6zWl5d+d3VtHBsrGGvte1XpP68cq/Wcm50vLOr\nQPU/MhVqeskfVMLP/nxf++rw8z9+uXe9klqOev4dwqYySX6GKMnLJnM57b9bA1TkkoxP18sh\n7KH6zsqLvV3L89scHRbFMoEABCDQ6gQwSK3+H1CH48cg1QEqRUKgRQisoot6dUubKIPxv9Lh\nunj/nKYTpG6/+LTaZ2Q03LVN0jLSt1WmW34+oHm3sLTdMQa2B2tbdXPbUgbjUJX5XWklGRMP\n/x12HEO55W6qZ5x6Hho2OB6y3Lz2lAnq0oh1XdeokOQw4+sqT/3+llD9DlDcT6RdZK48OEPH\nSYot0Q2x3OoQBwEIQCATBDBImTiN6ToIDFK6zge1gUCzEehShY+VoXlWRklmKfeCV73vp9Sz\nNmUdokdjuFJmS8/jTJTZavuPlj9f1palg9yFTYPTTLxVZV+vebfETJEalcxLI9V1XxTCpLtk\ngs7S8sclP1eVnxZQxoEyVeIwScaw42Qtb5MfxDIEIACBFieAQWrxf4B6HD4GqR5UKRMCEIAA\nBCAAAQhAoBEEMmWQsj6KnY3H5Cr+K27RNrqzSYIABCAAAQhAAAIQgAAEWolA1g3SV3Qy1Ye8\n4nSotsAgVYyNDSAAAQhAAAIQgAAEINDcBLJukPzA7/nSZtLfJT9UW056pJwgYiAAAQhAAAIQ\ngAAEIAABCDQbgR5V+DbJQ7Kul9LK8wxSSk8M1YIABCAAAQhAAAIQGJVApp5BaoUhSm2MNFpR\nLmnUJBIEIAABCEAAAhCAAAQgAIHCBFrBIPnIH5T87g0P2LCWRIIABCAAAQhAAAIQgAAEIACB\nlBKgi11KTwzVggAEIAABCEAAAhAYlQBd7EZFRAAEIAABCEAAAhCAAAQgAIEmJNAqXeya8NRQ\nZQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAE\nIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQw\nSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEI\nQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAA\ngdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQ\nMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAE\nIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQw\nSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEI\nQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAA\ngdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQ\nMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAE\nIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQw\nSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEI\nQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAA\ngdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQ\nMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAE\nIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQw\nSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEI\nQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAA\ngdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQ\nMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAE\nIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQw\nSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEI\nQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAA\ngdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQ\nMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAE\nIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQw\nSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEI\nQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAA\ngdQSwCCl9tRQMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQ\nMQhAAAIQgAAEIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQMQhAAAIQgAAE\nIAABCECg0QQwSI0mzv4gAAEIQAACEIAABCAAgdQSwCCl9tRQsRoTWKcjhL9MDOEJ6ZnOEP6u\n8j9Q431QHAQgAAEIQAACEIAABCBQAwL7qowhab4alEURIwl8qS2Ege1DW9/vQ+fQ8dKnQvts\n5+kOwW9HhpMDAQhAAAIQgAAEIFABgW7F+lp2swq2IRQCJQlgkEriGdPKLWyE/iRT1B965tE1\noWuoK4R+lb7PmPbAxhCAAAQgAAEIQKC1CWCQWvv81+XoMUh1wRpCTwhXu7Uo3xzFy4eHjiHF\nPF+n3VMsBCAAAQhAAAIQaAUCmTJIPIPUCv+yLXyMah7aco/QrsePCqdPho7QG8IUrV2hcAS5\nEIAABCAAAQhAAAKtRACD1Epnu/WOtWMwhK7JQZ3siqSF5ubz/NdcFsxBAAIQgAAEIACBliWA\nQWrZU98SBz4wIYSn7wqySUXSnXqeUB+C2Vr9RJEQsiEAAQhAAAIQgAAEWogABqmFTnYrHuqs\nEE44Mgz0vZwbWGVeAn3K+0GY3af+d+dpzdvzrmUJAhCAAAQgAAEIQAACEBgvAgzSUD/yE/TU\n4D3LhzDrCo1a1xu6cyPZ3a75TUJbr0axe0G7nlq/3VMyBCAAAQhAAAIQyDyBTA3SkPmz1SQH\niEGq74laQK1Ep3q4bxmifnW769PuPMT31ZouXd9dUzoEIAABCEAAAhDIPIFMGaTOzJ8uDhAC\nIcwYCGFvgfi2RrXbUJI3Cvdp+iRwIAABCEAAAhCAAAQgkCSAQUrSYD7rBF7WAV6e9YPk+CAA\nAQhAAAIQgAAEqifAIA3Vs2NLCEAAAhCAAAQgAAEIQCBjBDBIGTuhHA4EIAABCEAAAhCAAAQg\nUD0BDFL17NgSAhCAAAQgAAEIQAACEMgYAQxSxk4ohwMBCEAAAhCAAAQgAAEIVE+g1QdpWE7o\nVpVekh6RZkokCEAAAhCAAAQgAAEIQKBFCWS9BelLOq9nSBPzzu9aWr5Tmi79Q7pXel76rqRX\n5pAgAAEIQAACEIAABCAAAQhkj8BJOqQhacHEoS2j+TeifJuk4yWbqGeivKM0bXTiRbGNJs7+\nIAABCEAAAhCAAARqRSBTL4qtFZS0llPIIJ2uyto0fS2v0pO0HK/bPm9dvRcxSPUmTPkQgAAE\nIAABCEAAAvUikCmDlPUudoX+CTZX5h3S0Xkr39XyPtKr0rZ561iEAAQgAAEIQAACEIAABFqA\nQCsapMk6r/cXObcepOFhac0i68mGAAQgAAEIQAACEIAABDJMoBUN0t06nx6koVBaVJkbSR6w\ngQQBCEAAAhCAAAQgAAEItBiBVjFI7lLn54u+Jd0ibSjtIiXTslpwtzv3obwhuYJ5CEAAAhCA\nAAQgAAEIQAACWSDwCR3E+dLjkgdmSOopLcdpZ830S15/s9QmNTIxSEMjaZfel8/93hoX/l7d\nPejVmO8zJ4TwT+X5f4QEAQhAAAIQgAAEIDCSQKYGaRh5eNnN8VDfW0v7SydLp0hxcmvSW9IJ\nkkeza3TCIDWaeOH9tXeFcJY+4f3fDh1Dl4SuoQtC59A+oX1AZmlAmxxReDNyIQABCEAAAhCA\nQEsTwCBl8PT7RbK6Nh63hEEaN/Tz7Phbcsd998gY9YeeeXS58mSSZit613m2YAECEIAABCAA\nAQhAAIPE/0DNCWCQao604gLb5JBf+bVajvLNUbz8VbUkqbudXy5MggAEIAABCEAAAhCYSyBT\nBqlz7nExJwL7SV+WjpOOl6pN82tDDwhRbqvUutXuiO1qRmCaHkJb9CNBTx0VSVrXfmwYXF+r\n1ZgUBouEkQ0BCEAAAhCAAAQg0MQEMEjznrwltLi25OlYkg3SppLddDnJw4s7eaAI0vgQyJ0r\ntRAVTT1ao1E8PIiDXRQGqSgpVkAAAhCAAAQgAAEIZIVArQxSpTw20wYeQa9cQ1Vp+cSPTqBb\nrufd0zUoQ9ylLn/6E3W/k4HyiIgkCEAAAhCAAAQgAIG5BDLVxW7uYTE3ngQwSONJP9q3+s0d\nvVwIs14O3SNM0qPKU7Ngr0IPSEFVqQIEIAABCEAAAhBIEwEMUprORkbqgkFKx4lcQJ/uh5aX\nSTpXLUmvyBQ9L52o+UVkjtTF7hpVk26p6ThX1AICEIAABCAAgfQQwCCl51xUVZOFtdU0aVVp\nKWk+abwTBmm8z8Dc/U9WV7s/qjXJrUXu9jgkR/SOpodL5Q66oVASBCAAAQhAAAIQaBkCGKQm\nPNXrqc5/ll6Sche9edPHtHyCtJg0HgmDNB7US+/TLwz2/81akj/0JAhAAAIQgAAEIACBwgQw\nSIW5pDb3x6pZbIqe1Pwt0iXS36TLpdul5yXHvCL9j9TohEFqNHH2BwEIQAACEIAABCBQKwIY\npFqRbEA5n9Q+bHxshPz+mmLJQzdvJfkloI7fXGpkwiA1kjb7ggAEIAABCEAAAhCoJQEMUi1p\n1rms01W+u8/5FTblJD+f9JY0lpfElrOf/BgMUj4RliEAAQhAAAIQgAAEmoVApgySnkXPdPJL\nX2+Vess8ytcV92/JgzeQIAABCEAAAhCAAAQgAIEWI5B1g+RnizaQyh19zC1INlUPSyQIQAAC\nEIAABCAAAQhAoMUIZN0gnarzuZp0nrRJiXPrZ5C2lK6QPHrZhRIJAhCAAAQgAAEIQAACEGgx\nAll/6eUZOp+LS36HzUekZ6VnpFclP2s0WVpEWk6aKs2WDpRulkgQgAAEIAABCEAAAhCAAAQy\nSWAFHdWZkg2SR6lLyi8BfVT6lbSMNB6JQRrGgzr7hAAEIAABCEAAAhCoBYFMDdKQ9Rak+IQ/\nrplPRwtuNVpQmiD5xbFvSiQIQAACEIAABCAAAQhAAAKhVQxS8lS7a51FggAEIAABCEAAAhCA\nAAQgMA+BrA/SMM/BsgABCEAAAhCAAAQgAAEIQKAUAQxSKTqsgwAEIAABCEAAAhCAAARaigAG\nqaVO97gfrN9H5dECe2pck+VV3lZSOV1GF1LcYmXu/z2K87uxaplcRzOYWMtCKQsCEIAABCAA\nAQhAAAJZIpD1UexW1tAmF8qN9+mkDemlU/1ySFdqfp0xnsQzVc6Ay7TkvgZV9suaX7NAufsq\ndrrjLM077seSR11JJpu4H2i9B/CIY5/U/JckFV91WloFn94RwkyV4HIHtI9/arp51SWyIQQg\nAAEIQAACEEgHgUyNYpcOpNQiywZpYzWZvLN1aOu7KHQOPRi6hi6XdtayDFOvTv0OVZ7+h7T9\n4NdC++BNKu9+6RSVv7zy9AkdVJlmmksyJifLjPQfEjqG7lDcv6TfKVYvwOpV7M0K0upc6tbM\njWpi6v2N1jvuTulQbachD/tUzl+juEonq2nb19YPbb3nRgyuVrmfDu2z5bj87q09Ki2QeAhA\nAAIQgAAEIJAiAhikFJ2MrFQlqwapR4bj2b1lBPpC91B/6JlHB8rcyDy9oZPobm+VpMMUPHiO\nzEZ+ma9rP2uHtkEZErfUOH1G8/23yZDkx05XrN4iPEsxP89FhvBT9amb9USButpY6ZPfr7jP\nRbHlTtrF4MGdZAhnFij3SJmvyCguXW6BxEEAAhCAAARSRkAdJHI9MnyRjFqTwXw69+4hM+cG\nteZJEBgTgawapE/qQZu+1woYA5uVd5Wvh4FsUL5aCT19C8/YUSYo3/DEy/+UmVF51oe1//u+\nJSMWr8ufniSTJZP2tmInyEi9dUIB0xVv893hlqQHK6mrYreWARp4qggDG8dVhhkcWmG5hEMA\nAhCAAATSQGB+VeIdKf7tZdraLDJhkHRtSIJA3QhssImMzAJFHt3pUv4HQnvXGWFw/UpqoFtT\n8+0YOoo+D7RJaPcICENqQtpL7muND5aI1f7dx813PbZS89ACO2i5WHLskWFgNa3358Zd48pJ\nG8gA9U4NbQUHZWgTg51CR8+TYWDT3nJKIwYCEIAABCCQLgL+fZsk7Sk9ka6qUZsGEvD/wTUN\n3F9dd4VBqiteCocABCAAAQhAAAItQeBfOsr/tMSRcpCFCPhmc2ZS8dvlmTlEDmQcCdx9exhq\nn5FrdR9Zi37lXxXU+y2Ee0auLZ6jofDeuTwMuAm/YLpdYzSo9cgtTH/R4AoP/qNErPbv5iB3\nDbhRXexmXJkb36FgseFqrVN5D2ttua1HLuju/2oQiOeLMBhS/mVhoFetR7cV3iu5EIAABCAA\nAQhAAAIQaD0CWX0Gqa6DNJxd4HkhBmlovQ8PRwwBCEAAAuNKQI8T5+4Crj6utWDn402AQRrG\n+wxkcP9ZNUg+VSOG+b5CgygwzDfDfGfwc8whQQACEGhFAhikVjzrI48ZgzSSCTljJJBlg2Q0\nvCg2BF4UO8YPCZtDAAIQgEAqCWCQUnlaGl4pDFLDkWd/h1k3SPEZ1GM+YaqkVwPVNC2v0raS\nyhl0xO9c8pd5OUmvRQoLlxNYQYzraAYFR7WroBxCIQABCEAAAmkggEFKw1kY/zpkyiCVc0E5\n/sipQVYIeECG5+twMB5WtNyhRf1i2nLTK+UGVhDnAR7qwaCCKhAKAQhAAAIQgAAEIFCMAKPY\nFSNDPgQgAAEIQAACEIAABCDQcgQwSC13yjlgCEAAAhCAAAQgAAEIQKAYAQxSMTLkQwACEIAA\nBCAAAQhAAAItRwCD1HKnnAOGAAQgAAEIQAACEIAABIoRwCAVI0M+BCAAAQhAAAIQgAAEINBy\nBDBILXfKOWAIQAACEIAABCAAAQhAoBgBDFIxMuRDAAIQgAAEIAABCEAAAi1HAIPUcqecA4YA\nBCAAAQhAAAIQgAAEihHAIBUjQz4EIAABCEAAAhCAAAQg0HIEMEgtd8o5YAhAAAIQgAAEIACB\nKgmsqe1Or3JbNmsSAp1NUk+qCQEIQAACEIAABCCQTQJTdVg7S0tJL0qXS09KaUwXqFIT0lgx\n6gSBrBHYTAc0JHVn7cDyjmc9Le8lbZqXX2jxU8o8RNqq0MpEXpvmV5M2lBZO5I91dpIKcH3X\nkrJ+XsbKiu0hAAEIQKB1CSymQ/c1zOpVIPBv+I/UnalPhczaNLTNlFOaqczZyvu11nVUUWa9\nN3lUO3i63jtpwvLnU539f+BrWhIEakIg6wZp354Q3hEpf3By0vIszX+3AL2ztW4wjvNUy7M1\nPahA7H5dIbwcx+oLdUBO5iItL1sgttysyfpS/qPUG5erZlbX/XBJuyNBAAIQgAAEIJAgIG9T\ntUE6TE0xfWeEzqH+0DNHF2t5sn6H5Y6OT+ynmlkbsB2lwyQbrn2lVaRCyb2qdpUOkY6Qdpcm\nSnFSlcLeklu4Xovm82/irqH8A6TfSN+Q1pUKJfnA8HXpt9LBkvdbrFfX+7Tuq5LL/JG0h5TG\nFiwMkk4MqbYEsmyQfqRvp8HPhPbBu0PX0Juhe+h+TffTsvOF8ZgEyrud922te0hxjr1NsbuG\ntkF9STr2/+JYGZg/yAz1Hxk6hp5Q3BvS1YrdJLT1ysW8qrjl49gKpguozIe04axz9eX8isp8\nXjpR84voi1pG7RqVVewLrILdEAoBCEAAAhDIDIFqDdI0/ZbPPke/sUlzFM9fq990EfJvfzGT\nMRpA39R0Vz2X4xutNjae9w3Qr0nJtIIWbpe8/k3plWj+P5quLTmtLLk+jrE8f6YUp6M04/04\n/7loOqCp85PXDttr2TeJXYb3E9+QvVPz7mIYpwU1c7YU7+vlaN7Lj0hLSmlKGKQ0nY2M1CWr\nBmmqvp0GDpLhib/wktNfytxExmctncc9bY7+XOSLch+VIfPiL52FpA8oduA6fXkmy/P8TBma\nrUNbn8zMTZX+b+iL+ujl9KX1ssrIL/dR5c0//CV2QKXlEg8BCEAAAhDIMIFqDdIB+s2dmf97\nm1zeUF3uxO1nVbLbS9vZTPjm6gJRGe4GaPPicn094aRLimBzYjPzmWhZk/AByTdcbUZ0CTIn\nFepi93mt9b6ukJaIIt+jqXu1OP/AKM+TxyWbHdfFSZcXuWN03C+cEaVDNXXebyWX5fRe6RzJ\n+dVy0aZ1SRikumBt7UKzapCO1zfS4NsFDIe/AHuVv8yw6fEXyFNrqqUo+cWYnH9VsTJbNkhn\n6DbM+XuE9tnJ9cn5e4fvOvnLY+UK/q26ZdbePb2IQXP5P5GhU5u2v9hIEIAABCAAAQgME6jW\nIP1mR93QTP5+58//b2gf0s3L06oEbQPha4H3522/g5a/KsVG5lOad9zFUn76iTK87kuJFfkG\nyQbrdclmyq0+yWTT8Lw0Q/K8u8bZiF0vebs46b5u+L60Y5yhqY3RldKkRJ5nN5Bcp3O9kKKU\nKYOk/zsSBOpGYD11eQs983wHzN1Xu/K3Cbl/wdV1a2bx7UJ78stibqDmJitWBsp5G8gobbBV\naJefKZzWVJn6lPZp7VqFIwrmLq9vrIlbDtenYIDXqU18mlaqCiQIQAACEIAABMZA4JWnh81C\n0SKeCkN9ujP6ctGA0iuuiVb7Juyx0kckX8TbdLh7v7vcOW06PAnXaurudEm5i52TB4IqlpbT\nCrdGXSq5e14yvaOFCyS3Eq0m6TIi3CxtLd0ifVNyq1Cv9HPpcilOB2jGZu7dKMOtSFtIO0fL\n+cYpymZSCwIYpFpQpIxiBPrdhl0qRev9BTg4K3dDpHj0zOH1/YroKxU7qDh1Avb/tk1SuSkX\n62+uYsnfXrJovmvjuz8kCEAAAhCAAASqJ3DZAxqH6Z5c55CRhTyun9vrg3vih8tGri0rx4Zn\nH8m/2ftJNkpu5blE2kSK08rRjJ8Vui9PZ0brVoqmhSarRplPFlqpvDg/LuMTyrtOsjHzPm3C\nHpcOlXS/eE7ydczekmNfkWwUb5JsnJx0SUKqFwEMUr3IUq4JXHOHvuBeznmKkUDeVf6Vw1+M\nt8rQPH5RGNSzP/YfI9N05T8ynH2JjMr1F4TBoubnOsUqxv/bd4wsqWjOdDULvXpxCe+jdYNq\nA79HJcjPkSAAAQhAAAIQGAOBe/W7e+7HQn/vw3k/q0/qd/wjob+vc9gQXDWGfZyobadIbj06\nWnpGcgvMjdI2klN8b3RPzW9fRN9xYJHkViInt04VSgtEmfF+XtLytpKNlc3OFdJU6RAp2c3P\n9T1FWlY6W/q85O51q0skCLQEgc10lHYGyTsHWTjwLh1Q74f0bNE7ec8h+fmjPYcHXpA3yr2/\naG19EQ5+VXl9ebEezW5zlaGyHOu0um6b9P+uwPNCzyh2mr7sdMvpFAdWmL41Sa1O9xQY/OFy\n5bUP73/XCsskHAIQgAAEIJBlAovp4HwNU82F+yT9tl/i39ed9DzSN/Ws70dDW7+uB/p1Q9Kt\nJQuPAdxK2nanAtt/V3mu7wnRup9Hyx+OlpMTd52zaVomkZn/DNISWufybHQKpfOV6fXrSjZR\nW0g2R8m0qBaekRy3pLR4NP+gphOlZHqfFhx3ZTIzBfM+NtfL17QkCNSEQFYNkuF8SF9+A6vI\n4BwrQ3OljMafNF1Xy7pz5JaYzyYI/kFfioObad3JivmHYm2CdOskHsEu+eW1l0zS7F30RXqm\nYq5Q7OH6YtU3Wa/2d6fKdH/fSlO76nSWtu//tsq6RGVeoLI1gt6AvrzdRH9EpQUSDwEIQAAC\nEMg4gbEYpBjNDpo5TqbIJuPP0i7SWLuQ+dkfX7DvLCXTB7Tg/N9Emb4G8/XILZK79CXTaVpw\n7O6JTHeJey2x7NlbJZexoRcSaU3N++bu45KPZx3J5fk6JT/drAzHLiK5C6DjrpWSyWXEdbou\nuSIF8xikFJyErFUhywbJ58oPJt6jL77Z+mTb7NhwPKS8jb0yL+2pb6e3FJN7T5KGe/EXju+q\n+EsmP22ouItlqmao3H7F+q7OQZJ2VXXyl8/eul1zr+rol9TNVLn/VF7+F2zVO2BDCEAAAhCA\nQIYI1MIg1QPH+1Wob276GuJn0oek70v/T3J3t42kOJ2kGRsS/97vIe0mnSo57+9SMl2vBeef\nLH1ecnLXN3f9f0M6UNpO2l/yM0+WjVGcbHq8/YXS3pLN118k550nOalDS3hJct7hkq8TXa8L\npHekmZKfl0pTwiCl6WxkpC5ZN0gZOU0cBgQgAAEIQAACeQTSapBcTZuK6ZKNhuWbrg9Km0jJ\npHuiuRusNjjJ2HO1PCUZqPmtpRclxz0gxWk9zdwlxdu/q/mrpfWlZHJ3ujMktxbFsW9p3s8c\nqSPLnLSF5nzjN45x/MXStGhq8+fueGlJGKS0nIkM1QODlKGTyaFAAAIQgAAEWohAmg2ST4PN\nz9KSjcpkabS0rALc4jNa7BKKUSeTEcnbrS2pk0vJNL/WriGtLLn3SqHkuk+TXF6hfSk7NQmD\nlJpTkZ2KYJCycy45EghAAAIQgEArEUi7QWqlczGex5opg2RnSoIABCAAAQhAAAIQgAAEIAAB\nEcAg8W8AAQhAAAIQgAAEIAABCEAgIoBB4l8BAhCAAAQgAAEIQAACEIBARACDxL8CBCAAAQhA\nAAIQgAAEIACBiAAGiX8FCEAAAhCAAAQgAAEIQAACEQEMEv8KEIAABCAAAQhAAAIQgAAEIgIY\nJP4VIAABCEAAAhCAAAQgAAEIRAQwSPwrQAACEIAABCAAAQhAoDEENtZudpNGe5HsWGqzcLQP\nv4iWVAUBDFIV0NgEAhCAAAQgAAEIQAACVRA4SNucLy1YxbblbrJqtI+9yt2AuHkJdM67yBIE\nIAABCEAAAhCAAAQaSmCq9raztJT0onS59KSUxXSPDmqi1JfFg+OYIFBLApupsCGpns2tS6r8\nD0v+AvJ8rdLHVdAvpG9Ji5YotEvrTpRuk06X3PxbLK2jFU9Jb0n3S21SseRjmi69LF0qlUp7\naOW9ksv8XqlArVtW+oi0k7S4VIvk41hfctP61lKPRIIABCAAAQg0M4HFVHlfw6xexUH4d/FH\nIbTLLCw+K4TNZuoSRWqbrbxfa11HFWWySQibCoLPyZENhDFftE9f05IgUBMC9TRI71EzoZty\nB3U13m95Psp7zxhqv6/K6tX2Q/pEDOobLCct/0PKNzQ3y/kNKnNw/mgqtzSouP9I+alPdZsT\nq5Wut2N9RymZbFoG1Ec0t1/XQctDUewNyUDNb6b6DXj/3u+EKNZ10rpv5MUuqXwfw5Di+jRv\nXgPa/q+aTs6LrWRxO9VtujYYVF17Ve8BHecMLefvv5IyiYUABCAAAQiMN4GxGKTDQpggc3SW\nLuaHErpM85N1jdFxfJUHt5C221vapsj2m0XrF0ms189y2FU6RDpC2l1yS08y+Uawy11JWlf6\nmfQJyebAaar0dem30sGSy3O5ybS1FlyGLjPmSY6zsfm+ZGOzp6TLlhFJlybhU5L3bbmek6Rk\nKmWQ1lDgAdJvJF+D+Djy07bK+LjkfX1Z+oG0plQqmcGQZLYkCNSEgP+Z/E/lf8RapgVV4GNr\nhLbe60PXUF/ozsnzzvM67WzBKna4n43JZ0P74GMqsz/0DM3Q9M+hc0if0EGteyhR5oM2Jt8P\nHUMvRLGvaHqEll2G4p5LxOYMzG9VzhtR7DOafl37cRmKeyOO1TfG4ELS6Yp9J4p9WNPdFGuz\nprgbo9iVdJyD06TLddy9Ueztmt8ktA16neL2jWKX0PJzG4nNrVrv43L8PzS/YgiztO7fisv/\nsow2LTnZSfWf/dXQPvB0tH8f3x9Ud5VpA/aLkluzEgIQgAAEIJBeAtUapGlqJVJL0fm6/kma\no3j+Rl8X+Te60AX8aDR0KZC7vnhBU8/np0eV8ZKky4lcWkF/b5e8zzelV6J538hdW4rTBppx\njI2Jr0k8b71P2l6aFS17+95o/k5Nl5LidI5mvI25xUmXNLneLc537xnfQPW89580Uutp2XWP\n41xXzztvYylOxQzSUQoQ8xzX56LpgKbOTxq5i7X8pHS05PKtq6RSCYNUig7rqiJQF4MkA/K7\nafqwvhZdlPuCP5bzvM4xFda4Sy0h/fvIiMRlJac3yUxEZuZbKnc7fdoGfykzlIyJ50+VQdD+\n/eX3VclfTIMXKS9en5werP3ZFClmR+k1l/uvyMQk4zz/McVGLUkKDW8vqtjnCjCwsVpHJkll\n+cvB36CnrSlz9HaB2OeVt/jwF9+PHVtBmqh6v/ydIrwu0zGoLB/X+hWUSSgEIAABCEAgLQSq\nNUgHhDBN3eliQ1RoupHW58xINcfqm4/+jf1g3sbxNZdNgZMuW4JNjK8FPhMtaxI+IL0qPSLp\nfmYuxQapX0vnSjtJB+bWhPC4pi9Lq0fL82tqI+U6JG+EnhPlxQZJlyy5m7o2V/H+fTP2u1Hc\nDzR1ct7D0tvSpyRdQuXq/jFNbaqelSZLToUM0ueV77pcIS0hObkn0UWS8+Pj0Gy4WLKRel3a\nR/q0tJVUKs2nlS7HfEkQqAmB+MMafwBrUWi7LszfOrmI4bCR8DrHaGf+kJWbvmZTY8OQb0zi\n5V1lOmQ2/EXx/xZV7KwSsSsPmwN/oQxuqu3iMvKnbqHSN4ONxAxBGvx8EcPh7f6rWMVZV+q2\ny+CRRQyaYy+RQfHxKHYLTXsvLMHr1ypH5fkLqJK0qw3lmyUYbCFTpgJ/W0mhxEIAAhCAAARS\nQqBag6QuXjure10hYxTnfUG/5e2nVXmcq2o7Xwv8NW/7Y6P8taJ8mw3H2RTkp58ow+u+FK3Y\nIFp+RlMbmzjp8iBnsK7X1IYrTo75vuSbu3HKN0gf0Arvw13eksnlXCNdKelyLXxTctyPpPz0\nLWV43SHRinyD5LJsdmz4Foxi4omNzfPSDMnzTmbh8r7mhTKTt/U2mTBIuiYkZZTAYrq9scCG\n83xO5z1Sr3OMcuO7GPMGFF7aaCnlv6dEuZuE9jaZmCkKm7KB4jpKxL5P3kyf2gX9DbKZtiu8\nS7cvt+mWTG71RLeVb1QidnnF6RaKP6QbzvKfEv5P3ensjlzw/pp2l45td9v5koqtxMiutlpo\n6580XHdtOjJtHtq79c269sg15EAAAhCAAAQyS0Dd0J7K9eAofoRPykANvlx8fck1j2jtrdJu\nUnzh79/vPaS7pfslJ5sJp2sl/xYn5S5uThsOT+b8vU9zvrkZJ19u3CxtLd0i2cy8V3LMz6XL\npWJpvWjF+XkBvo7ZTtpB0uVaWEdyOn14Ms/f2ETm1zMOWk4z7sZ3qfRmnBlN39H0AsktXqtF\nefHk9nim1aYYpOye8Xd9aPmfguThJtb5w1FumuEmp1LJ5epT7Q9z/xulArXuNUUqdsDtuG/k\n7iIV30DrvTL3583hScHg2Vo3c3jNLJupt0rEJurnu0HilSt+eOu8v16nD4yr6mMrN70d1bto\n/Os6bhWaOB1FQ1kBAQhAAAIQyAqBy+RRdH/0niLH87jyr/PPuOKqTidpS5ujXaMS3CVuEenk\naNmTlaP5ozS9L09nRutWiqbx5Il4JjH9hOavk2y4XJbNlQ/iUKnUjdXY+DytuFJpVa30RUqh\nOD9P5Uuf/HoqK5e8rdOTw5MRf+P8/O0LHeeIjbOYgUHK4lkdPqYZ+tZ58Oww4A9TweR1arl4\nQCvfLhhQOPMvvpK/IdcrbWTAgD67Z6lc3Uq5S2tvvEvLT+U+zyNjZQz0xF+ueg/pFtLsC1Xm\nu0ViH9S6x4aL+Le+AYbODINFj+sSxUa3pL7dqW3OKhF7jiL1reWyvilez55T5Li8a5UzoDZu\n3xkqum/H5aUb9K0z8b4i5c5SUReEwT4ZJN+5IkEAAhCAAARahcC98g3nhrCLWlkezjtmX6/v\npNajzps0c1XeykoWz1Kwbxh/Jtros5q6VefMaNkTt/447SltX0TfcUAiqW4jkk3KtpLNyAHS\nFdJU6RDJXdaKpfim66RiAVG+b2a3SRMLxNmAuZtffCz5IfGN8LglLX+9exM55W9f6DiHI/kL\ngQYQ2Ez78EV3qTsM1VRjVznggfMLPFfjPK9TofFdlbLL1+2cR5dWm3c8gl38vJBHfPuing2S\nKRlUYau4QJmOQXXlG/TIdXGcp29p+QPK1wE71h/MbT3/cW3/bl6sB1h479xYF/sH1WGw0MAH\nD+iZokWHy4w8UrhK3yaDfyrA4BrFyvB4/y+6UKXPqe79Vyk/WVfP+3ktleMyt85FVvBHx3XR\nKqFtlkfkS5br4/yURvBRHV5QcW7aJkEAAhCAAASajcBiqrCvYVavouIyBd2XDI9m5+eRDlQ5\nu8kwdEo9NkcLV1Fm/ianKsMX+stJNgBnS8n0cy24/h9OZkbz7pZm07RMtLyBpo51C1Ey2Xhs\nIdkcJZMuScIzkrdZMlpxTrRsbk4/lLz+I17ISzZm50srSMdJjttUyk9rK8PrLoxWOMbLR0bL\nS0TLV0TL+RPvw/HrRits6Lw8OVouZ2IG3sbXtCQI1IRAvQySK3ewNLCLnoM5Rhf5luedF63T\npOK0qC76X9ctjEEPwe3hvX+uAQxsYiJztF+ixE/Z+Ni0HKyYExV7iKb6lojNUfKuzF02LNOk\nn0axB2mqT2cc+41Euc/aJK2nfXqUPBugL6ku3ldkeuIvM2/ysk3S9or9veKOl/ZQrPNkEv2l\nOSdp+Zc2Qp+UcXGch+LeIbT1OU9BX5kTWNnMQqrX3XJAvd+OjutwTfVtN0t1fVVFrVdZcURD\nAAIQgAAEUkNgLAYpPogdNCMD0KML+PY/a34XST+9NUnbqBRfuNsceLqjlEy+BvPN0lskXVrM\nk07TkrfZPcotZpDcTc5xd0ZxycnNWpgtuWufU75BWl953v+VXplINifutOMnG3S/OTcan/fx\ndymfzd+U53V7S075Bsl5t0rez4ZeSKQ1Ne/6PS7F5WKQEoCYHT8C9TRIPqrNdSF+tgzNU5bn\nnTfGw1Ux4UR9Yt9Qm+5sldurZX8xxH1pk8Uvr4XnFZd7Sati/QG1MfCXQn76tjIGHRPHa9km\n5r35gVo+XpoTq7q4XH+ZxB9wzc5Jf5X5GYjLVeUde/uctfPOeHjyCxX7tDRd35Z/1eqxmhjz\n2k/HdIv0vG6ZPajln0nvkUgQgAAEIACBZiVQC4NUz2P3NcFjkg3Es1K+CVJWOEny+n9Ke0i7\nSadKzrMhiVMxg+T110qOdyvO3pJN1V8k550nxSnfIDnfpjDel83hlyRfUzkveXP4/ChPrW65\nOroXUJz3R83H1z+FDJLr7uupN6QDpe2k/SVfj1nJ6zcMkoCQxp9AvQ3S+B8hNYAABCAAAQhA\nIIsE0m6QzPxHks3Gz71QIOkeajhIsnlwnOUbqedKU6Q4lTJIiyroDMmtMXEZbv05WvJN0jgV\nMkg2bT+U3pbibV/X/NelZHI5P5GScf9Py0dIsTnSbMEWJOf7Zu9dUryPdzV/tZR/wxqDJCik\n8SeAQRr/c0ANIAABCEAAAhConEAzGKRKjmpZBbs1ZXIlGyVi1aM+rCGtLCVNSyKk6KyN2krS\nqpI6sxRNLndFKfk4QdHgAit8bGtL3QXWVZs1nza08fI1LQkCNSGAQaoJRgqBAAQgAAEIQKDB\nBLJmkBqMLzO7y5RBslMlQQACEIAABCAAAQhAAAIQgIAIYJD4N4AABCAAAQhAAAIQgAAEIBAR\nwCDxrwABCEAAAhCAAAQgAAEIQCAigEHiXwECEIAABCAAAQhAAAIQgEBEAIPEvwIEIAABCEAA\nAhCAAAQgAIGIAAaJfwUIQAACEIAABCAAAQhAAAIRAQwS/woQgAAEIAABCEAAAhCAAAQiAhgk\n/hUgAAEIQAACEIAABFqVwAI68N0kvxy2lmms5W6syrhetXyZay2Pj7IgUHcCvCi27ojZAQQg\nAAEIQAACdSDQ7C+KXUNMhqRjasxmrOWeE9XLfJshZepFsZ3NQJw6QgACEIAABCAAAQhklsBU\nHdnO0lLSi9Ll0pNSI9Lb2sml0gM13tlYy71H9Zko9dW4XhQHgaYhkKYWpA5R20b6qrSPtJrU\n6LSGdni0dK70M2kJqVjaWitOlM6RvifNJ5EgAAEIQAACEGgMgbG0ILWpij8K7aGvffEwq2ez\ntpkdS4aZoS3MVt6vtc7XJKTmIODrL7fE+ZqWBIGaEEiLQdqkJ4TH9WDawAohvDsl6EtK/+zq\n/HqxpovU5EhLF9Kl1bfp23JwQWllaYKkzEHl/zFv08WU/4TyBvXNPLiSpObQQdV1tvIOyotl\nEQIQgAAEIACB+hAYi0E6rG1C6FvirI6hFYe652jKZZ1DbZNDr+zR8VVWeSFtt7e0TZHtfd3l\n9b62iWM3iWIXjdbp0iKsK/1M+oSUvAGry5PwQekX0lekZaXlJJfpVjCn/HKdt430Sc8orS99\nSzpS+rSkS7B50tZacnneVzLpcidsKn1f8rZ7SrokGpHeo5w9pB9LR0mu59pSvRIGqV5kW7jc\nNBikdXWbZtZeoX3286F7qD/05HRn6Bp6b2jrlfF4QOfHTb11S/rEPzJZJue80DnUF9XhbU2P\nDB1DMm02SSdFO+9Sfd7Qt9HgDapfXNdXFfuN0D5og6W4/etWUQqGAAQgAAEIQCAmUK1BmqZW\notlLnN85xxglTdKSN3YOaQf+PbdJqTS55ek56QWpUCvUo8p/SbKxWEPyvo6RnDaQvGxj9EY0\n7+X3SU6rSa9LzntZche416QTJOd9SHLKL9d550uul42Rj61f8jbWPZINW5zO0YzzzTdONl33\nS85/S5oRzf9H06SR2lXLrpvj3pRmRfMDmn5HqkeaT4V6f76mJUGgJgTG3SDpU3XHR0Nbf2w2\nktMXZDz0ie3VkdbrQ2WIX7SxuSlheJJ1OEomyS1EiltWOlFObfDxyEQl4zz/JZkk3YbxF5ab\n7kkQgAAEIAABCNSPQLUG6YDOaWFm0hTlz3dv1OaeLDYq1aRfaCNfsLulJ5nia66josx8IxMb\nJJsXd/XfSTowip2s6cPSK9K2UZ5vHruly/uydpSc8st1ng2Sr2Vszr4sLSxNkS6RvO33pTid\noxnnxQbJLUw3SjY7n5F8jeN9f1dy3A8kJ9fR5ulVaUPJBtHm5aOSr+XeldRRp+bJ+3A9zJcE\ngZoQiD+sahgZl2TTMXRvEXNi03GYDIpM1EN1rN1924a2wXyzEy/PlBnSeJn+Ujla3xCvf00m\nKF6XP31asYpz7J51rC9FQwACEIAABCAwfAHv393VK4Txm4k7t/Xlm6Lk8gJfaB9SK9NpFZYb\nh6+qGdfrr3FGND02yl8rWs43MrFBekbrbUqSaT8tuEybm2RSR5dcTxuvG80gOeZLyY01b3bO\nt4GKU75B+oBWOOY3cUA0tVG6RrpS6pI2la6QviDlp4uV4TLWzF9Rg+VMGSTdlCdBICwvBkOr\nh7aiLS5r5Z6YzLXe1AWXzNdS64X2ovvv1P5Xle4KQ6sqaIG1SsROUVx0+2R9Vfb0ulSYQiEA\nAQhAAAIQGAuBV2Y/Fdzlyxf1BdPsJ9XjfjDXVazg+lEyH9H6WyW/S8gX7+9IvhHt53Lulu6X\nSqX7tNItLslk8+R0wfBkzl/flD1PstkqJ92SFzQ9WvblS7G0XrQiaaKcZcOzXbTOk9ukDyWW\nzXdFyV0Vl4jyJ0VTJkUI2PGSIOA+tm1uLy6W3BYsN+0m27ok9Yeb8UIY8oe8aHox9x0QXpNB\n6o/mC8b2Ks7fgkovDE/4CwEIQAACEIBAyghc1n//UE/vPfYWI1P/40Nh5nVDHVpz2ci1Zeec\npEibIz+T47STpKcGwsleGCU9UWD9Ospz17sXC6x7ukBesaz86xN3m3MqdV3ufTuVs5+VFHec\n5J4/7lLnqW8YryI5Fb0hPbyav6VOBHRah8D9ur3wyl9yN3IKH/RJYaBPJmYsX1KFC45y9fV4\n5YW6TfT6sAkaEXur1kXfCCfP1J2fU8PA0OwisX/L9a7LFXHKiILIgAAEIAABCEAgDQTuVXvO\nuc/vMru37+F574/2PzkUnt+pv093Zm9SRa8aQ2XP0rY2CH5mx+mzkluFzvTCKMnPMuent5Xh\nFhn1+h+RFhyRUzyjsCssHu81NmZOo7X+rKaYO6R9pMekQ6SdpSmSTRIJAk1DYLyfQTKoL6iF\nqP9ijSCXfKanV8/z7K/nfTqGv2BWqCPRiWr37t1SzyG9kjf4wn/0bNSSeqZI30j+oDutpvmB\nz6he7+TFXq9YfXP4i8f9b0kQgAAEIAABCNSXQLWDNLhWk2SSLvFodpP0PNKCB7YPTdqtrV/G\nSJciOXPkQQzGmk5VATY7y0luqTlbSiZ3i7NDOybKjJ9BOioZFM27VcaxWxRY99doXTnPIC2a\nt70bLFzutYn8c6I883X6oeSYj3ghL31Hy+565+u0YyXH7S3lJ5tNr9s8f0UNlt1S57J9TUuC\nQE0IpMEg+UB+Ig2+X8N6/0iDMnxbmqYvExmnGcrfTqp3ep9MUp9uwQx+UebnUO1/D021f5uj\nl7Tz5BflXjZJU7XuAMUdIu0oc6U240F9y3hIcpqP6322KB8CEIAABCBQ/SANSXY7aOE4maIr\nZJb+rPldpFr9jm+jsnzh7hunnsYGRrO5VIlBcjc334S9RkoO4OBnnt3Ckyw/v1ytzpkYx1Rj\nkLwP7/tKKZkma+FNyY9BuE6XS97HVlIy+Rkmt4B53dbJFTWaxyDVCCTFzCWQFoPkGvnOyXET\nQ7h9QgjXaf7HUnz3QrN1T262Pk3m50XV4W21XD2p5Z8V2esyyr9U9XxVsTP0TfqwlvcrEks2\nBCAAAQhAAAK1JzCWFqTa12ZkiTZa7oFiY/CspEuLeVK+kfF1kGMLtSB5Q+d7/f3SEdKfJHfj\ne1ly/gclp/xynXe+5JhqDJK3t3n09n+XdpG+JN0pOe8bktNBkpfvlj4tubXou5Lr96rkdbtJ\ntU7zqUCX7WtaEgRqQiBNBqkmB0QhEIAABCAAAQi0BIG0GySfhB9Jvnj/uRfyUr6RGc0geXMb\nk5slt9zcK31FOlzyPt4nOeWX67yxGiSbO3e1i1uCvL/Xpa9LcXKMuwLOlrze8qAQ+0obRsvH\na1rrhEGqNVHKy7lt/wOrhxkJAhCAAAQgAAEINA2BZjBItYI5vwrKb4GKyz5GM76W8yAJ9U5+\nZmklaVVJTyIUTJOV66G9lyy4tvaZGKTaM235EmlBavl/AQBAAAIQgAAEmpJAKxmkfXSG+qQv\n5J2pKVp+TfIbU2xeWjFlyiAVc52teGI5ZghAAAIQgAAEIAABCBQjcLVWzJKOlHifNV0AABY2\nSURBVNxS5G527kq3h+QWmz0lD6RAggAEakCAFqQaQKQICEAAAhCAAAQaTqCVWpAM16PD3SXF\nz/f0av52aXeplRMtSK189jl2CEAAAhCAAAQgAIGWJXCjjtyDHSwiTZU8Qp5blUgZIkAXuwyd\nTA4FAhCAAAQgAAEIQKAhBPzMkUXKIIFWfZAsg6eSQ4IABCAAAQhAAAIQgAAExkoAgzRWgmwP\nAQhAAAIQgAAEIAABCGSGAAYpM6eSA4EABCAAAQhAAAIQgAAExkoAgzRWgmwPAQhAAAIQgAAE\nIAABCGSGAAYpM6eSA4EABCAAAQhAAAIQgAAExkoAgzRWgmwPAQhAAAIQgAAEIAABCGSGAAYp\nM6eSA4EABCAAAQhAAAIQgAAExkoAgzRWgmwPAQhAAAIQgAAEIAABCGSGAAYpM6eSA4EABCAA\nAQhAAAIQgAAExkqgc6wFsH1NCXTXtLTChXUVziYXAhCAAAQgAAEIVExgUrTFApouVPHWbJA2\nAkOq0OwqKjV/FdukdhMMUjpOTX9UjRnpqA61gAAEIAABCEAAAhURuK2iaIKzSqAvCwfWloWD\nyMgxbKjjqHfrzqHahx3+KRIp/QQWVxUPlw6S3kx/damhCHxZekP6GzSagsCyquUPpa9LvU1R\nYyp5gBA8KV0AiqYgsIpq+W3pi01RWyppAt+VrpFOkSpNNkd3V7oR8RAYbwKnqAIWqTkI+IfF\nTd1Tm6O61FIEzpP+AImmIbCBaurPWKa6hjQN/eoqeqU2O6K6TdlqHAhso336M0ZqHgK3qqrf\na57q1qemDNJQH66UCgEIQAACEIAABCAAAQg0IQEMUhOeNKoMAQhAAAIQgAAEIAABCNSHAAap\nPlwpFQIQgAAEIAABCEAAAhBoQgIYpCY8aVQZAhCAAAQgAAEIQAACEKgPAQxSfbhSKgQgAAEI\nQAACEIAABCDQhAQwSE140qgyBCAAAQhAAAIQgAAEIFAfAhik+nClVAhAAAIQgAAEIAABCECg\nCQlgkJrwpFFlCEAAAhCAAAQgAAEIQKA+BDBI9eFKqRCAAAQgAAEIQAACEIBAExLobMI6U+Xq\nCfRVvylbjgOB+Hz1j8O+2WV1BHzO4vNWXQls1UgCPleD0uxG7pR9jYkAn7Ex4Wv4xv794jux\n4djHtEOfL647xoSQjZuNwCKqsEVqHgIrNU9VqakILCYtCImmIrBiU9WWyi4hBPODoWkItKmm\nfMaa5nTlKrqk/k5sripTWwhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQ\ngAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAAC\nEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAA\nAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhA\nAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEI\nQAACEIAABCAAAQhAoIkJtDVx3al6dQQ+qs0elR6sbnO2ahCBFbSf1aQu6WHpEYmUXgILqGrr\nSwtLt0vPS6TmIbCtqjpLuqV5qtxSNZ2so/Vnq1B6R5mvFFpB3rgT8O/XWpJ/z56Q7pUGJVJ6\nCNgHTCujOs8ppreMOEIg0JQE9lWth6QDm7L2rVHpKTrMCyWfp6Su1bJ/ZEjpI/BpVellKXm+\nfKG9ePqqSo0KENhJeT53/yiwjqx0EDhW1Uh+vpLzZ6SjitQij8CHtfy6lDxXd2l55bw4FseX\ngG/uJc9RsfmNx7eajd97Z+N3yR7HicCu2u8x47RvdlsegXaF/U3aWjpbOkV6V9pL+l/pImlD\nyXe6SekgsJWq8VfpCelg6Vbp49L3pP/f3r0A21bXdQAv5CUooEACSo0SQmqIQROPMEbQ8TFa\n0yhWVjhCRlg442vGmRoZsgypiHLSHLMoCM1HOYqhZBkmUYyGQkpogS9GMUZBUhC1vt9799Lt\nnn0O995z9jnrnPv5z3zvWuu/9uO3Puuee/Z/r8f9YPKYxLduQRhpOzB1vXGktSnrOwJHZ/au\n5A3f6fr23Ie+PWdmLAJPTyHvSHqmyvOSW5LnJ/2S9u1Jj7bfm2jrL/D1lHDhEmX0S77nJD0j\n4r+XeIxuAhtWYP9UfknSbwX6wbpTR5CCMMLWgVH3T48+zLbL09F1z5pdYXldBd6Vd+9+edpM\nFX826X/iTL/FcQn0Q9xtSfehI0jj2jdDNf3iqIOjfxw6TEcvcG0qvDM5fKbSN2e5P2snz/Rb\nHKfA21JWv+A7fpzlqYrAygR6PUT/QeoRiR6J6LwBUhBG2E5PTTcnZ86p7WfS1333ijnrdK2f\nQL8RPT+ZvZ7zF9LX/XVOoo1ToN9odx/1usxOr0i08QkckZK6fy4YX2kqmiPwE+nr/upR9Nl2\naDpOSXpkQhu3wM+mvO7Hc8ddpuoI7LjAH+epp06e/oxM+xfeAGkCsoEmPX2r++7nN1DNO2up\nHSz1NJLur0fvrAgj3+5+s92jEq9J9ky6rwyQgjDC9uzU1P3TL4lOSH4tOT3pwEkbn8CLUlL3\nV0+ja9s3OTHp6azaxhA4KGXenvxnssfGKFmVBFYmYIC0Mr/1evYBeeMvJnck/YdLG6fAo1LW\necmHk28mL0m08QnsmpL+Lbkx2SsxQArCiNurUls/cN80mXa+6c/Y7yfdn9p4BLpPun8enrwz\n6X4a9llP2do/0cYtcHHK6z47bdxlqo7A6gkYIK2e5Vq90t55o2uS/mN1xlq9qffZIYHX51nD\nB4HeSv+Hd+hVPGnRAr+ZN+gF4j86eSMDpEWLr+z1r8jT+3N1VfKU5GGT6Q2Ztv/XE208AsN1\nRv2i6CNJf2/1KOBwd9YPZn72lOR0aSMReFDq+Fpya7LbSGpSBoGFCxggLZx4Vd+gR456w4Z+\nCLhoVV/Ziy1CoB/cHpL02pbrk34I77w2HoGeovWN5BVTJRkgTWGMcPak1PS8pPtpuvVo+peT\nu5N+kaSNQ+DvUkZ/Z30smd1nHeR2XQdM2jgFzklZ3UfnjrM8VRFYjIAB0mJcF/Gqh+VFexSi\n/1C9chFv4DUXKtBrj7rvOlDSxiHwwJTRW9X2m+19kp5e1zw46b66crK8e6baxhB4S8rsvhuO\nBm6Mqjd3lb1tfvfJC+Zs5tmTdX8wZ52ucQgMX+4dMo5yVEFgbQQMkNbGeaXv0v8759akRyB6\nlzRtYwpck7L7QeH7N2b5m67qx0/2R/fJcrls02355t2g3oSo+/KUzbuJG27Leh1m98kz51T+\nyMm6S+es07X+AsdN9s9fr38p61+BixvXfx+ogMC0wLFZeE/Sc3+flrw30cYp8ICUdV3y6eQJ\nc0r81qTvrjnrdK29QL90+KM5b9vfg7+SdD++I+kRJm0cAj3q9/7knuTHk+FnKrNb2pGTae+2\npY1D4OOTMnoXu7fOlHTwZPnamX6L4xAYvmjov4MagZ1KwBGkce/u+6e8m5OeU3/8uEtV3UTg\nQ5n2Lk2PmxHp/mv/v8/0WxyfQK+T6DfeV4yvNBVFoKf8dP/M3lHrxPR1wPS+RBuPwO4ppV82\nfC556ExZwymRx8z0WxyHwCUpoz9rjx1HOaogsHYCBkhrZ70j73RentR/nPqLpXf8mZcz06+N\nR6DfavdUyNuS85N+A/fS5I7knmR24JQubWQCBkgj2yEz5fRnql82/E/ye8mpycuSryS3J0cl\n2rgETk85Hbz2Rg1nJU9Kelpdf79dkGjjFOjR897Exv99NM79o6oFChggLRB3FV66Rxv6C2S5\nXLQK7+MlVlegH9huTKb3279k2bdwq+u8qFczQFqU7Oq97lPzUjclw89YP8R9IOn/taONU6D7\n7FPJsM96iuurE7f4DsII2y6p6avJcIrkCEtUEgECBAhsRIGeTtK7ae23EYtXM4ENINBrWHpt\ny14boFYlbhU4KJMjYRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAA\nAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAA\nAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAA\nAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAA\nAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAA\nAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAA\nAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAA\nAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAA\nAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMC6B\n7x1XOaohQIAAgXUWeHref9eZGr6Z5TuSLyYfm1m31osPyhuenNyU/EeyVNslK34yuSu5cqkH\nbZD+H0udhySXJ1/fIDUrkwABAgQIECBAgMCmEOiA4v+WyY1Z96wVbOluee5Lk2fv4Gscl+e1\nvvPv4/l7Th73ift43JhWL2Xz9sm27D+mYtVCgACBzSow+y3hZt1O20WAAAEC2y7w1Tz07KmH\n92yDPZITkl9MLk2+kFyVbG87LU94dXLm9j5xJ3g8m51gJ9tEAgTGL2CANP59pEICBAistUBP\n47p4zpv+SfpuSDrAeWGyIwOkPE0jQIAAAQLjFTBAGu++URkBAgTGKHBJiuoAqdfFzLbD0/GE\n5IjkluT9yUeToZ2UmaatR6O+kfxNcmfSdkByStLn75d8MvnnZPo1srjQdl/b0Dc/OTkweUvy\nI8nJyUOS65KeDndPMtsOS8dTkoOTq5N3J89I7p3M35dNHralHZM/a1Sfa5K/T3rETyNAgAAB\nAgQIECBAYAECvQbpS8u8bgc2vQboppnHvDjLHRh8K/lM0sFPb+7wW8lwQ6Cemjd9fVMf28FQ\nW2+o0JtAdH1vCHH3ZL6v8bJkaIu8BmlbtqF1dBB0a/KipNvQQc6wXR/O/IOT6fbaLHR9H3fb\nZP7Nmf5X0kFO23I2fb8+/6Kk71fn4f06gNw70QgQIECAAAECBAgQWIDAcgOkDnQuS/rh/M+T\nofXOd+37p+SQSecDM/2rpP2nT/o6eU7SvjO6MGn7ZHpncntybHK/pB/6fyrpYKBHSPZN2hY1\nQNqebeiApQOVDnbOSnpnvYOSdyXdtpcnQ/vlzLTvL5JhIHNi5jvAav+/JkObZ9N1wwCpDj+d\n9AYUP5S8O+lr9KYXGgECBAgQIECAAAECCxDoAKlHb86byisz//rk+qQfyDuYOTQZ2o2ZaX9P\n/5puHRD0Q30HA8NRpHmDgA56rkimB01Z3NLemT/72o/ZuriwAdL2bMMwYOngZ7o9KgutteuH\n9oXMfCrZY+iYTE/LtI/dngHSC2Ze49TJa7xxpt8iAQIECKxAYNcVPNdTCRAgQGBzCvTD/G/M\n2bSvpO+tSY9Y9DS6tl4Lc0TyieTe5Khkul2bhccnPbL0uekVU/M9zezJU8u7Zf6w5Oik1/a0\n7bV1spA/d3Qbrp6p5pbJ8j6T6cMy/b7kdUmPhE23DqJ6+uD2tDpNt6uy0EHWI6Y7zRMgQIDA\nygQMkFbm59kECBDYjAIdCJ04tWE9naxHgeZdm3T45HGdfmQyP2/yg+lcaoDUx3f9i5OTJ/P9\n/dT3bS1twxGorUur++eObsPnZ8q4e7K8y2T62Mn0szOP62Kv0Zp9/pyHfVfXp79raet/GtsB\nUk9J1AgQIEBglQT6C0gjQIAAAQLTAj2ycf10xzLzw6DgPXnMBcs87oZl1h2ZdT0a0+uW+jp/\nmVyX9OjTucnZySLbjm5DB3DLtZ6u2DZ704atvVuvq1pu0Dg8bpje1/sNjzMlQIAAgRUIGCCt\nAM9TCRAgQGDLrbh7FOOA5H1zPHo78A64hiNBcx7yPeekszc6eG5ycTLdHjlZWORRkk/mPVa6\nDdM1D/M3TmaGI0lDf6eHJQ+Y7jBPgAABAuMQGE4DGEc1qiBAgACBjSbwtRT83uSY5KkzxT86\ny1clf5p0ANLW65Ta9t462fLnwyfzN0/1dfZxyfGTvt0m00VMtncbtrWG3qCh1xqdkjxx6kkd\n7L1qanmYnWczrDMlQIAAgTUScARpjaC9DQECBDaxwAuzbT0l7m3J7yQ9Xa6Dm+cnHQyckQwf\n/m/LfNuvJg9NXpP8Q/Lk5MLkd5Pe9e2k5CVJb27QwdRSp6ll1ZYbQ/T6p48ms0drDk7f3ybz\n2pfT+dzJiu3ZhnmvtVTfy7PihOTy5LLkM8mTkmFQOH3a3DybPl4jQIAAAQIECBAgQGCdBHrd\nzJd24L17HVGPFvV0uh4taj6bnJ5Mt34x96akA6Y+5pnJ/ZLXJr1xwfDcz2f+l5JjJ32vy7Tt\nuKSPOb8Lk3ZUpu3rIGloe2ZmeK2lpn2P6XZkFrZlG3pUqK+5//STM9+zMtrfAd90693sOji6\nOekgqAPJRyR97JXJ0ObZdN1S79d19f5AZzQCBAgQIECAAAECBMYnsFdKOjr5gaQDn6Xa/bOi\nt8Cebvtkoc/tLcHXs23rNmxLjfst8aAD098B0pvmrJ9nM+dhuggQIECAAAECBAgQILCxBHoU\n7ePJ7jNl/3aWO0DqqX0aAQIECBAgQIAAAQIEdgqBP8xWdiDUG1mclfxc8oakpxhenfTW5hoB\nAgQIECBAgAABAgR2CoEeObow+d+kA6Wm//fRpcm+iUaAAAECBAgQIECAAIGdTmC3bHFvzHDo\nTrflNpgAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBBYA4H/B5fzSPcHgsubAAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title “Iris data”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(iris[,3], iris[,4], pch=21, xlab=names(iris)[3], ylab=names(iris)[4],\n",
    "     bg=c(\"red\", \"blue\", \"green\")[as.numeric(factor(iris$Species))],\n",
    "     main=\"Iris data\")\n",
    "legend(\"bottomright\", pch=21,legend=levels(iris$Species),pt.bg=c(\"red\", \"blue\", \"green\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Training and testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>Sepal.Length</th><th scope=col>Sepal.Width</th><th scope=col>Petal.Length</th><th scope=col>Petal.Width</th><th scope=col>Species</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>23</th><td>4.6       </td><td>3.6       </td><td>1.0       </td><td>0.2       </td><td>setosa    </td></tr>\n",
       "\t<tr><th scope=row>135</th><td>6.1       </td><td>2.6       </td><td>5.6       </td><td>1.4       </td><td>virginica </td></tr>\n",
       "\t<tr><th scope=row>79</th><td>6.0       </td><td>2.9       </td><td>4.5       </td><td>1.5       </td><td>versicolor</td></tr>\n",
       "\t<tr><th scope=row>67</th><td>5.6       </td><td>3.0       </td><td>4.5       </td><td>1.5       </td><td>versicolor</td></tr>\n",
       "\t<tr><th scope=row>105</th><td>6.5       </td><td>3.0       </td><td>5.8       </td><td>2.2       </td><td>virginica </td></tr>\n",
       "\t<tr><th scope=row>130</th><td>7.2       </td><td>3.0       </td><td>5.8       </td><td>1.6       </td><td>virginica </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllll}\n",
       "  & Sepal.Length & Sepal.Width & Petal.Length & Petal.Width & Species\\\\\n",
       "\\hline\n",
       "\t23 & 4.6        & 3.6        & 1.0        & 0.2        & setosa    \\\\\n",
       "\t135 & 6.1        & 2.6        & 5.6        & 1.4        & virginica \\\\\n",
       "\t79 & 6.0        & 2.9        & 4.5        & 1.5        & versicolor\\\\\n",
       "\t67 & 5.6        & 3.0        & 4.5        & 1.5        & versicolor\\\\\n",
       "\t105 & 6.5        & 3.0        & 5.8        & 2.2        & virginica \\\\\n",
       "\t130 & 7.2        & 3.0        & 5.8        & 1.6        & virginica \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| <!--/--> | Sepal.Length | Sepal.Width | Petal.Length | Petal.Width | Species | \n",
       "|---|---|---|---|---|---|\n",
       "| 23 | 4.6        | 3.6        | 1.0        | 0.2        | setosa     | \n",
       "| 135 | 6.1        | 2.6        | 5.6        | 1.4        | virginica  | \n",
       "| 79 | 6.0        | 2.9        | 4.5        | 1.5        | versicolor | \n",
       "| 67 | 5.6        | 3.0        | 4.5        | 1.5        | versicolor | \n",
       "| 105 | 6.5        | 3.0        | 5.8        | 2.2        | virginica  | \n",
       "| 130 | 7.2        | 3.0        | 5.8        | 1.6        | virginica  | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "    Sepal.Length Sepal.Width Petal.Length Petal.Width Species   \n",
       "23  4.6          3.6         1.0          0.2         setosa    \n",
       "135 6.1          2.6         5.6          1.4         virginica \n",
       "79  6.0          2.9         4.5          1.5         versicolor\n",
       "67  5.6          3.0         4.5          1.5         versicolor\n",
       "105 6.5          3.0         5.8          2.2         virginica \n",
       "130 7.2          3.0         5.8          1.6         virginica "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rowsTrain=sample(1:nrow(iris),round(0.75*nrow(iris)))\n",
    "train = iris[rowsTrain,]\n",
    "head(train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       " randomForest(x = train[, -5], y = train[, 5]) \n",
       "               Type of random forest: classification\n",
       "                     Number of trees: 500\n",
       "No. of variables tried at each split: 2\n",
       "\n",
       "        OOB estimate of  error rate: 5.36%\n",
       "Confusion matrix:\n",
       "           setosa versicolor virginica class.error\n",
       "setosa         42          0         0  0.00000000\n",
       "versicolor      0         34         2  0.05555556\n",
       "virginica       0          4        30  0.11764706"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "iris.rf <- randomForest(train[,-5], train[,5])\n",
    "iris.rf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "            \n",
       "pred         setosa versicolor virginica\n",
       "  setosa          8          0         0\n",
       "  versicolor      0         13         0\n",
       "  virginica       0          1        16"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pred=predict(iris.rf,iris[-rowsTrain,])\n",
    "\n",
    "table(pred,iris[-rowsTrain,5])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       " randomForest(formula = Species ~ ., data = iris, mtry = 2, ntree = 200,      subset = rowsTrain) \n",
       "               Type of random forest: classification\n",
       "                     Number of trees: 200\n",
       "No. of variables tried at each split: 2\n",
       "\n",
       "        OOB estimate of  error rate: 5.36%\n",
       "Confusion matrix:\n",
       "           setosa versicolor virginica class.error\n",
       "setosa         42          0         0  0.00000000\n",
       "versicolor      0         34         2  0.05555556\n",
       "virginica       0          4        30  0.11764706"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# And I can tune RF parameters \n",
    "\n",
    "fit=randomForest(Species~.,data = iris, subset = rowsTrain, mtry=2, ntree=200)\n",
    "\n",
    "fit"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Variable importance list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ikgIK1S37kJECBAgAABAgQIEGhKQEBq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\nkalCmQEAAAAASUVORK5CYII=",
      "text/plain": [
       "Plot with title “”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wVIL <- randomForest(Species ~ ., data = iris, subset = rowsTrain, mtry=2, ntree=200,importance=TRUE)\n",
    "varImpPlot(wVIL, type=1, pch=19, col=\"blue\", cex=0.7, main=\"\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "?varImpPlot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "3.3.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}