SMLHomework/SML-ComparisonLearningMethod.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Comparison of differents Learning Methods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as pyplot\n",
    "import seaborn\n",
    "import pandas\n",
    "\n",
    "# Insert the working directory here.\n",
    "workspace = \"/home/toshuumilia/Workspace/SML/\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Basic Comparison: Decision Tree vs Logistic Regression vs Neural Network"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Explanation of Figure 1*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAx8AAAFOCAYAAADn6aDeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa3727a1a20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Basic Comparison Experiment #\n",
    "\n",
    "experimentBasicMethodsDF = pandas.read_csv(workspace + \"results/experimentBasicMethods.csv\")\n",
    "\n",
    "seaborn.set_style(\"whitegrid\")\n",
    "pyplot.figure(figsize=(10,5))\n",
    "seaborn.barplot(x=\"Value\", y=\"Measure\", hue=\"Method\",\n",
    "                data=experimentBasicMethodsDF)\n",
    "pyplot.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "pyplot.ylabel('Measure', fontsize=12)\n",
    "pyplot.xlabel('Value', fontsize=12)\n",
    "pyplot.xlim(0.5, 1)\n",
    "pyplot.title('Figure 1: Comparison of learning methods with default parameters', fontsize=15)\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Decision Tree : Optimize the parameters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Maximum Depth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvoAAAE8CAYAAACxRhXhAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAEyIog8AAACYEEUfAAAAMKH/B/YkhOM5nwJeAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa3729f7ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Max Depth Experiment #\n",
    "\n",
    "experimentDTDepthDF = pandas.read_csv(workspace + \"results/experimentDTDepth.csv\")\n",
    "\n",
    "seaborn.set_style(\"whitegrid\")\n",
    "pyplot.figure(figsize=(10,5))\n",
    "seaborn.barplot(x=\"Value\", y=\"Measure\", hue=\"Depth\",\n",
    "                data=experimentDTDepthDF)\n",
    "pyplot.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "pyplot.ylabel('Measure', fontsize=12)\n",
    "pyplot.xlabel('Value', fontsize=12)\n",
    "pyplot.xlim(0.5, 1)\n",
    "pyplot.title('', fontsize=15)\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Splitting Quality Criterion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxQAAAE8CAYAAABZ4/fjAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa372a0a400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Criterion Experiment\n",
    "\n",
    "experimentDTCriterionDF = pandas.read_csv(workspace + \"results/experimentDTCriterion.csv\")\n",
    "\n",
    "seaborn.set_style(\"whitegrid\")\n",
    "pyplot.figure(figsize=(10,5))\n",
    "seaborn.barplot(x=\"Value\", y=\"Measure\", hue=\"Criterion\",\n",
    "                data=experimentDTCriterionDF)\n",
    "pyplot.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "pyplot.ylabel('Measure', fontsize=12)\n",
    "pyplot.xlabel('Value', fontsize=12)\n",
    "pyplot.xlim(0.5, 1)\n",
    "pyplot.title('', fontsize=15)\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Minimum number of Samples to Split a node"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAyIAAAFCCAYAAAANJmktAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nam0CAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa371bcbba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# MinSampleSplit Experiment\n",
    "\n",
    "experimentDTMinSampleSplitDF = pandas.read_csv(workspace + \"results/experimentDTMinSampleSplit.csv\")\n",
    "\n",
    "seaborn.set_style(\"whitegrid\")\n",
    "pyplot.figure(figsize=(10,5))\n",
    "seaborn.barplot(x=\"Value\", y=\"Measure\", hue=\"MinSampleSplit\",\n",
    "                data=experimentDTMinSampleSplitDF)\n",
    "pyplot.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "pyplot.ylabel('Measure', fontsize=12)\n",
    "pyplot.xlabel('Value', fontsize=12)\n",
    "pyplot.xlim(0.5, 1)\n",
    "pyplot.title('', fontsize=15)\n",
    "pyplot.xticks(rotation='vertical')\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Maximum Number of Features considered when looking for the best split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxcAAAFCCAYAAACD/CBRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa371bf7710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# MaxFeature Experiment\n",
    "\n",
    "experimentDTMaxFeatureDF = pandas.read_csv(workspace + \"results/experimentDTMaxFeature.csv\")\n",
    "\n",
    "seaborn.set_style(\"whitegrid\")\n",
    "pyplot.figure(figsize=(10,5))\n",
    "seaborn.barplot(x=\"Value\", y=\"Measure\", hue=\"MaxFeature\",\n",
    "                data=experimentDTMaxFeatureDF)\n",
    "pyplot.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "pyplot.ylabel('Measure', fontsize=12)\n",
    "pyplot.xlabel('Value', fontsize=12)\n",
    "pyplot.xlim(0.5, 1)\n",
    "pyplot.title('', fontsize=15)\n",
    "pyplot.xticks(rotation='vertical')\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Maximum Number of Leaves allowed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After 260, no real change."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0MAAAGOCAYAAABVKdisAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa372b1c320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# MaxLeafNodes Experiment\n",
    "\n",
    "experimentDTMaxLeafNodesDF = pandas.read_csv(workspace + \"results/experimentDTMaxLeafNodes.csv\")\n",
    "\n",
    "seaborn.set_style(\"whitegrid\")\n",
    "pyplot.figure(figsize=globalFigsize)\n",
    "seaborn.pointplot(y=\"Value\", hue=\"Measure\", x=\"MaxLeafNodes\",\n",
    "                data=experimentDTMaxLeafNodesDF)\n",
    "pyplot.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "pyplot.ylabel('Measure', fontsize=12)\n",
    "pyplot.xlabel('Value', fontsize=12)\n",
    "# pyplot.xlim(0.5, 1)\n",
    "pyplot.title('Insert Title', fontsize=15)\n",
    "pyplot.xticks(rotation='vertical')\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Minimum Impurity Decrease to split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0MAAAGCCAYAAAAi6xjXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAIABJREFUeJzs3Xd4VFX+BvB3esqk90ZCSCABQgu9\niASwgHRE3FXsBcWyFhTdBcUVBF0x64ouYoWV3yKCLoQVFlCa1FBDSw+BJJNeZpKZyczc3x8ThkSS\nMAnJTCZ5P8+TJ5l7z9z7vZss3nfOueeIBEEQQERERERE1MWI7V0AERERERGRPTAMERERERFRl8Qw\nREREREREXRLDEBERERERdUkMQ0RERERE1CUxDBERERERUZcktXcBLZWcnGzvEoiIiIioC4iPj7d3\nCdTObBKGFi1ahF9//RU+Pj7Ytm3bDfsFQcC7776LvXv3wsnJCe+99x769OnT5PH4h0lERERE7Ykf\nwHcNNhkmN3PmTKxdu7bJ/fv27UN2djZ27tyJd955B2+99ZYtyiIiIiIioi7MJmFoyJAh8PDwaHL/\n7t27MX36dIhEIgwYMACVlZUoLCy0RWlERERERNRFdYhnhlQqFQIDAy2vAwMDoVKp4O/v32j7Cxcu\n2Ko0IiIiIiKHUVxVitySPHg4u6G7fzeIRKI2Oe6uXbvw7LPPYvv27ejRo0ebHLMj6BBhqKViY2Pt\nXQIRERERdWKO9sxQmaYCK7d+gl/PH4JJMAEAegZG4pV75qN/eO9bPv62bdsQHx+PpKQkPP/887d8\nvMYYjUZIJJJ2OXZTOsTU2gEBASgoKLC8LigoQEBAgB0rIiIiIiJyDLpaPZ77+k3sOXfQEoQAILUg\nE899/SYu5qXf0vE1Gg2Sk5Px7rvvIikpybJ9zZo1mDJlCqZOnYoPPvgAAJCTk4OHH34YU6dOxYwZ\nM3D58mUcOXIETz31lOV9S5cuxebNmwEACQkJeP/99zFjxgz8/PPP2LhxI2bNmoWpU6fiueeeQ01N\nDQCguLgYzz77LKZOnYqpU6fixIkTSExMxNdff2057qpVq/DNN9+06No6RM9QQkIC1q9fj8mTJ+P0\n6dNwc3NrcogcERERERFdt/PsXqQVZDW6T2fQ44tfNuD9P/6l1cffvXs3xowZg+7du8PLywspKSko\nKSnBnj17sHHjRjg7O6O8vBwA8Morr+DJJ5/ExIkTodPpYDKZkJ+f3+zxPT09sWXLFgBAWVkZ5syZ\nA8AcbjZt2oQHH3wQf/3rXzFkyBB88sknMBqNqK6uhr+/P5577jk8/PDDMJlMSEpKwvfff9+ia7NJ\nGHrppZdw9OhRlJWV4bbbbsNzzz0Hg8EAALj//vsxduxY7N27FxMnToSzszOWLVtmi7KIiIiIiBze\nvguHm91/MPUoDEYjpK0cgpaUlIR58+YBACZNmoSkpCQIgoCZM2fC2dkZgDnQqNVqqFQqTJw4EQCg\nUCisOv6kSZMsP6elpeGjjz5CVVUVNBoNRo8eDQA4fPgwVq5cCQCQSCRwc3ODm5sbPD09cf78eRQX\nF6N3797w8vJq0bXZJAx9+OGHze4XiURYsmSJLUohIiIiIupU9AZ9s/uNJhOMptaFofLychw+fBip\nqakQiUQwGo0QiUS46667rD6GRCKByXR9+J5Op2uw/1qgAoDXX38dq1evRkxMDDZv3oyjR482e+x7\n770XmzdvRnFxMWbNmmV1Tdd0iGeGOpISdRmyCi+jRq+1dylERERERDcV1635ycV6BfeAQiZv1bF3\n7NiBadOm4ZdffsGePXuwd+9ehIaGQqlUYvPmzZZnesrLy6FUKhEYGIhdu3YBAPR6PWpqahASEoKM\njAzo9XpUVlbi0KFDTZ5Po9HAz88PtbW12Lp1q2X7iBEj8N133wEwT7RQVVUFAJgwYQL279+Ps2fP\nWnqRWqJDPDPUEaQVZCHxv5/jWOZpAICzzAn3DJqAZ+94BM5yJztXR0RERETUuOmD78J3B7dAo6tu\ndP8Do1reY3LNtm3b8MQTTzTYdscddyAjIwMJCQmYNWsWZDIZxo4di5deegkrV67E4sWLkZiYCJlM\nhsTERISFheGuu+7CPffcg9DQUPTu3fTsdi+88ALuvfdeeHt7o3///tBoNACAN998E3/5y1/www8/\nQCwW46233sLAgQMhl8sxbNgwuLu7t2omOpEgCEKL32VHycnJiI+Pb9NjZhZexuNrXm70D2hQRBw+\nfvjdVo+xJCIiIiLH0x73nO3pVM45vL5hGco05ZZtYpEYT094EA/dNseOlbUvk8mEGTNmIDExERER\nES1+P3uGAKzZvb7JJH0i+yz2XjiE8X1b3u1GRERERGQLA8L74MeXv8Qv5w4iqygXni7umBA3Bv7u\nvvYurd2kp6fjqaeewsSJE1sVhACGIdQaarHvYvMzcKw7sAkh3oHo7tet1eMtiYiIiIjak5NMgbsH\nJNi7DJuJiorC7t27b+kYXT4M6Y21MJqMzba5cDUND336AiRiMcJ9w9AzsDuigiIRHdgdPQMj4a30\ntFG1RERERETUVrp8GHKRO6ObTwgul1y9aVujyYTMwhxkFuYAZ361bPdRepmDUVAkogK7IzowEt18\nQvicERERERFRB9blw5BIJMLckdOwcuvqRvfLJFI8e8cjUFUUIa0gC2kFWaiormzQpkRdhpL0MhxO\nP2HZppDKERkQjp6B5h4kc0jqDqWTa7teDxERERERWafLhyEAmDlkErKLrmDj4f802O4sd8LyuYsw\nInqwZZsgCCisLEFaQSbSC7KQmp+JtIIs5Jbmof7EfDqDHheupuHC1bQGxwz2CkB0YKQlJEUHdUeQ\nZwBEIlH7XiQRERERETXAqbXrSSvIws4zv6Kiugrd/bth0oAEeLi4W/XeGr0W6apspBVkIb0gE6n5\nmUhXZVu1eKvSyRVRARGWoXbRgZHo7t8NTjLFrV5SpyEIArIKL6OipgphPsHwdfO2d0lERETUiTna\n1NrXlGsroKouhlLmgmBlYJt84B4bG4uePXtaXn/yySdwdXXF888/j5SUFMyYMQOLFy+27N+0aRO+\n+eYbAOZ7uBdffBETJky45TraA3uG6omuG8rWGs5yJ8SFxSAuLMayzWQy4WpZgaX3KK3A/F1VUdTg\nvWqtBqdyzuFUzjnLNolYjG4+ofUCkrk2HytDgEZXjR2nf0XKlYtQSBUY23sEhkYOgFgsbtX12dPp\nnPN4f9tqpBVkATDPmT+u90gsnPIMPF097FwdERERkf1V6tT49twmJBecgQBzX0c39xA82Hsmor0j\nb+nYTk5O+Omnnxpsq66uxgsvvIC0tDSkpV0fCVVQUIDPPvsMW7ZsgZubGzQaDUpLS2/p/AaDAVJp\n+8QWhqF2JBaLEeYTjDCf4AbrFFVUV1mCUVpBFtLyM5FVdBm1RoOljdFkQlbRZWQVXcbOs3st272V\nnogOvD6TXXRgd3TzDW0wWcOlvAy8uG4xStXXF93afGw7hvYYiJV/+DOc5U7tfOVt52JeOhZ8/Sb0\nBr1lm0kwYfe5A8gpvoovn/qQ050TERFRl6Y31uL9o58ityqvwfbLlVex8uhneHPEc4jwCGvTc7q4\nuGDw4MG4fPlyg+0lJSVwdXWFi4sLAMDV1RWuruZn5nNycrBkyRKUlpZCIpEgMTERYWFhWLlyJfbv\n3w+RSIT58+dj0qRJOHLkCBITE+Hu7o6srCzs2LEDP/30E9atW4fa2lr0798fS5YsgeQWJyxjGLID\nDxc3DI7sj8GR/S3bDEYDsouuILUgs8HzSOW/m6yhVF2OI+kncKTeZA1yqQyR/uGIDuyO7n7d8M3+\n72+Y5AEAjmacxN9//gKvTX22/S6uCYIgwGgywSSYYDIZYRRMMNW9Nv7ue/39iT+vbRCE6ktXZeF/\nZ/finkETbXw1RERERB3HkbwTNwSha2pNtfgpfSdeiH+s1cfXarWYNm0aACA0NBSffPJJk21jYmLg\n6+uL8ePHY8SIEZg4cSISEsxrH73yyit48sknMXHiROh0OphMJuzcuRMXL17ETz/9hLKyMsyePRuD\nB5uf1z9//jy2bt2KsLAwZGRk4L///S82bNgAmUyGt956C1u3bsX06dNbfV0Aw1CHIZVIERUYgajA\nCADmPxhBEFBcVYq0ehM1pBVk4nLJ1QaTNegNtbiYl46Leek3Pc+Px39GiboMYpHYymBiglEwmveb\nTE20Nd406LTXo2mr/vs5fj3/G3zdfeDr5g0/Nx/4unvDz80bvm4+8HRxd8ihgURERETWOlGY0uz+\n04XnYTQZIRG3rhelsWFyTZFIJFi7di3Onj2LQ4cOYfny5Th37hweeeQRqFQqTJxo/hBboTA/G5+c\nnIzJkydDIpHA19cXQ4YMwdmzZ6FUKhEXF4ewMHOP1qFDh5CSkoLZs2cDMAc0Hx+fVl1PfQxDHZhI\nJIKfuw/83H0wsuf1Ge20ei0yCnPqBaQspBdkoVpfc9NjmgQT9l441J5l25Raq8H+S0eb3C8RS+Dr\n5l0XlLzh6+5TF5Tq/+wDd2elzWf0M5qMEIvEnEmQiIiIbkn9Ry0aYxLMH2hLYJs1MEUiEfr164d+\n/fph5MiReOONN/DII4+0+DjXhtoB5k6CGTNm4OWXX27LUhmGHJGT3Al9QnuhT2gvyzaTyYS8chU+\n+9+3+F/KvhYfUyIWQywSQyyWQCISQ1z3WiIWQyKWWH4W1+2T1LW1bK/Xvsk2DbbX219vW/22ErEE\n/z29p8GzTzf8byFTQFura3K/0WSEqqLohkkrfk8uldWFJp8bQpNfXa+Tr5sPXBXOtxxe9pw7iH8d\n3IxzVy5BJpHitpjhePT2uegREHFLxyUiIqKuKdorAinFF5vcH+4eCrlEZpNaVCoViouL0adPHwDA\nxYsXERwcDKVSicDAQOzatQsTJkyAXq+H0WjE4MGD8e9//xszZsxARUUFjh8/joULFyIzM7PBcUeM\nGIFnnnkGDz/8MHx8fFBeXg6NRoOQkJBbqpdhqJMQi8UI9Q7C4wl/aDYMdfcNw5dPr4JELGkQUDqq\nmOAo/OX7lY3uc1W44PsX/gl3ZzeUqMtQVFWK4soSFFeVmn+uKkFRZSmK636urFE3eR69oRZ5ZSrk\nlamarcdZ7nR9OJ6bd92QPJ/fhSbvJiepWHfgB/xjx5cNzrsrZT8OXjqGTx5d1iDgEhEREVljbNhw\n/Jz1K2oMjS/pcnfkuHY5b0JCAtRqNWpra7Fr1y58+eWXcHZ2xooVK1BYWAiFQgFvb2+8/fbbAICV\nK1di8eLFSExMhEwmQ2JiIiZOnIiTJ09i2rRpEIlEePXVV+Hn53dDGIqKisKLL76IRx99FCaTCTKZ\nDIsXL77lMMR1hjqhD7Z9iu+PbLthu0QswaoH38awqIF2qKr1vt67Ef/cvQ4mwWTZ5uXqiRX3v4n+\n4b2tPo62VoeSa0GpshRFVebgVFxZUheeSlFUWWLVcMObUTq5Xh+a5+YDP3dvKGQKrN3znWW6y9/r\nHdITXz296pbPbWvpBdn4+fQelFdXItwvDJMHjIe30tPeZbWKVq/FrpT9OHP5AuRSGcbEDMeQyP4d\n+gOD5mSosvHz6V9QpqlAuG8oJg0cDx+ll73LahVtrQ57Ug7gVM45yKQyjIkZ5rDLBRCRY3C0e87U\n0kz848RXqNRf//BXLBJjZs+7cU+PjrnGT0fAMNQJmUwmfPfbFvzfbz+hqKoEANCvWyyenjAP8d37\n2bm61imsLMaus/tRXl2J7n5hGNdnVLstSqvRVTcISzf0ONX9rGtilrtb0SuoB7xcPeAkd4KL3BnO\ncie4yJ3gLHeGi8L83bnBvrrvCmc4ycxtZVLbdIMLgoC///wFvvttS4PtCqkc78xZiLGxI2xSR1vJ\nKryMF75dfMOQyqE9BmDF/X+Gi8LZTpW1nCAI+GTnV1h34IcG2+VSOZbOfgXj+oyyU2Wtk1N0BS98\n+xfklxc22B7fvR/e/+Nf4KpwaeKdRESt54j3nHqjHscLziBPrYJS5ophwQPg5eSYH1DaCsNQJ2Z+\nXqYYCpncYT8N7qgEQUCVVl0XmuoPybvey1RcWYJidRkMN3mosa1JJVJLgHJuJFQ5K8zbroUnZ4Xz\n9cBV/32K6+9XSOU3fAL/n+SdePfHxEZrkEmk+PfznyHEO8gWl3zLDEYj5iQ+iatlBY3unxp/B96c\n/oKNq2q97Sd34+3NHza6TyqWYMPzn6Kbz60NK7AVo8mI+/7+NHJLGp8ydvLA8Vg88yUbV0VEXQHv\nObsGhiGidmQymVBRU4WiyhJsP7kLGw41Py2lq8IFNXptgyGBHYFIJIKTTNEgXOWW5DU7eUXPoEjE\nhcXasMrWyysrwKG05Cb3i0UiTB44AXKpYyzwuztl/w1rlNUXHdgd/bpZP8TUnvLLVfgt9XiT+yUi\nCbYt/NZhh2YSUcfFe86ugWGIyEZq9FpM/eBhVNZUNbp/XO9ReO/+NyAIAvSGWtToa1Ct1zb4XqPT\noqZW2+B1tb4GNfrr3y3tdfXep9e2y7A+oo4gwjcM/cN7IyowAj0CIhAVEAEPF3d7l0VEDo73nF0D\nZ5MjshFnuROWz12EV9YvRU1tw9leIv3DsXDKMwDMvTAKmRwKmRyerh5tdn6jyYgavc4SjhqEKF0j\nYcryuvG2xVWlbVYb0a3ILs5FdnFug21+bj4NwlGPgAhE+IVBbqNn6oiIyDGwZ4jIxlQVRdh8dDvO\n5F6AQirH2NgRuLv/ODg1MR13R7Vk0wf4+fQvTe5/6e4ncVtvx5hEIb+8EPO/eK3J/YEe/lj96HKH\nmbks8ee1+OXcwSb3v3DX4w4ziYKqoghPrV3Y5H6ZRAqJWNLskM1rJGIJwn1DLeEoKtAclAI8/Lj4\nMRHdgPecXQN7hohsLMDDD/MnPmTvMm7ZY+Pux8FLx1ClvXH9pn7dYjFz6CSbzWx3q4I8/XHfiGn4\ndyPPdIkgwkuTn0SId6AdKmud5+54BCeyzqCi+sYhmX1Ce2H2sHscpockyNMffxg1A98d3HLDPhFE\neOde88yFV8sKkKHKRnpBNtJV2UhXZeFKaT7qf95nNBmRWZiDzMIc4Oxey3alk6ulBymqLiRF+kdA\n6cRZ6oiIOjv2DBFRq2UVXkbiz1/gcFoyBAhwljlh0sDxePaOhx1uuuNrU9Jv+O1HyxDAXkE98PSE\neRjZc7Cdq2u5nKIr+Ojnz3Eo1fy7cZIpMGnAeDx7xyMOd5MvCAI2/PYjvju4xbJcQM/ASDw14UGM\n7jW0yffV6LXIKrxcF46y68JSVrOTS9QX5BmAqIBwRAV2t4SlMJ8QSCWSNrkuIurYeM/ZNTAMEdEt\nK9dUoLJGDX93H4cb7vd7BqMR+eUqyKUy+Lv7OvzwqXJNBSqqq+Dv4Qtn/m4gCAJK1WVIs4Qj8/fM\nwhzUWjENvlwqQ3e/bpZhdj0CIhAdEAFvpVeL6lFrNdh74RBK1eXo5hOCUb2GQCpxzMEagiDg/NVU\nnM45D6lEglE9hzjMtPpEzeE9Z9fAMERERF2ewWhEbsnVBj1I6aoc5JerrHq/p4t7gx6kqIAIRPp3\na/TDgW0n/ocPtn3WYCIVf3dfLJu7CHFhMW12TbZQUV2JRf+3HMlZZyzbRBBh6uA7sPCeZxw24BEB\nvOfsKhiGiIiImqDWViOzsP6zSOawpNZqbvpekUiEUO8gRAV0tzyLpNFVY+nmVY22VypcseH51fB3\n923ry2gXgiDgmS8X4UT22Ub3/2HUDLxw1+M2roqo7fCes2tgGCIiImoBQRCgqigyh6O6YXbpqmzk\nFF+B0WS8pWMPixqE0b2GtFGl7etqaQH+r5mFpGUSKb5++iMEeQXARe7s8ENOqevhPWfXwDBERETU\nBvSGWmQX5VrC0bVnkq5N+tCVScQSuDm5wt3ZDW7OSrg7Ky0/uzkp4eFi/u5Wt93d+frPTjKFzepU\na6ux/sAP+O+p3ShRlyHMJwQzh9yNGUMmOeTEGcczT2P9gR9wMjsFUokUo3oOwUO33YseARH2Lq3F\nNLpq/OvAZiSd3IUSdRlCvYMxY8jdmDV0crv9bnjP2TUwDNXR1Fbj58xfcTgvGeraaoQoA5EQPhoj\nggfx0ywiImq1iupKSy/SR//9HCbBZO+SHIpcKoObk7LRIOXupIR7vSDlcS1g1e1ryfT+am01nv5i\nIdIKsm7Yl9BnFN6d87rDrDUGANtP7sbSzasgoOFtnpNMgY8f/iv6dettp8paTqOrxvwvX8elvIwb\n9t0eOwLL5i6CRNz2gYhhqGvgk40AqvRqLDv0MfI1hZZt6eXZSC/PRmZ5Dh7oM9OO1RERkSPzcHFH\nfPd+iO/eDyezU/DL+aYXxJ02+E4k9Bltw+par6BMheX/+UeT++VSOSYNSIBaW40qrRpVNWpU1lSh\nskYNtVZjdSjUG2pRoi5DibqsxTU6y50sQep6b5OyXpByq9uvxP/O7ms0CAHAnnMH8euFQ0hwkMWK\n1VoNVm5dfUMQAgBtrQ7LfvwYG55b7TAf9n53cEujQQgAfr1wCHvOHcTEuNtsXBV1FgxDAH5M29Eg\nCNW3K2c/hgYNQE/vSBtXRUREnc0jY+/DwdRj0Bv0N+wL9PDDc3c8CjdnpR0qa53krLPYWW8B2/rm\nT5iHP4ya0eg+k8kEjc4ckirrQlJVjRoVNWpU1f1cWfdVpVWjsrrK0lajq7a6vhq9FjV6LQori1t1\nffX9eeMKh5mevtZYC13tjX9j12QVXca4v85ul96U9qDRNv87Tzq5m2GIWq3LhyGTYMLBK8eabbP/\nylGGISIiumW9gnvgo3lvY/lPHyO3JM+yfWBEXyye+SeHCkIA8JeZf4LSyRX/Sd4Jg8m8TpPSyRWP\njL0P94+c3uT7xGKxZThbsFfLzmkwGqHWqlH5u5BUWWPufTKHKnOguhakKut6prS1ulZfq9FktGoW\nQUdRo9fevJGDKG1FryHRNV0+DOkMemiNzf/jWKGzbrVyIiKim4nv3g8bn/8nzl1NRam6DN18QtDd\nv5u9y2oVuVSG16Y+iycS/ojzV1MhlUgxoFvvdl18WSqRwNPVA56uHoBPy96rN9Siqm6onqXXqa5n\n6stf/w8V1U3/997TxQPhfqG3WL1tlGsqkFN8pdk2McFRUNhwcopbcSkvvdkgG+YTbMNqqLPp8mFI\nIZXDTe6KKn3Tn/YUVZegSq+Gm9yxPrEjIqKOSSwWO9wCq83xVnpidK+h9i7jpuRSGXzcvOHj5t3o\n/lXb1zT53uVzF2FQ97j2Kq1N6Q21mP63R5p8zmpQRBw+few9G1fVet8f2YYPtn3a5P4ZQ+62YTXU\n2TjOtCjtRCwS47bQ4c22ydcU4vW9y/HL5d84CxAREVEnNHvoPbg9dkSj+x69fa7DBCHAHPreve/1\nRp9xCvDww59nvGCHqlpvxuC7m5y84uHb5mBwZH8bV0SdCafWBqAz6PC3Y/9EatmNs8g4SRXQGq53\nzUZ6dMO8vrMR4RHWpjUQERGRfRlNRvxy7jdst6wzZF7LJr57P3uX1ir55YXYdGRbvXWGBmP64Lvh\n4eJm79JazGQy4Zfz5t9NcVVp3TpDd7VrEOLU2l0Dw1CdWqMBB68exaG8E9DoqxHsFoDx4aPRzT0E\nP6XtwM7sfZZeIRFEGNdtJGb1mgRXmUub10JERERE9sUw1DUwDFnpSlU+vk3ZhNSyTMs2N7kS98VM\nwaiQIQ4zVz8RERER3RzDUNfQ5Z8ZslaoWxAWDV+AJ/r/Ae51EylU6dVYe2YDlh/+GLmVeTc5AhER\nERERdSQMQy0gEokwKmQIlo99A+PDR0MEc29QalkWlhz8G747vwU1tZ1n3n4iIiIios6MYagVXGXO\neLDPLCwZ9SdEeoYDMC/eujN7HxbtW47DeSfgYKMPiYiIiIi6HIahWxDhEYY/j3gej8TdZ5lIoVxX\nic9OrcPKo58iT62yc4VERERERNQUhqFbJBaJMTZsOFaMfQNjw66vV3ShJA1/2f8+vr+4DTpD06sm\nExERERGRfTAMtRGl3BWPxN2Hv4x8EeHuIQAAo2BEUuZuvLFvBZILznDoHBERERFRB8Iw1MZ6eIZj\nyaiX8EDvWXCWmld+LtGW4eMTX2HV8c+h0hTZuUIiIiIiIgIYhtqFWCTGhIjReG/sGxgZMtiy/UzR\nBby5fyW2pP4XeqPejhUSERERERHDUDvyULjhyf5/xKLhCxCqDAIAGEwG/JS+E2/uX4nTheftXCER\nERERUdfFMGQDvbx74K3RL2NuzDQ4SRQAgKLqEqw6/jn+nvwlimtK7VwhEREREVHXY7MwtG/fPtx5\n552YOHEi1qxZc8P+vLw8PPjgg5g+fTqmTJmCvXv32qo0m5CKJbgr8nYsH/s6hgYNtGw/oTqLN/a+\nh23pu2AwGexXIBERERFRF2OTMGQ0GrF06VKsXbsWSUlJ2LZtG9LT0xu0+fTTT3H33Xfjxx9/xKpV\nq/D222/bojSb83LyxDMD5+HVoU8j0NUfAKA31WJTahL+vP99nCu+ZOcKiYiIiIi6BpuEoTNnziA8\nPBxhYWGQy+WYPHkydu/e3aCNSCSCWq0GAFRVVcHf398WpdlNH99eeGf0q5jVcxLkYhkAoEBTiPeP\nfobVJ79BmbbczhUSEREREXVuUlucRKVSITAw0PI6ICAAZ86cadBmwYIFeOyxx7B+/XrU1NTgq6++\nskVpdiWTSDElaiKGB8djw4UfcUJ1FgBwNP8UzhRewLToOzEx4jZIxRI7V0pERERE1PnYJAxZIykp\nCTNmzMCjjz6KkydPYuHChdi2bRvE4hs7ry5cuGCHCtvXRJcRiAwIwa6Sgyg3VEFr1OHfF/+D3Rn7\ncYfvaIQ5Bdm7RCIiIiKiTsUmYSggIAAFBQWW1yqVCgEBAQ3abNq0CWvXrgUADBw4EDqdDmVlZfDx\n8bnheLGxse1bsJ3EIhZ3GMchKWMPkjJ3w2AyoLi2DN/lb8WokMGYEzMVHgo3e5dJRERE1OklJyfb\nuwSyAZs8MxQXF4fs7Gzk5uZCr9cjKSkJCQkJDdoEBQXh0KFDAICMjAzodDp4e3vborwORS6RY0bP\nu/DumIWI84uxbD949The37sQqKlqAAAgAElEQVQMu7IPwCSY7FghEREREVHnIBIEQbDFifbu3Ytl\ny5bBaDRi1qxZmD9/PhITE9G3b1+MHz8e6enp+POf/4zq6mqIRCK8+uqrGD169A3HSU5ORnx8vC1K\ntjtBEJCsOovvzm9Bab0JFcLdQ/Bgn9mI8oqwX3FEREREnVhXuufsymwWhtpKV/zD1Bl0+Cl9J3Zk\n/QpjvV6h28KGY06ve6CUu9qxOiIiIqLOpyvec3ZFNlt0lVpPIVVgTswUvDNmIWJ9oi3b9+Uexmt7\nl2Fv7mEOnSMiIiIiaiGGIQcSrAzAwqHz8fSAB+GpcAcAaGqr8dXZf+PdQ39HTsUVO1dIREREROQ4\nOszU2mQdkUiE4cGD0N+vN35M+xn/y9kPk2BCRnkO3jr4IRLCR2Fmz0moMdTgl5zfkFmRA5lYhkEB\ncRgZEg+5RG7vSyAiIiIi6hD4zJCDy63Mw7fnNiGtLMuyzUXqDJ1RD6NgbNA2zC0YC4fNh5tcaesy\niYiIiBwK7zm7Bg6Tc3Bh7sFYNHwBHut3vyXkVBtqbghCAJBblYf15zbbukQiIiIiog6JYagTEIvE\nGBM6FO+NXYQY76hm2x7NP4UjeSeRW5kHtV4DB+sYJCIiIiJqM3xmqBNxlbkgwiMUF0vTm2wjQMCn\np761vJaKJfCQu8PDyR2eCvOXh8IdnvVfO7nDXa6EWMTsTERERESdB8NQJ9PS54EMJiNKtGUo0ZY1\n204sEsNdrrwxKNV77VH3JRVLbuUSbiAIAi6UpOFQXjKq9BoEKwNwe9gI+Lv6tul5iIiIiKhrYRjq\nZIYHD8KmS0kQ0PjwtwAXX4zrNgrlukpU6Cqvf9dWotpQ0+RxTYIJ5XXtcyqbr8FNrrwelOrCkofC\nre5nD8s+uUR20+sxCSZ8fvo7HMpLtmw7VXgOP2f9isf6zcWokCE3PQYRERERUWMYhjoZH2cvzOo5\nCZtSk27Yp5AoMH/gPER4hDX6Xr1Rbw5H2kpL8KnQVaFcWy806SpQpdc0W0OVXo0qvRq5VXnNtnOR\nOtcFpes9S171Xnsq3HEs/3SDIHSNSTDhizP/h0iPcAQp/Zs9DxERERFRYxiGOqF7oibA39UXP2f+\ngsyKy5CKpYgPiMPUqDsQ4hbY5PvkEjn8XXzh79L88DODyYAKXZWlZ6lcaw5KZfWCVEVdkGqqhwow\nz3pXra5BnlrVqus0CSb8mnsI98dOa9X7iYiIiKhrYxjqpIYGDcDQoAEwCSaIIIJIJGqzY0vFUvg4\ne8HH2avZdibBhEq9GhXaSpTpKiy9TJYQVS88NTYVuDWO5Z9CjHcPxPpEw0mqaNUxiIiIiKhrYhjq\n5Ow5A5xYJLYMdwtHaJPtBEGAulZzQ1Aq11ZiT84BmJrpXSrVliMx+QtIRBJEeUWgr28v9PXthXCP\nUM5+R0RERETNYhgiuxOJRHCTK+EmVyIMwQ32aQ06HLh69KbHMApGXCrNwKXSDPyQuh1KmSv6+PZE\nX99e6OPbC97Onu1VPhERERE5KIYh6tBm9LwLKcUXUa67cQq7fn6xuKfHeJwrTsO54kvIKM+xPKOk\nrtXgSP5JHMk/CQAIVgYgzjcGffx6oZd3DygkcpteBxERERF1PCJBEJoeg9QBJScnIz4+3t5lkA0V\n15Tih0vbcSz/FAyCER4KNyR0G4XJPcZDKr6e5zW11ThfF4zOFl9ESU3jaydJxRL09Io0D6nzi0Go\nWxCH1BEREVEDvOfsGhiGyGEYTAZoDTq4yJxvGl4EQYCquhgpRReRUnwJF0vSoTXqGm3rLnczD6nz\nMw+p81S4t0f5RERE5EB4z9k1cJgcOQypWAql3Lo/WZFIhEBXPwS6+mFCxBgYTAZklOfgbNFFnCu+\nhOyKK5YhdZX6KhzKS7asZxTmFoy+fuaJGKK9Iq1aHJaIiIiIHA97hqhLqtKrcb44DSnF5p6jMm1F\no+3kYhl6+fSwzFIXrAxs02nKiYiIqGPiPWfXwJ4h6pLc5EoMCx6IYcEDIQgC8tQqpBRfwrm6IXV6\nUy0AQG+qxdmiizhbdBEA4KnwqHvWqBf6+PaEm1xpz8sgIiIiolvAniGi39Eba5FeloWU4ktIKb6E\ny5VXG20nggjh7iHo6xeDvr69EOUV0WBCByIiInJcvOfsGhiGiG6iXFeJ88Wp5nBUdAmV+qpG2ykk\ncsT4RNUNqYtBoKtfo0PqDCYDTqhSkF6WBblEjoEBfRHp0Y3D74iIiDoQ3nN2DQxDRC0gCAJyq/LM\nQ+qKLuFSWSYMJkOjbX2cvSzPGvX27QlXmQsKNEX48NgaFFYXN2gbH9APTw14gJM1EBERdRC85+wa\nGIaIboHOqMel0gycKzIPqbuqLmi0nQgidPcIg6q6GJra6kbbTIwYgz/2ntme5RIREZGVeM/ZNfAB\nB6JboJDI0c8vFv38YgEAZdpypBSnIqXoIs4Vp0JdqwEACBCQWXG52WPtzT2MGdF3w0Xm3O51ExER\nERHDEFGb8nLyxJjQoRgTOhQmwYTLlVeRUtdrdKk0w7K2UWP0xlpsvLgVI0MGo7tHN8gk/L8nERER\nUXviMDkiG/khdTu2pv/PqrZSsRSRHmHo6d0DPb0iEeUVwR4jIiIiG+I9Z9fAj56JbGR40ECrw5DB\nZEBqWRZSy7IAmJ85CnULQk/vSPTyjkS0VyS8nDzas1wiIiKiTo9hiMhGQtyCMCZ0GPZfOdLo/kfj\n5kIpd0FqaRZSyzKRU5ELo2ACYH7mKLcqD7lVedidcwAA4Ofig55ekejpHYmeXpFNTuVNRERERI1j\nGCKyoYf73gtPJ3fszj6AakMNACDQ1R/39pqM+MB+AIBBAXEAAJ1Bh4zyy0gry0RqaSbSy7OhM+ot\nxyqqLkFRdQkOXj0GAHCXKxFtCUfd0c09BBKxxMZXSEREROQ4+MwQkR3ojXrkqwshk8gQ5OpvVY+O\n0WTE5cqrSK0LR6llWajSq5ts7yRRoIdXuKX3KNIzHAqJvC0vg4iIqNPiPWfXwDBE5KAEQUCBpqgu\nHGUgtSwLRdUlTbaXiCSI8AhFtNe15466Qyl3tWHFREREjoP3nF0Dh8kROSiRSIQgpT+ClP4YGzYc\ngHmdo2vPHKWWZuJKVb5lOm+jYERGeQ4yynPwc9YvAIBgZUBdz1EP9PKOhI+zl92uh4iIiMjWGIaI\nOhEvJ08MCx6IYcEDAQCa2hqkl2UhrSwLqaUZyKy4DIPJaGmfp1YhT63Cr7mHAADeTp6WCRl6eUci\nSBkAsUjc7DkNJiMulaajSq9BkDIA4e4h7XeBNlBcU4rM8hxIxVLEekfDWeZk75JazWgy4lJpBir1\nagS6+iHcPdShJ9koqSlDRnk2JCIpYn2iON08ERHdMoYhok7MVeaM/v690d+/NwDzwq5ZFZeRVtd7\nlFaWhRqD1tK+VFuOw3kncDjvRN37XRDt1d0SkCI8QiEVX/9n46QqBd+kbEK5rsKyrYdnOJ7q/wD8\nXX1tdJVtQ2vQ4auz/8bR/FOW3jSFRIEpPSZgco/xDhciThWew7cpm1CqLbdsi/TohicHPIBAVz87\nVtZyOoMOX6d8j8N5J+r9buSY3GMCpvSY4HC/GyIi6jj4zBBRF2YSTMitykdaaaZlaF25rrLJ9nKx\nDJGe4ejpHQlnqRM2XtxquTmtz8fJC++MedVhPrkXBAGrjn+OM0UXGt1/f+w03Nn9dtsWdQvSy7Kx\n7PDHMNVNzV6ft5Mn3hnzKlxlLnaorHU+Or4WpwrPNbpvTswUTIpMsHFFRNQV8J6za2DPEFEXJhaJ\nEe4egnD3EEyIGANBEFBUU2Kera5uxroCTaGlvd5Ui4ul6bhYmt7scUu0Zfju/I8YGNCnvS+hTag0\nRU0GIQDYkvYzPBUekDrIVOVb0//XaBACzL1/353/EYMC+tq4qtYprC5uMggBQFLGbkwIHw05Z0ok\nIqJWYM8QETWrUleF1LpnjtLKspBTebXJG20ie1g0fAF6efewdxlE1MnwnrNrYM8QETXLXeGGwYH9\nMLhuUdgagxZppVn48PgaO1dGZOZgn+kREVEHwjBERC3iLHVCP/9YxHhHNTtcbnBAP8T5x9qwstZT\naYqwPXNPk/vlYhnui53aYPKIjmxH5q/I06ia3D8oIM4yqUZHV6gpRlLm7ib3yyVyRHiE2bAiIiLq\nTBzjv+xE1OHc02M8LpVmNDqBgrtciYfj5jjMoq6CICC9LBupZZmN7p/cYwLGh4+2cVWt5+fsg/eP\nftro70Ypc8XDfefAXaG0Q2UtJwgCMitycKGk8eBtNBlxpSofUV4Rti2MiIg6heYXECEiakJfvxg8\n3v9+OEsbrsMT6OqPV4fOd5ggBJgXsH0+/lH09Y1psF0sEuPuyHGYEjXBTpW1Tm/faDzZ/49wkTac\nzS/Q1Q8Lh813mCAEmH83CwY9gn5+jfcyGgUj/nbsn8iuyLVxZURE1BlwAgUiuiU6gw6ni86jUqdB\nsDIAMT49brpQa0eWW5mHtLIsyMRSxPnHwlPhbu+SWk1n1ON04XlU6tQIUvoh1ie6U/xupGIp+vr2\nxL8vbsWR/JMAzGtivTbsGXRz8EV/iajj4D1n18AwREREDslgMuLTk98iWXUGAOAmd8XrwxYgxC3Q\nzpURUWfAe86uwXE/IiQioi5NKpZg/sAHLZNBVOk1WHl0NQrUhTd5JxERkRnDEBEROSypWIpnBz6M\nvr69AAAVuiqsOLoahZpiO1dGRESOgGGIiIgcmlwiw/PxjyLWJwoAUKatwIojq1FcU2rnyoiIqKNj\nGCIiIocnl8jxYvzj6OnVHQBQoi3DiiOrUaYtt3NlRETUkTEMERFRp6CQKvCnwU8i0jMcAFBUXYIV\nR1ajXFdp58qIiKijYhgiIqJOw1nmhJeHPIVw91AAQIGmCCuPrEalTm3nyoiIqCOyKgwJgoCNGzdi\n3rx5mDJlCgDg2LFj2L59e7sWR0RE1FKuMme8OvRphLkFAwDy1Cq8f/RTqPUaO1dGREQdjVVhKDEx\nEZs2bcJ9992H/Px8AEBgYCDWrl3brsURERG1hlLuileHPo1gZQAAILcqDx8c/Qya2ho7V0ZERB2J\nVWFoy5Yt+OyzzzB58mSIRCIAQGhoKHJzc60+0b59+3DnnXdi4sSJWLNmTaNttm/fjkmTJmHy5Ml4\n+eWXrT42ERHR77kr3LBw6HwEuPgBALIrr+DDY/9EjUFr58qIiKijsCoMGY1GuLq6AoAlDGk0Gri4\nuFh1EqPRiKVLl2Lt2rVISkrCtm3bkJ6e3qBNdnY21qxZgw0bNiApKQlvvPFGS66DiIjoBp5OHnht\n2DPwc/EBAGSU52DVsc+hM+jsXBkREXUEVoWhsWPHYvny5dDr9QDMzxAlJiZi3LhxVp3kzJkzCA8P\nR1hYGORyOSZPnozdu3c3aLNx40b88Y9/hIeHBwDAx8enJddBRETUKG9nT7w27Bn4OHkBAFLLMvFR\n8hfQG/V2royIiOzNqjC0aNEiFBUVIT4+HlVVVRg4cCDy8vLwyiuvWHUSlUqFwMBAy+uAgACoVKoG\nbbKzs5GVlYW5c+dizpw52LdvXwsug4iIqGm+zt54bdgz8FSYP3C7UJKGj098hVqjwc6VERGRPUmt\naaRUKvHJJ5+guLgYeXl5CAoKgp+fX5sWYjQakZOTg3Xr1qGgoAAPPPAAtm7dCnd39xvaXrhwoU3P\nTUREXcNs3zuxoWArNMYanC26iBX7P8Z0/4mQiCT2Lo2IiOzAqjBkMpkAAN7e3vD29m6wTSy+eedS\nQEAACgoKLK9VKhUCAgJuaNO/f3/IZDKEhYUhIiIC2dnZ6Nev3w3Hi42NtaZsIiKiG3SPjMB7Rz5B\nlV6D9OrL+FV7DPMHzINEzEBERNclJyfbuwSyAauGyfXu3Rt9+vRp9MsacXFxyM7ORm5uLvR6PZKS\nkpCQkNCgzYQJE3D06FEAQGlpKbKzsxEWFtbCyyEiImpeiFsQXh06H64y8yRAxwvO4PPT38EkmOxc\nGRER2ZpVPUO/n+ygqKgIa9assXoCBalUisWLF+Pxxx+H0WjErFmzEB0djcTERPTt2xfjx4/HmDFj\ncPDgQUyaNAkSiQQLFy6El5dXy6+IiIjoJrq5h+CVIU9h5dFPUWPQ4nD+CUjFUjza7z6IRVZ9TkhE\nRJ2ASBAEoTVvrKqqwuzZs7Fjx462rqlZycnJiI+Pt+k5iYioc0ovy8YHRz+D1mieavv2sBF4qO+9\nlmUkiKjr4j1n19Dqj7/UajVKS0vbshYiIiKbivKKwJ+GPAG5RA4A+DX3ENaf34xWfk5IREQOxqph\ncq+++mqDT8m0Wi2OHTuGqVOntlthREREttDLuwdejH8Mq46vRa2pFrtzDkAmluK+mKnsISIi6uSs\nCkPh4eENXjs7O2Pu3LkYOXJkuxRFRERkS719e+K5+Efw9+QvYDAZ8XPWr5CKpZjVcxIDERFRJ2ZV\nGFqwYEF710FERGRX/fxi8ezAh/GPE1/BKJiwLWMXZGIZpkXfYe/SiIionTQZhjZt2mTVAWbPnt1m\nxRAREdnTwIC+eHrAPHx66luYBBO2pP0XMrEEk3qMt3dpRETUDpoMQz/99NNN3ywSiRiGiIioUxkS\n1B9G4Y/456n1ECBg46VtkIiluLP7WHuXRkREbazJMLRu3Tpb1kFERNRhDA8eBIPJgLVnNgAANlz4\nETKxFAnho+xcGRERtaUWT60tCAJMJpPli4iIqDMaHToUD/e91/L623ObsDf3sB0rIiKitmbVBAoq\nlQpLly7F8ePHUVlZ2WDfhQsX2qUwIiIie7u920gYTEasP78ZAPD12Y2QiiUYFTLEzpUREVFbsKpn\naMmSJZDJZPj666/h4uKCLVu2ICEhAW+//XZ710dERGRXEyLG4L4Y87p6AgSsPb0BR/NP2rkqIiJq\nC1b1DJ08eRK//PILXFxcIBKJEBMTg3fffRdz587FnDlz2rtGIiIiu7o7chwMJgN+SN0OAQI+O7Ue\nEpEU8YFx9i6NiIhugVU9Q2KxGFKpOTe5u7ujtLQULi4uUKlU7VocERFRRzElaiKmRZnXHDIJJqw+\n+Q1OFZ6zc1VERHQrrApD/fv3x969ewEAo0ePxosvvogFCxagb9++7VocERFRRzI9+i5MikwAABgF\nI/5x4mukFF20c1VERNRaIkEQhJs1qqyshMlkgqenJ7RaLb788ktoNBo89NBD8Pf3t0WdFsnJyYiP\nj7fpOYmIiK4RBAHfXfgR/8veBwCQiWV4aciTiPWJsnNlRNSWeM/ZNTQbhvbu3YsxY8ZALG7xDNzt\nhn+YRERkb4IgYN25H7Dn8kEAgEIixytDnkK0d6SdKyOitsJ7zq6h2ZSzaNEi3HbbbXjvvfdw6dIl\nW9VERETUoYlEIjzQZyZuCx0GANAZ9fjb8TXILM+xc2VERNQSzYah/fv345133kFBQQHmzJmD6dOn\n4+uvv0ZJSYmt6iMiIuqQxCIxHo6bg5EhgwEAWoMOHxz9J7Ircu1cGRERWcuqZ4YAQK1WY/v27fjP\nf/6D06dPY9SoUZg+fTruuuuu9q6xAXZZEhFRR2I0GfHP0+txNP8UAMBV5oLXhz2LMPdgO1dGRLeC\n95xdg9UPAymVSsyZMwfr16/HunXrkJqaij/96U/tWRsREVGHJxFL8GT/BzAowLzmkKa2GiuPfoo8\nNZefICLq6KwOQ3q9HklJSXjiiSfwwAMPIDQ0FMuWLWvP2oiIiByCVCzB/AHz0M8vFgBQpVdj5ZHV\nKNAU2bkyIiJqzk2HyR07dgw//vgjduzYAR8fH0ybNg3Tpk1DSEiIrWpsgF2WRETUUemNtUhMXotz\nxakAAG8nTywavgB+Lj52royIWor3nF1Dsz1DCQkJePbZZyGRSLBmzRrs2LEDzzzzjN2CEBERUUcm\nl8jwfPxjiPE2rzlUqi3HiiOrUVJTZufKiIioMc2GoVdeeQUHDhzA0qVLMWjQIFvVRERE5LAUEjle\nHPw4or26AwCKa0qx4shqlGkr7FwZERH9XrNhaNKkSZDL5baqhYiIqFNwkirw0uAnEenRDQBQWF2M\nlUdWo0JXZefKiIioPqsnUCAiIiLrOcuc8PLQpxDubh5anq8pxPtHPkWVXm3nyoiI6BqGISIionbi\nKnPBK0OfRqhbEADgijof7x/9DBXaKqQUXcJvV48jszwHVi7512EV15TicN4JHMs/DU1ttb3LISKy\nmtWLrnYUnNmDiIgcTaWuCssP/wP5mkIAgEQkgVEwWvaHu4fiqQEPIFgZYK8SW0Vn0OHrlO9xOO8E\nBJhvJ+RiGe6OTMD06DshEonsXCFR6/Ges2uwqmdIEARs3LgR8+bNw5QpUwCYp9zevn17uxZHRETU\nGbgr3LBw2DPwdvIEgAZBCAByKq9g5ZHVUOs19iiv1f55+l84lJdsCUIAoDfV4qf0HdiWscuOlRER\nWUdqTaPExET89ttveOihh7BkyRIAQGBgIJYvX45Jkya1a4FERESdgZeTB4Jc/VGqLW90f7muEuvP\nbUZ8YD8bV9Y6xTWlOKE62+T+7Zl7cEfEbVBIFTasioioZawKQ1u2bMGWLVvg7e2Nt956CwAQGhqK\n3Nzc9qyNiIio0xAEAZfKMpttczj/BA7nn7BRRe2rxqBFZsVlxPpE27sUIqImWTVMzmg0wtXVFQAs\n4381Gg1cXFzarzIiIqJOx6Ee071lDvZYMhF1QVb1DN12221Yvnw53njjDQDmf9wSExMxbty4di2O\niIiosxCJROjt0xNnii402WZQQF8MDIizYVWtV1xdgp/Sdza5XyFRoLtnNxtWRETUclaFoTfeeAOv\nvfYa4uPjYTAYMHDgQIwaNQorVqxo7/qIiIg6jck9xuNs0cUGEw5co5S54KG+c+ChcLNDZa2TUX4Z\nKcUXG913R8RtcJY62bgiIqKWuWkYEgQBZWVlSExMREVFBa5evYqgoCD4+fnZoj4iIqJOo5d3D8wf\nOA/fpHzfYD2eQFc/zB/4kEMFIQB4ZuA8fH76O5wsTGmwPcI9FDN63mWnqoiIrHfTMCQSiTBlyhSc\nOHECPj4+8PHxsUVdREREndLQoAEY4N8bZ4ouolJXhUBXP8T4REEscrx10F1kznhh8GPIU6twvjgV\nGy9uhd5Ui3Jdlb1LIyKyilXD5GJjY5GVlYUePXq0dz1ERESdnlwix2AHmULbGsHKAAQrA5BTeRX7\nrxxBua4Cl0ozEesTZe/SiIiaZVUYGjp0KJ544gnMmDEDgYGBDVaUnj17drsVR0RERI5jRPAg7L9y\nBABwOC+ZYYiIOjyrwtCJEycQEhKCo0ePNtguEokYhoiIiAgAEOMTBQ+FGyp0VThecAYP9pkFqdiq\nWw0iIruw6l+odevWtXcdRERE5ODEIjGGBQ3Ezux90NRW42zRRQwM6GvvsoiImmTV05omk6nJLyIi\nIqJrhgfHW34+nHfCjpUQEd2cVT1DvXv3bvCcUH0XLjS9eBwRERF1Ld09wuDv4ovC6mKcVKVAa9DB\nSaqwd1lERI2yKgzt3r27weuioiKsWbMG48aNa5eiiIiIyDGJRCIMDx6E/6TvhN5UixOqFIwMib/5\nG4mI7MCqYXIhISENvgYMGIAVK1Zg7dq17V0fEREROZjhwYMsPx/OS7ZjJUREzWv1Cm9qtRqlpaVt\nWQsRERF1AsHKAIS7hwAAUoovoVKntnNFRESNs2qY3KuvvtrgmSGtVotjx45h6tSp7VYYEREROa7h\nwfHIqbwKk2DC8YLTSAgfZe+SiIhuYFUYCg8Pb/Da2dkZc+fOxciRI9ulKCIiInJsw4IGYuPFrRAg\n4HDeCYYhIuqQrApDCxYsaO86iIiIqBPxdvZET+9IXCrNQGpZJkpqyuDj7GXvsoiIGrDqmaFt27Yh\nIyMDAJCVlYUHHngADz74oGUbERER0e+NqDeRwhGuOUREHZBVYeijjz6Ch4cHAGDFihWIi4vD0KFD\n8fbbb7drcUREROS4Bgf2h0RkvtU4xDBERB2QVcPkSktL4evrC51Oh+TkZPz973+HVCrF8OHD27s+\nIiIiclBKuSv6+sXgdOF55Fbl4WpVPkLcguxdFhGRhVU9Q97e3sjJycG+ffsQFxcHuVwOnU4HQRDa\nuz4iIiJyYCOCry+4ejjvpB0rISK6kVU9Q8888wxmzpwJiUSCVatWAQB+++03xMTEtGtxRERE5NgG\n+veBXCKH3qjH4bxkzOx5d4PlOoiI7MmqnqGZM2fiwIED2Lt3L0aNMk+NOWDAAHz44YdWn2jfvn24\n8847MXHiRKxZs6bJdjt27ECvXr1w9uxZq49NREREHZNCqsCggL4AgKKaUmSU59i5IiKi66wKQ4B5\nbSFnZ2cIggCTyQQvLy/4+PhY9V6j0YilS5di7dq1SEpKwrZt25Cenn5DO7VajW+//Rb9+/e3/gqI\niIioQxtef1a5fE6kQEQdh1VhSKVS4dlnn8WwYcPQu3dv9OnTx/JljTNnziA8PBxhYWGQy+WYPHky\ndu/efUO7xMREPPHEE1AoFC27CiIiIuqw+vrGQClzBQAcyTsFo8lo54qIiMysemZoyZIlcHJywtdf\nf40HHngA//rXv/Dxxx9j7NixVp1EpVIhMDDQ8jogIABnzpxp0ObcuXMoKCjA7bffji+++KLZ4124\ncMGq8xIREVHHEOXUDadqL6BSX4Udp/agu3OovUsiIrIuDJ08eRK//PILXFxcIBKJEBMTg3fffRdz\n587FnDlzbrkIk8mE9957D8uXL7eqfWxs7C2fk4iIiGxHXCrHqcPmDzPzJMWYFDvRzhURNS85Odne\nJZANWDVMTiwWQyo15yZ3d3eUlpbCxcUFKpXKqpMEBASgoKDA8lqlUiEgIMDyWqPRIDU1FfPmzUNC\nQgJOnTqF+fPncxIFIiKiTiLaqzu8nTwBAMdVp6E36u1cERGRlWGof//+2Lt3LwBg9OjRePHFF7Fg\nwQL07dvXqpPExcUhO04QJR8AACAASURBVDsbubm50Ov1SEpKQkJCgmW/m5sbjhw5gj179mDPnj0Y\nMGAAPv30U8TFxbXikoiIiKijEYvEGBY8EACgNehwupBD3onI/qwKQytXrsSQIUMAAG+88QaGDx+O\n6Oho/O1vf7PqJFKpFIsXL8bjjz+OSZMm4e6770Z0dDQSExMbnUiBiIiIOp/hDRZg5axyRGR/IkEQ\nBHsX0RLJycmIj4+/eUMiIiLqUARBwJv7VyBPrYJULMXfxy+Fi8zZ3mURNYr3nF2DVT1Der0eq1at\nwvjx4y1/FAcOHMD69evbtTgiIiLqPEQikWXNIYPJgGQVnw0mIvuyKgwtW7YMqamp+OCDDyASiQAA\n0dHR2LBhQ7sWR0RERJ3L8KDrC7AezuNsXURkX1ZNrb1r1y7s3LkTLi4uEIvN+SkgIMDq2eSIiIiI\nAMDf1ReRHt2Q+f/t3XlgVNXd//HPZLKyBgJZIICKyCZLZAuCUkEIS4AAorb6CNJHikopyCNqVGyp\naB/FX4q4IJUHwV2hgCXWsoMbAcMSZBUkIRCSEEIgIfvM/f0RnZKKSALMnbnzfv01M/dm5nM4lzPz\nnXvm3DNHtTfvOxWUnVVoUAOzYwHwUZd0ZiggIEAOR/WrRefn5ys0NPSqhAIAANb141Q5Q4a2ndhp\nchoAvuySiqHBgwfrscceU2ZmpiQpNzdXs2bN0rBhw65qOAAAYD09o7rKpqpp91+zqhwAE11SMTRt\n2jRFR0drxIgROnv2rOLi4hQeHq6HH374aucDAAAWExrcUB3C2kiSvi/IUO65PJMTAfBVl/SbocDA\nQCUmJioxMVH5+flq1KiRayEFAACAmoptdpP2nDooSdpyYrtGXD/I5EQAfNFFi6GsrKwLPn7ixAnX\n7WbNml3ZRAAAwPK6RXbW4j1LVems1Jas7RreeiBftAJwu4sWQ/3793cNTBe6NqvNZtO+ffuuTjIA\nAGBZdQJC1KVpB6XmpCmrKEeZhVlq2aC52bEA+JiLFkPt2rVTaWmpRo0apREjRig8PNxduQAAgMXF\nNrtJqTlpkqQtWdsphgC43UUXUFixYoVefvllFRQU6Ne//rUmTpyo5ORkVVRUyG63y263uysnAACw\nmC7h7RXsHySpqhhyGk6TEwHwNb+4mtwNN9ygxx57TOvXr9f48eO1ceNG9e3bV3v27HFHPgAAYFGB\n9kB1i+gsScovLdB3p4+YnAiAr7mkpbUlKT09Xdu2bdPOnTvVvn17NWjA1aIBAMDl6f3DBVilqrND\nAOBOF/3NUEFBgZKTk7V8+XKdO3dOI0eO1DvvvMMKcgAA4IpoH9ZGDQLr6Wx5kbad2KV7OoyWvx/T\n8AG4x0WLoVtuuUXR0dEaOXKkunTpIknKyMhQRkaGa5/evXtf3YQAAMCy7H529YyK0dqMz1VUcU57\n8g6oS3gHs2MB8BEXLYaaNm2qsrIyffTRR/roo49+st1ms2ndunVXLRwAALC+2GY3aW3G55KqpspR\nDAFwl4sWQ+vXr3dXDgAA4KNah7ZS05DGOlmSr+05u1VWWaagH1aZA4Cr6ZIXUAAAALgabDabev2w\nkEKZo1w7clmxFoB7UAwBAADTsaocADNQDAEAANM1rx+lFvWrVqvdfXKfisrPmZwIgC+gGAIAAB4h\n9oezQw7DqW+yd5mcBoAvoBgCAAAeoVezGNftr5kqB8ANKIYAAIBHaBLSWDc0ulaSdDD/e+WXFJic\nCIDVUQwBAACPEdusmyTJkKGUEztMTgPA6iiGAACAx+gR1UV2W9XHE1aVA3C1UQwBAACPUT+wnjo2\naStJyjh7TFlFOSYnAmBlFEMAAMCjxJ53zaEUzg4BuIoohgAAgEeJibhRgX4BkqqmyhmGYXIiAFZF\nMQQAADxKiH+wukbcKEnKKc7TkTOZJicCYFUUQwAAwOP0Pm+q3JasVBOTALAyiiEAAOBxOjVtp7oB\ndSRJW0/slNNwmpwIgBVRDAEAAI/j7+ev7pGdJUkFZWe1/9RhkxMBsCKKIQAA4JF+vACrxFQ5AFcH\nxRAAAPBIbRtfp9CghpKkbdm7VOGoNDkRAKuhGAIAAB7Jz+anXs1iJEkllaVKO7nP5EQArIZiCAAA\neCxWlQNwNVEMAQAAj9WqQbQi6zaVJO3M3auSilKTEwGwEoohAADgsWw2m2J/ODtU4azQ9tzdJicC\nYCUUQwAAwKPFRp0/VW67iUkAWA3FEAAA8GiR9cJ1bcMWkqQ9eQd1tqzQ5EQArIJiCAAAeLxeP5wd\nchpObT2xy+Q0AKyCYggAAHi8Xs26yiabJGnLCVaVA3BlUAwBAACP1yg4VO3CWkuSDp1O18niUyYn\nAmAFFEMAAMArxDbr5rqdkrXDxCQArIJiCAAAeIXukZ1lt9klsaocgCuDYggAAHiFugF11Dm8vSTp\nWNEJZZ7NMjkRAG9HMQQAALxG72b/vuZQygmmygG4PBRDAADAa3QJ76hge5Ak6eusVBmGYXIiAN6M\nYggAAHiNIHugYiJulCSdKjmtQwXp5gYC4NUohgAAgFfpfd6qciykAOByUAwBAACv0qHJDaofWFeS\ntPXETlU6HSYnAuCt3FYMbd68WXFxcRo4cKAWLFjwk+2LFi3S0KFDNXz4cI0bN07Hjx93VzQAAOBF\n/P3s6hHZVZJUWF6kvacOmpwIgLdySzHkcDg0a9Ysvfnmm0pOTtaqVat06NChavu0b99ey5Yt0z/+\n8Q/FxcXpxRdfdEc0AADghaqtKsdUOQC15JZiKC0tTa1atVKLFi0UGBioYcOGad26ddX2iY2NVUhI\niCSpa9euys7Odkc0AADghVo3ukZhIY0kSanZu1XuKDc5EQBv5JZiKCcnR5GRka77ERERysnJ+dn9\nly5dqltvvdUd0QAAgBfys/kpNqrq7FCpo0w7c/eanAiAN/I3O8B/Wrlypb799lu98847P7vPvn37\n3JgIAAB4ovDyUNftNQc2qX5BkIlpAHgjtxRDERER1aa95eTkKCIi4if7ffXVV5o/f77eeecdBQYG\n/uzztW/f/qrkBAAA3qOdYWj1mS91vChbR0oz1fL6VqobUMfsWLCI1NRUsyPADdwyTa5Tp05KT09X\nZmamysvLlZycrP79+1fbZ+/evZo5c6Zef/11hYWFuSMWAADwYjabTbE/LKRQ6XTom+w0kxMB8DZu\nKYb8/f01c+ZM/fd//7eGDh2qIUOGqE2bNpo7d65rIYUXXnhBxcXF+sMf/qCRI0dq0qRJ7ogGAAC8\nWOx5q8pxAVYANWUzDMMwO0RNpKamqlu3br+8IwAA8AnPfjVXhwrSZZNN/6//M2oU3NDsSLAAPnP6\nBrdddBUAAOBq+PHskCFDW0/sNDkNAG9CMQQAALxaj6iu8rNVfaRhqhyAmqAYAgAAXq1hUH11CLtB\nknTkzFFlnztpciIA3oJiCAAAeL3YZjGu2ymcHQJwiSiGAACA1+sW0Vn+flWXT/w6a7u8bH0oACah\nGAIAAF4vJCBYXcM7SpKyz+Uq4+wxkxMB8AYUQwAAwBJ6c80hADVEMQQAACyhU9P2CvEPliSlnNgh\np+E0OREAT0cxBAAALCHQHqDukV0kSadLz+hg/vcmJwLg6SiGAACAZTBVDkBNUAwBAADLaBd2vRoG\n1ZckbcvepUpnpcmJAHgyiiEAAGAZfjY/9YyquubQuYpi7T653+READwZxRAAALAUpsoBuFQUQwAA\nwFKubdhS4XWaSJJ25Hyr0soykxMB8FQUQwAAwFJsNptifzg7VO6s0Pacb01OBMBTUQwBAADLiT1v\nqlwKU+UA/AyKIQAAYDnN6kWoVYPmkqRv8/arsLzI5EQAPBHFEAAAsKTYZt0kSQ7DqW0ndpmcBoAn\nohgCAACW1DOqq+s2q8oBuBCKIQAAYElhIY3UtnFrSdLB09/rVMlpkxMB8DQUQwAAwLJYSAHAxVAM\nAQAAy+oR2UV2W9XHna8phgD8B4ohAABgWfUC6+rGpu0kSZmFWTpemG1yIgCehGIIAABYWu8fVpWT\npC0nODsE4N8ohgAAgKXFhHdUoD1QUtWqcoZhmJwIgKegGAIAAJYW5B+kmyJulCSdLD6l788cNTkR\nAE9BMQQAACwvNurfq8ptyUo1MQkAT0IxBAAALO/Gpm1VN6COJCkla6ccTofJiQB4AoohAABgef5+\n/uoR2UWSdLa8UPtOHTI5EQBPQDEEAAB8Qu/m560qxzWHAIhiCAAA+Ig2ja5V4+BQSVJqTprKHRUm\nJwJgNoohAADgE/xsfurVLEaSVFJZqrST+0xOBMBsFEMAAMBnxJ5/AVZWlQN8HsUQAADwGS3rN1NU\n3XBJ0s7cvSquKDE5EQAzUQwBAACfYbPZXGeHKp2VSs3ZbXIiAGaiGAIAAD4l9offDUlMlQN8HcUQ\nAADwKRF1m+q6hi0lSXvzvlNB2VmTEwEwC8UQAADwObHNbpIkGTK07cROk9MAMAvFEAAA8Dk9o7rK\nJpskLsAK+DKKIQAA4HNCgxuqQ1gbSdLhggzlFueZnAiAGSiGAACAT/pxqpwkbcnaYWISAGahGAIA\nAD7ppsjO8vezS6paVc4wDJMTAXA3iiEAAOCT6gaEqEvTDpKkrKIcZRZmmZwIgLtRDAEAAJ9Vfaoc\nCykAvoZiCAAA+Kwu4R0U7B8kqaoYchpOkxMBcCeKIQAA4LMC7YHqFtFZkpRfWqDvTh8xOREAd6IY\nAgAAPq33eVPlUlhVDvApFEMAAMCntQ9rowaB9SRJW0/sVKXTYXIiAO5CMQQAAHya3c+unlExkqSi\ninPak3fA5EQA3IViCAAA+DxWlQN8E8UQAADwea1DW6lJSGNJ0vac3SqrLDM5EQB38Dc7AAAAgNls\nNptim92kVYfXqsxRrpe2LVDHJm11S3RPNQ4JNTterZQ7yrX1xE4dyD8su82uLuEd1CW8g/xs3vld\n+PHCE/ry+DcqKDuriDpN1De6p8JCGpkdC17ObcXQ5s2bNXv2bDmdTo0dO1YTJ06str28vFwzZszQ\nnj17FBoaqqSkJEVHR7srHgAA8GGGYaiwvMh1/+Dp73Xw9Pf65NBq/bbz3bq5eXcT09Vc9rmTmrN1\nvvJK8l2Pbcz8Wq1DW+mRHhNVN6COielqxjAMLf/uM31yaHW1xz85tEb3d7pTfaN7mpQMVuCWrwYc\nDodmzZqlN998U8nJyVq1apUOHTpUbZ+PP/5YDRo00Jo1azR+/HjNmTPHHdEAAACUcmKHNmVu+cnj\nDsOhN9PeV+bZLBNS1Y7TcOrl1IXVCqEfHS7I0Fu7PzIhVe1ty971k0JIquqbhWkfKOPscRNSwSrc\ncmYoLS1NrVq1UosWLSRJw4YN07p163T99de79lm/fr0mT54sSYqLi9OsWbNkGIZsNps7IgIAAB+2\nOn3zz25zGk69vnOJbmh0nRsT1V5+aYGyinJ+dvu27F2av/NtBduD3Jiq9rbnfPuz2wwZWpfxhSZ0\nusuNiWAlbimGcnJyFBkZ6bofERGhtLS0n+wTFRVVFcrfX/Xr19fp06fVuHFjd0QEAAA+7OjZYxfd\nnlWUc9ECw9tYacW8jDMX7zvgYrxyAYV9+/aZHQEAAFhIgPxVKS626o2McgefDVFrbimGIiIilJ2d\n7bqfk5OjiIiIn+xz4sQJRUZGqrKyUoWFhWrU6MIrhLRv3/6q5gUAAL6lt6O71h/98me3j20br5ub\nd3NjotorKCvUrC+TZMi44PbQoAZ6qvcfZPfzjlXllh34p744vvVnt/+qdR+1b3XlPxumpqZe8eeE\n53FLMdSpUyelp6crMzNTERERSk5O1ksvvVRtn/79+2v58uWKiYnRv/71L8XGxvJ7IQAA4BbxrW9X\nak6azpQV/mTbtQ1baOA1tyrQHmBCspprFByqEdcP1MoLLDogSb/pkKAmdbznZwhj2g7Vt3n7VVB2\n9ifbWjWIVt/oHiakglXYDMO48NcGV9imTZv03HPPyeFwaMyYMXrwwQc1d+5c3XjjjRowYIDKysr0\n6KOPat++fWrYsKGSkpJcCy6cLzU1Vd26ecc3MwAAwHvkFufpw33/0I7cb+U0nAqyB+rm5t01tm28\n6gSEmB2vRgzD0IajX+nT79e7VpVr2aC5RrUZrJiIG01OV3Mni/P14f5PtD1nt5yGU4H2AN3crLvG\nthuuulepb/jM6RvcVgxdKRyYAADgaiquKFFR+Tk1DG6gIHug2XEui9NwKr+0QHabXaFBDbx+1o07\n+4bPnL7BKxdQAAAAuFrqBIR43Zmgn+Nn81OTEO+ZEvdLrNQ38Aze8cs5AAAAALjCKIYAAAAA+CSK\nIQAAAAA+iWIIAAAAgE+iGAIAAADgkyiGAAAAAPgkiiEAAAAAPoliCAAAAIBPohgCAAAA4JMohgAA\nAAD4JIohAAAAAD6JYggAAACAT/I3O0BtpKammh0BAAAAgJezGYZhmB0CAAAAANyNaXIAAAAAfBLF\nEAAAAACfRDEEAAAAwCdRDAEAAADwSV65mtzVlJ+fr8WLF6usrEx33323rrnmGrMj1VpGRobmzZun\nsrIyTZgwQTExMWZHgkVZ7VjbuXOn5s2bp/Lyco0bN06333672ZFqzUpjmmStY81KfWOlfpGs1x4r\njWlW6xt4AAPVPProo8a2bduMbdu2GaNHjzY7To2UlpZWuz9t2jQjKyvLyMrKMkaMGGFSqisnPT3d\nmD59ujF58mRj+/btZse5bDt27DAmTJhg3HvvvcaaNWvMjlMjVjvWcnNzq92fMmWKUVJSYhQXFxvx\n8fEmpboyvHlMMwzrHWvn8+a+sVq/WK09VhrTrNY38Dw+P03ut7/9rbZt2+a6X1FRoebNmys6Olrl\n5eUmJqu5SZMmacWKFa77/v7+On78uI4fPy673W5istopKyurdn/u3LmaPn26EhMT9cc//tGcUJfh\n5MmT1e4vWrRIr776qhYsWKC5c+ealKp2rHasPfPMM3rllVdcx1yDBg302Wefac2aNapbt67J6WrG\nSmOaZK1jzUp9Y6V+kazXHiuNaVbrG3gen7/OUGFhoV577TXl5ORo6tSpcjqdrgFk3Lhx6t69u9kR\nL5nD4dD777+vDRs2aNKkSbruuuu0ZMkSlZWVaezYsWrdurXZEWvk/vvv18iRI5WQkCBJmjFjhu68\n805J0nPPPae///3vZsarsYceekgdOnTQAw88oKCgID399NPq1q2b/Pz89N577+mDDz4wO+Ils9qx\nJknr16/XkiVLlJCQoLi4OK1atUolJSWKj49X48aNzY53yaw0pknWOtas1DdW6hfJeu2RrDOmWbFv\n4Fl8vhj6UWZmppKSkhQeHq6HHnpIDRo0MDtSrf3nG27Lli3NjlQrVhwArfLm9COrHGs/cjgceu+9\n97Rx40ZNmjRJPXr0MDtSrVlpTJOsdaxZqW+s1C+S9dpjpTHNan0Dz+HzxdDRo0f1/vvvKyAgQPfc\nc48yMzP1+uuvq1+/frrnnnu86hTsrl27tHDhQgUEBOh3v/udgoODlZSUpIiICK9+w7XaAGiFNyer\nHWvr1q3TW2+9JX9/f/3ud79Thw4dXMfctGnTvOqYs9KYJlnrWLNS31ipXyTrtcdKY5rV+gYeyMwf\nLHmCMWPGGKmpqcYXX3xh3Hfffa7Hly9fXu2+NxgxYoSRnZ1tfP/998Zdd93lejwlJcWYMGGCiclq\nZ+fOncbvf/9745FHHjEOHDhgZGRkGFOnTjWef/5548yZM2bHq7G1a9ca9957rzF+/Hjj66+/Ns6c\nOWM8//zzxtSpU42MjAyz49WI1Y61+Ph4o7S01CgoKDDGjBnjevzIkSPG1KlTTUxWc1Ya0wzDWsea\nlfrGSv1iGNZrj5XGNKv1DTyPzy+tXV5erujoaBUXF6u0tNT1eEJCggYPHmxispqz2+06fvy4SkpK\nFBAQ4Hq8Z8+e6tmzp4nJamfmzJlasGCBiouL9cQTT+iDDz5QUlKStm7dqmnTpmnhwoVmR6yRv/71\nr1q6dKlKS0v129/+VkuXLtXjjz+u9PR0JSUlKSkpyeyIl8xqx1r9+vW1evVqlZaWKiwszPX4Nddc\n41X9IllrTJOsdaxZqW+s1C+S9dpjpTHNan0Dz+Pz0+S2b9+uRYsWKSAgQBMnTlS7du3MjlRrR44c\n0YcffqiAgAD95je/UVRUlNmRLsvo0aP11FNPqaSkRPPnz9fbb79tdqTL8pvf/Ea//vWvVVpaqrVr\n1+qNN94wO1KtWe1Yy8/PV3Jysvz9/TV8+HDVq1fP7Ei1ZqUxTbLWsWalvrFSv0jWa4+VxjSr9Q08\nj88XQ+crKCiQJIWGhpqcBJL1BkArvTn9KC8vTzk5OZKkiIgINWnSxOREV05BQYHXjwWMaZ6LvvFM\njGmey8p9A3P5fDGUlZWlF198UVu2bFH9+vVlGIaKiooUGxur6dOnKzo62uyIl2zp0qW64447JEnZ\n2dl67LHHtGfPHl1//fV6/vnnde2115qcsHasPAB665vTvn379Mwzz6iwsFARERGSqo65Bg0a6Jln\nnlHHjh1NTlgzr732mh566CFJ0qFDh/Twww+roqJCkpSUlKQuXbqYGa9GrDSmSdYa16zUN1bqF4kx\nzZNZrW/ggUz7tZKHuPPOO43k5GSjsrLS9VhlZaWxatUqY+zYsSYmq7mEhATX7SlTphgffPCB4XA4\njNWrV3vdj3MNwzD27t1rjB071hg8eLAxbtw4Y9y4cUZcXJwxduxY49tvvzU7Xo29+uqrrtvfffed\nMWjQIOO2224zbrvtNmPnzp0mJqu5ESNGXDDzjh07jOHDh5uQ6PKc/3/ngQceMDZu3GgYhmHs2rWr\n2g92vYGVxjTDsNa4ZqW+sVK/GAZjmiezWt/A8/iZXYyZ7fTp0xo6dGi1JU3tdruGDRvmmsbgjdLT\n03XXXXfJz89PAwcO1JkzZ8yOVGOPP/64nnzySf3zn//UW2+9pbfeekufffaZEhMT9cQTT5gdr8bW\nrFnjuv3CCy8oMTFR69ev11//+lc9//zzJiaruZKSkgt+s9i1a1eVlJSYkOjKyc3NVb9+/SRJnTt3\nrvZDd29g1TFN8v5xzap94+39IjGmeTIr9w08g8+vJtexY0f98Y9/1KhRoxQZGSmp6vTr8uXL1b59\ne5PT1Ux2draeffZZGYah/Px8VVRUuFZeqaysNDldzVl5APT2N6dbb71VEydOVEJCQrX/NytWrNAt\nt9xicrqay8zM1KRJkyRVtaOkpEQhISGSvO//jpXGNMla45qV+sZK/SIxpnkyq/UNPI/P/2aovLxc\nS5cu1bp165Sbmyup6ncpt912m8aOHavAwECTE1665cuXV7vfv39/NWzYUCdPntTbb7+tRx55xKRk\ntfPss8/q6NGjFxwAo6OjNXPmTJMT1kz37t3VvXt3SdLOnTu1YcMG15tTfHy8Vq1aZWa8Gtu0aVO1\n/zfh4eEaMGCAq8jzJlu3bq12v2PHjqpbt67y8vL0r3/9S/fcc49JyWrOSmOaZK1xzUp9Y6V++RFj\nmueyUt/A8/h8MQTPZqUB0GpvTgAAAN6OYugiNmzYoNtuu83sGFeEldoCz/bhhx/qrrvuMjvGFWOl\n9lhtHLBSe2iL57LSGCBZqz1WagvM4/MLKFzM7t27zY5wxVipLVLVAGglVmqP1b5fsVJ7rDYOWKk9\ntMVzWWkMkKzVHiu1Bebx+QUUJOnw4cMXnIo1ZcoUk5PVnJXacjFWGwC9sT2HDx9Wbm6uOnfurLp1\n67oeb9asmYmpas9K7UlLS5NUtTjHoUOH9Pnnn+u6667z2nHAau0534wZM/TCCy/QFg/zzTffaPfu\n3WrTpo3uvvtus+NcNm9uz65du9S6dWvVq1dPpaWlWrBggfbu3avWrVu7FokALofPT5NbsGCBkpOT\nNWzYMNfFvHJyclyPTZw40eSEl85Kbfkly5Yt05gxY8yOccV4W3uWLFmid999V61bt9b+/fuVmJio\n22+/XZI0atSon/y42tNZqT2vvPKKNm/erMrKSvXp00e7du1Sr1699NVXX6lv37568MEHzY5YI1Zq\nz4U+uKWkpKhXr16SpPnz57s7Uq1ZqS2SdMcdd2jp0qWSpI8++kjvvvuuBg4cqC+++EL9+/f3uvdP\nK7Vn2LBhWrlypfz9/fX0008rODhYcXFx2rJli/bv369XXnnF7Ijwdu6+sJGnGTRokFFeXv6Tx8vK\nyoyBAweakKj2rNSWX9KvXz+zI1xR3tae+Ph4o6ioyDAMw8jMzDRGjRplvPXWW4ZhGMbIkSPNjFYr\nVmpPfHy8UVlZaRQXFxsxMTFGYWGhYRiGUVJSYsTHx5ucruas1J6EhARj+vTpxpYtW4yUlBRjy5Yt\nRp8+fYyUlBQjJSXF7Hg1YqW2GEb1/+ejR482Tp06ZRiGYZw7d87rjjPDsFZ7Bg8e7Lp9/sVkDaPq\ngqzA5fL5aXI2m025ublq3rx5tcdPnjwpm81mUqrasVJbJGn48OE/uy0vL8+NSa4MK7XH6XS6ppJF\nR0fr7bff1pQpU5SVleWVU/6s1B673S673a6QkBC1bNlS9erVkyQFBwfLz8/7fiZqpfYsW7ZMS5Ys\n0fz58zVjxgy1b99eQUFB6tmzp9nRasxKbZGqxoAzZ87I6XTKMAw1btxYklSnTp1qF8n1FlZqT5s2\nbVyzJ9q1a6fdu3erU6dOOnLkiPz9ff5jLK4Anz+KEhMTNX78eLVq1UpRUVGSpKysLB09elRPP/20\nyelqxkptkaRTp05p4cKFatCgQbXHDcPwujnPkrXaExYWpn379rkuFFm3bl298cYbSkxM1MGDB01O\nV3NWak9AQIDrAot///vfXY8XFhZ6XfEgWas9fn5+Gj9+vAYPHqznnntOTZo0kcPhMDtWrVipLZJU\nVFSk0aNHyzAM1xeL4eHhOnfunNd9ISJZqz2zZ8/W7Nmz9frrr6tRo0a6++67FRkZqaioKM2ePdvs\neLAAn//NkFT16jPM0QAACaRJREFUDUpaWppycnIkVV0Er1OnTl737YlkrbYkJiZq9OjRrguVnm/6\n9Ol66aWXTEhVe1ZqT3Z2tux2u5o2bfqTbampqerWrZsJqWrPSu0pLy+/4MU78/PzdfLkSbVt29aE\nVLVntfacb+PGjdq+fbtXXqD0P1mpLecrKSlRXl6eWrRoYXaUK8Kb21NUVKRjx46psrJSkZGRatKk\nidmRYBEUQwAAAAB8knfNMQAAAACAK4RiCAAAAIBPohgC4NNmzpypV1991ewYl+2bb75RXFyc2TEA\nAPAq/GYIgCX1799fubm52rx5s2tZWUlKSEjQvn37tG7dOkVHR1/Wa/zXf/2XRowYobFjx15u3Cuu\nf//+evbZZ3XzzTfX+G+PHTumAQMGqE6dOpKkkJAQderUSffdd5/69OlzpaMCAGAazgwBsKzmzZsr\nOTnZdf/AgQMqKSkxMdHVUVlZeVWed9u2bdqxY4dWrlypm2++WZMnT662vPWVcLWyAwBwKSiGAFjW\nyJEjtWLFCtf9FStWKCEhodo+jz/+uJKSkiRJKSkpuvXWW/V///d/6t27t/r27atly5Zd0mv9+Ld/\n+9vfXH+7du1abdq0SXFxcerZs6fmz5/v2n/evHmaMmWKpk6dqpiYGI0aNUr79+93bW/btq0yMjIu\nmnPBggXq06ePnnjiCddjkvToo48qKytLkyZNUkxMjP72t79p4sSJevvtt6tlHj58uNasWfOLbWva\ntKnGjRunyZMna86cOXI6nZKknJwc/f73v1dsbKz69++vJUuWuP7G4XBo/vz5uv322xUTE6PRo0fr\nxIkTrra9++67GjRokAYNGiRJOnz4sO6//3717NlTcXFx+vTTT13PtXHjRiUkJOimm25Sv379NG/e\nPNe2srIy/c///I969eql7t27a8yYMa6LGBcWFioxMVF9+/bVLbfcoqSkJK++Fg4A4MqjGAJgWV27\ndlVRUZEOHz4sh8Oh5ORkjRgx4qJ/k5eXp8LCQm3evFmzZ8/WrFmzdObMmUt6vby8PJWVlWnz5s2a\nMmWKnnrqKX3yySdatmyZ3n33Xb322mvKzMx07b9u3ToNHjxYW7duVXx8vB566CFVVFRc8mudOXNG\nGzZs0J///Odq21588UU1a9ZM8+fP144dO/TAAw8oISFBn3zyiWuf/fv3Kzc3V/369buk15OkQYMG\n6dSpUzpy5IicTqcefPBBtW3bVps3b9bixYu1ePFiff7555KkRYsWKTk5WQsWLND27dv13HPPKTg4\n2PVca9eu1UcffaRPP/1UxcXFmjBhguLj4/XVV18pKSlJf/rTn3To0CFJVdP0/vd//1fffPON3njj\nDb3//vtau3atJGn58uUqKirSxo0blZKSoj/96U+u13n88cfl7++v1atXa8WKFfryyy/18ccfX3J7\nAQDWRzEEwNJ+PDv05ZdfqnXr1oqIiLjo/v7+/nr44YcVEBCgfv36qU6dOjpy5MglvZa/v78efPBB\nBQQEaOjQoTp9+rTuu+8+1atXT23atNH111+vAwcOuPbv2LGjBg8erICAAN1///0qLy/Xrl27Lum1\n/Pz8NGXKFAUGBlYrMn7OgAEDlJ6ervT0dEnSypUrNWTIkAte0PTnhIeHS5IKCgq0e/du5efna/Lk\nyQoMDFSLFi105513us7ofPzxx/rDH/6g6667TjabTe3atVOjRo1czzVx4kSFhoYqODhYGzduVPPm\nzTVmzBj5+/urQ4cOiouL02effSZJ6tWrl9q2bSs/Pz+1a9dOw4YN09atWyVV/ZsXFBQoIyNDdrtd\nN954o+rVq6e8vDxt2rRJiYmJqlOnjsLCwjR+/Phq0yYBAPA3OwAAXE0jR47Uvffeq2PHjmnkyJG/\nuH9oaKj8/f89NIaEhKi4uPiSXis0NFR2u12SXAVKWFiYa3tQUJDOnTvnuh8ZGem67efnp4iICOXm\n5l7SazVq1EhBQUGXtO+Prz1kyBB98sknmjx5slatWqWXX375kv9eqpoWJ1W188CBA8rNzVX37t1d\n2x0Oh+t+dna2WrZs+bPPFRUV5bp9/PhxpaWl/eS5fjyLt2vXLs2ZM0ffffedKioqVF5ersGDB0uq\n6t/s7Gw98sgjOnv2rEaMGKFp06YpKytLlZWV6tu3r+s5nU5ntdcFAIBiCIClNW/eXNHR0dq0aZNm\nz55tdpxqsrOzXbedTqdycnJcZ19CQkKqLfZw8uTJame1bDZbjV9v1KhRmjFjhrp166aQkBDFxMTU\n6O/XrFmjsLAwXXvttTp79qyio6O1evXqC+4bGRmpo0eP6oYbbrjg9vPzR0VFqUePHlq0aNEF950+\nfbruvfdevfnmmwoKCtLs2bN1+vRpSVJAQIAmT56syZMn69ixY5o4caKuvfZa9evXT4GBgdqyZUu1\n4hYAgPMxTQ6A5c2ePVuLFy92LRXtKfbs2aPVq1ersrJSixcvVmBgoLp06SJJateunVatWiWHw6HN\nmzdr27ZtNXruJk2aVPt9kiTFxMTIz89Pf/nLX37xt1Pny8vL0zvvvKNXXnlFjzzyiPz8/NS5c2fV\nrVtXCxYsUGlpqRwOhw4ePKi0tDRJ0tixYzV37lylp6fLMAzt37/fVcD8p1/96ldKT0/XihUrVFFR\noYqKCqWlpenw4cOSpHPnzqlhw4YKCgpSWlqaVq1a5frbLVu26MCBA3I4HKpXr578/f3l5+en8PBw\n9enTR3/5y19UVFQkp9Opo0ePuqbXAQAgUQwB8AEtW7ZUp06dzI7xEwMGDNCnn36qHj16aOXKlZo3\nb54CAgIkSU8++aQ2bNig7t276x//+Iduv/32Gj33xIkT9frrr6t79+5auHCh6/GRI0fq4MGDlzRl\nsEePHuratauGDx+uTZs2ae7cubrjjjskSXa7XfPnz9f+/fs1YMAAxcbG6qmnnlJRUZEk6f7779eQ\nIUM0YcIE3XTTTXryySdVVlZ2wdepV6+eFi5cqE8//VS33HKL+vbtqzlz5qi8vFyS9Mwzz+jll19W\nTEyMXn31VQ0ZMsT1t3l5eZoyZYq6deumoUOHqmfPnq62vfDCC6qoqNDQoUPVo0cPTZkyRSdPnqzR\nvyMAwNq46CoAmGDevHnKyMjQnDlz3Pq6K1as0Icffqj333/fra8LAIAn4swQAPiIkpISvffee7rr\nrrvMjgIAgEegGAIAH/D555+rd+/eCgsLU3x8vNlxAADwCEyTAwAAAOCTODMEAAAAwCdRDAEAAADw\nSRRDAAAAAHwSxRAAAAAAn0QxBAAAAMAnUQwBAAAA8En/Hy4cRC7LLZVJAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa372ae74a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# MinImpurityDecrease Experiment\n",
    "\n",
    "experimentDTMinImpurityDecreaseDF = pandas.read_csv(workspace + \"results/experimentDTMinImpurityDecrease.csv\")\n",
    "\n",
    "seaborn.set_style(\"whitegrid\")\n",
    "pyplot.figure(figsize=globalFigsize)\n",
    "seaborn.pointplot(y=\"Value\", hue=\"Measure\", x=\"MinImpurityDecrease\",\n",
    "                  data=experimentDTMinImpurityDecreaseDF, palette=\"Greens_d\")\n",
    "pyplot.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "pyplot.ylabel('Measure Value', fontsize=12)\n",
    "pyplot.xlabel('Min Impurity Decrease', fontsize=12)\n",
    "pyplot.title('', fontsize=15)\n",
    "pyplot.xticks(rotation='vertical')\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Default Decision Tree vs Custom Decision Tree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6EAAAGKCAYAAAD9r0f2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa371c62630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# BasicVsOptimized Experiment\n",
    "\n",
    "experimentDTBasicVsOptimizedDF = pandas.read_csv(workspace + \"results/experimentDTBasicVsOptimized.csv\")\n",
    "\n",
    "seaborn.set_style(\"whitegrid\")\n",
    "pyplot.figure(figsize=globalFigsize)\n",
    "seaborn.barplot(x=\"Value\", y=\"Measure\", hue=\"Tuning\",\n",
    "                data=experimentDTBasicVsOptimizedDF)\n",
    "pyplot.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "pyplot.ylabel('Measure', fontsize=12)\n",
    "pyplot.xlabel('Value', fontsize=12)\n",
    "pyplot.xlim(0.5, 1)\n",
    "pyplot.title('Insert Title', fontsize=15)\n",
    "pyplot.xticks(rotation='vertical')\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Logistic Regression"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "See http://scikit-learn.org/stable/modules/linear_model.html#logistic-regression"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Neural Network"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "See http://scikit-learn.org/stable/modules/neural_networks_supervised.html"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "See http://scikit-learn.org/stable/modules/tree.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}