File size: 79,467 Bytes
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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SVM Accuracy: 0.87\n",
      "\n",
      "Classification Report:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.90      0.84      0.87      1301\n",
      "           1       0.85      0.90      0.87      1244\n",
      "\n",
      "    accuracy                           0.87      2545\n",
      "   macro avg       0.87      0.87      0.87      2545\n",
      "weighted avg       0.87      0.87      0.87      2545\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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0R3J3d9cXX3yhvn37KjY2VoUKFdJTTz2lmJiYLA1dmzZt1KdPH3322Wf69NNPZRhGrhvJFStW6OOPP9bEiROt981K1xPa9evXq2vXrtq1a5fc3d3z5PoA3Pssxp3c7Q4AAACnxT2SAAAAMIVGEgAAAKbQSAIAAMAUGkkAAACYQiMJAAAAU2gkAQAAYAqNJAAAAEwpkAuSe9W6/QLEAO5dCV/yVX1AQRXi77jF7r0evvW3YN2pK3un2e3cjkYiCQAAAFMKZCIJAACQKxayNTNoJAEAACwWR1dwT6L9BgAAgCkkkgAAAExtm8KnBgAAAFNIJAEAALhH0hQSSQAAAJhCIgkAAMA9kqbwqQEAAMAUEkkAAADukTSFRhIAAICpbVP41AAAAGAKiSQAAABT26aQSAIAAMAUEkkAAADukTSFTw0AAACmkEgCAABwj6QpJJIAAAAwhUQSAACAeyRNoZEEAABgatsU2m8AAACYQiIJAADA1LYpfGoAAAAwhUQSAACARNIUPjUAAACYQiIJAADgwlPbZpBIAgAAwBQSSQAAAO6RNIVGEgAAgAXJTaH9BgAAgCkkkgAAAExtm8KnBgAAAFNIJAEAALhH0hQSSQAAAJhCIgkAAMA9kqbwqQEAAMAUEkkAAADukTSFRhIAAICpbVP41AAAAGAKiSQAAABT26aQSAIAAMAUEkkAAADukTSFTw0AAACmkEgCAABwj6QpJJIAAAAwhUQSAACAeyRNoZEEAACgkTSFTw0AAACmkEgCAADwsI0pJJIAAAAwhUYSAADA4mK/Vy5t2bJFLVq0UFhYmCwWi5YvX26z3zAMjRw5UqGhofLy8lJUVJR+/PFHmzFnz55Vp06d5Ofnp4CAAL3wwgu6ePGizZgDBw7on//8pwoVKqQSJUpo/Pjxua6VRhIAACAfuXTpkqpUqaLp06dnu3/8+PGaMmWKZs6cqR07dsjb21uNGjVSamqqdUynTp108OBBrV+/XitXrtSWLVvUs2dP6/6UlBQ1bNhQpUqV0u7du/X2229r9OjRmjVrVq5q5R5JAACAfHSPZJMmTdSkSZNs9xmGocmTJ2v48OFq1aqVJOnjjz9WcHCwli9frg4dOujQoUNau3atdu3apRo1akiSpk6dqqZNm2rChAkKCwvTvHnzlJ6erg8//FAeHh6qVKmS9u3bp3feecem4fw7JJIAAAB2lJaWppSUFJtXWlqaqXMlJCQoKSlJUVFR1m3+/v6qVauW4uLiJElxcXEKCAiwNpGSFBUVJRcXF+3YscM6pm7duvLw8LCOadSokY4cOaJz587luB4aSQAAADveIxkbGyt/f3+bV2xsrKkyk5KSJEnBwcE224ODg637kpKSFBQUZLPfzc1NgYGBNmOyO8fN75ETTG0DAADYcWp72LBhGjBggM02T09Pu73f3UQjCQAAYEeenp551jiGhIRIkpKTkxUaGmrdnpycrKpVq1rHnDp1yua4a9eu6ezZs9bjQ0JClJycbDPmxs83xuQEU9sAAMDpWSwWu73yUpkyZRQSEqINGzZYt6WkpGjHjh2KjIyUJEVGRur8+fPavXu3dczGjRuVmZmpWrVqWcds2bJFV69etY5Zv369ypcvryJFiuS4HhpJAACAfOTixYvat2+f9u3bJ+n6Azb79u1TYmKiLBaL+vXrpzFjxmjFihWKj49Xly5dFBYWptatW0uSKlasqMaNG6tHjx7auXOnvv32W8XExKhDhw4KCwuTJHXs2FEeHh564YUXdPDgQS1cuFDvvvtulin4v8PUNgAAcHp5nRzeie+++05PPPGE9ecbzV3Xrl01d+5cDRkyRJcuXVLPnj11/vx51alTR2vXrlWhQoWsx8ybN08xMTGqX7++XFxc1LZtW02ZMsW639/fX19++aWio6NVvXp13XfffRo5cmSulv6RJIthGMYdXm++41VrsKNLAGAnCV+Oc3QJAOwkxN/dYe/t3W6O3c59afFzdju3o5FIAgAA5J9A8p7CPZIAAAAwhUQSAAA4vfx0j+S9hEYSAAA4PRpJc5jaBgAAgCkkkgAAwOmRSJpDIgkAAABTSCQBAIDTI5E0h0QSAAAAppBIAgAAEEiaQiIJAAAAU0gkAQCA0+MeSXNIJAEAAGAKiSQAAHB6JJLm0EgCAACnRyNpDlPbAAAAMIVEEgAAOD0SSXNIJAEAAGAKiSQAAACBpCkkkgAAADCFRBIAADg97pE0h0QSAAAAppBIAgAAp0ciaQ6NJAAAcHo0kuYwtQ0AAABTSCQBAAAIJE0hkQQAAIApJJIAAMDpcY+kOSSSAAAAMIVEEgAAOD0SSXMc2kimp6dr+fLliouLU1JSkiQpJCREtWvXVqtWreTh4eHI8gAAAHAbDpvaPnbsmCpWrKiuXbtq7969yszMVGZmpvbu3asuXbqoUqVKOnbsmKPKAwAATsRisdjtVZA5LJHs3bu3KleurL1798rPz89mX0pKirp06aLo6GitW7fOQRUCAABnUdAbPntxWCP57bffaufOnVmaSEny8/PTG2+8oVq1ajmgMgAAAOSEw6a2AwICdPz48VvuP378uAICAu5aPQAAwIlZ7PgqwByWSHbv3l1dunTRiBEjVL9+fQUHB0uSkpOTtWHDBo0ZM0Z9+vRxVHkAAAD4Gw5rJF9//XV5e3vr7bff1sCBA633JhiGoZCQEA0dOlRDhgxxVHkAAMCJcI+kOQ5d/mfo0KEaOnSoEhISbJb/KVOmjCPLAgAAQA7kiwXJy5QpQ/MIAAAchkTSHL4iEQAAAKbki0QSAADAkUgkzaGRBAAAoI80haltAAAAmOLwRnLt2rXaunWr9efp06eratWq6tixo86dO+fAygAAgLPgu7bNcXgjOXjwYKWkpEiS4uPjNXDgQDVt2lQJCQkaMGCAg6sDAADArTj8HsmEhARFRERIkpYsWaLmzZtr3Lhx2rNnj5o2berg6gAAgDMo6MmhvTg8kfTw8NDly5clSV999ZUaNmwoSQoMDLQmlQAAAMh/HJ5I1qlTRwMGDNBjjz2mnTt3auHChZKko0eP6v7773dwdbgbHqtaRv2ffVzVKhRXaDF/PTN4rr7YctBmzIieDfVcq1oK8PFS3IHj6jt+qX765Yx1f9XyxTUmuqmqR5RQRmamln8dr6GTv9ClK+k253m2WQ31/VddhZe8TymX0rR04wH1f3vZXblOANKncz/Qlq+/UuKJBHl6FtJDlauqV5/+Klnqf19KkZaWpvfefVsbv1yjq1fTVfPRx9R/yHAFFr3POqbeIw9lOffIMeNVvyEzWTCHRNIchyeS06ZNk5ubmxYvXqwZM2aoePHikqQ1a9aocePGDq4Od4O3l4fif/xd/d5enu3+gZ0f10vP1FHft5aq7gtTdSk1XV+8212eHtf/Oyj0Pj+tmtpTP/36h+o+P1WtXp6tiDIh+mBke5vz9P1XXb32YmNN/Hijqv1ropr1maWvth+x9+UBuMn+Pd/pqaf/pRn/ma+JU2fpWsZVDerTU1euXLaOmTbpLW37ZpNei31H786cqzOnT2vE0H5ZzvXKyDFaunqT9VWnXv27dyEAJOWDRLJkyZJauXJllu2TJk1yQDVwhC/jjujLuFs3dNEd/qm35mzQyv9PKbuP/kwn1oxUy3qVtGj9fjWpU1FXMzLU7+1lMgxDktTnrSX6bv5APXB/Uf386x8K8PXSqBcbqe3AOdr03THrub8/dtK+FwfAxttT3rf5edjIsWrVqK6OHvpBVarV0MWLf2r1iqUa8cZ4VatZS5L0ysg31OWZljoYv1+VKlexHuvj46ui990nIC+QSJrj8ERyz549io+Pt/783//+V61bt9a///1vpaen3+ZIOIPSYYEKvc9PG3f+aN2WcilVuw4mqlblUpIkT3c3Xb2aYW0iJelK2lVJUu0q16fL6j8SLheLRWHF/LX3s0E69sWr+nTss7o/yP8uXg2Av7p48aIkydf/+u/i0UM/6Nq1a6r+yKPWMaVKP6DgkFAdjN9vc+zkt8eqZYM66tWtg1atWGrzzwAg1yx2fBVgDm8ke/XqpaNHj0qSfv75Z3Xo0EGFCxfWokWLNGTIkL89Pi0tTSkpKTYvI/OavcvGXRJS1FeSdOrsnzbbT529qODA6/s2fXdMwUV91f/ZenJ3c1WAr5fGRF+/TyrkvutjyhQvKhcXi4Z0e1KDJ61Qx2GfqIhfYa2c2lPubq538YoA3JCZmalp77ypylUe1gNlwyVJf/xxRu7u7vL19bMZWySwqM7+8b/7op/vFaPR4yZowrQPVO+JBpo8foyWfD7vrtYPIB80kkePHlXVqlUlSYsWLVLdunU1f/58zZ07V0uWLPnb42NjY+Xv72/zuvb7DjtXjfzkUEKyerz2mfp2rKezm8fq+OqROv77WSX98aeMzOsJhcVikYe7mwa+8199teOodn6fqK4j5qlciftUr3pZB18B4JwmjR+jhJ+PaeSYt3N9bNcXXlTlKtX0YPmK6tj1BXXo/Lw++2SOHaqEs2BBcnMc3kgahqHMzExJ15f/ubF2ZIkSJXTmzJnbHSpJGjZsmC5cuGDzcgurZdeacfck/XE9iQz6//TxhqBAHyXflFIu/HKfyjR9XWVbjFHxhqM05oMvVSzAWwm/nf3/81xfSupwQrL1mDPnL+nMhUsqERJg56sA8FeT3x6ruK2bNfm9DxUUHGLdXrTofbp69ar+/NN2+bdzZ/+weWr7ryIqVdbpU8ncEgXcZQ5vJGvUqKExY8bok08+0ebNm9WsWTNJ1xcqDw4O/tvjPT095efnZ/OyuDj8GSLkkeO/n9XJMyl6omY56zZfb0/VrFRSO+JPZBl/6uxFXbqSrnYNqio1/Zo27Lx+20Tc/uOSpPCSxaxji/h56T5/byUmnbfrNQD4H8MwNPntsfpm0wZNfu9DhRa3XebtwYoRcnNz055d/5tZSjyRoOSkkzYP2vzVsaOH5evnJw8PD7vVjoKNRNIch3dckydPVqdOnbR8+XK9+uqrKlfuesOwePFi1a5d28HV4W7w9vJQ2fv/lzSUDgvUP8LDdC7lsn5JPq/pn32joc/V17Ffzuj472c1qlcjnTyTohWb/7fW5Ivtamt7/AldvJym+rUe1Lg+zTRi+mpduJgqSTr2yxl9sfl7TRjQSjGxi5VyKVWvv9RUR06c0uabnuIGYF+Txo/RhnWrNXbCFHkV9tYf/z/z5OPjI89CheTj46umLdto+uTx8vXzl7e3t96dME6VKlexNpLffrNJ5/44o4jKVeTh4anvdmzTp3Nnq/2zXR14ZYBzshj59DG31NRUubq6yt3dPdfHetUabIeKYC//rPaAvpzRO8v2T1Z+p55vXF+gfkTPhnq+9aMK8CmkbfuP6+XxS3XspgXJZ4/qoMaPVZCPl6eOnDilyfM2a8GaPTbn8/X21Ph+LdXq8YeUaRjauudnDXrnv/r11AX7XiDyVMKX4xxdAu5AdguJS9fXhGzSvLWk/y1IvuHL1bqaflU1H62t/kNGWJf62RG3VbOmT9ZvvyZKhqHi95dUq7bt1bx1O7m4OHyiDXcgxD/3/87PK+UGrbHbuY9NaGK3cztavm0k7wSNJFBw0UgCBReN5L3H4VPbGRkZmjRpkj7//HMlJiZmuVH67NmzDqoMAAA4i4J+L6O9OHwO4LXXXtM777yj9u3b68KFCxowYIDatGkjFxcXjR492tHlAQAAJ2Cx2O9VkDm8kZw3b54++OADDRw4UG5ubvrXv/6l2bNna+TIkdq+fbujywMAAMAtOLyRTEpKUuXKlSVdf2rvwoXrDz40b95cq1atcmRpAADASbD8jzkObyTvv/9+nTx5UpJUtmxZffnll5KkXbt2ydPT05GlAQAA4DYc3kg+9dRT2rBhgySpT58+GjFihMLDw9WlSxc9//zzDq4OAAA4A+6RNMfhT22/+eab1j+3b99eJUuWVFxcnMLDw9WiRQsHVgYAAIDbcXgj+VeRkZGKjIx0dBkAAMCJuLgU8OjQThzSSK5YsSLHY1u2bGnHSgAAAGCWQxrJ1q1b52icxWJRRkaGfYsBAABOr6Dfy2gvDmkkMzMzHfG2AAAA2Sroy/TYi8Of2gYAAMC9yWGN5MaNGxUREaGUlJQs+y5cuKBKlSppy5YtDqgMAAA4G5b/McdhjeTkyZPVo0cP+fn5Zdnn7++vXr16adKkSQ6oDAAAADnhsEZy//79aty48S33N2zYULt3776LFQEAAGfFVySa47BGMjk5We7u7rfc7+bmptOnT9/FigAAAJAbDmskixcvru+///6W+w8cOKDQ0NC7WBEAAHBWJJLmOKyRbNq0qUaMGKHU1NQs+65cuaJRo0apefPmDqgMAAAAOeGwr0gcPny4li5dqgcffFAxMTEqX768JOnw4cOaPn26MjIy9OqrrzqqPAAA4EQKeHBoNw5rJIODg7Vt2zb17t1bw4YNk2EYkq5Hy40aNdL06dMVHBzsqPIAAIATKehT0PbisEZSkkqVKqXVq1fr3LlzOnbsmAzDUHh4uIoUKeLIsgAAAJADDm0kbyhSpIhq1qzp6DIAAICTIpA0h69IBAAAgCn5IpEEAABwJO6RNIdEEgAAIJ/IyMjQiBEjVKZMGXl5eals2bJ64403rA8lS5JhGBo5cqRCQ0Pl5eWlqKgo/fjjjzbnOXv2rDp16iQ/Pz8FBATohRde0MWLF/O8XhpJAADg9CwW+71y46233tKMGTM0bdo0HTp0SG+99ZbGjx+vqVOnWseMHz9eU6ZM0cyZM7Vjxw55e3urUaNGNmtzd+rUSQcPHtT69eu1cuVKbdmyRT179syrj8uKqW0AAAA7SktLU1pams02T09PeXp6Zhm7bds2tWrVSs2aNZMklS5dWgsWLNDOnTslXU8jJ0+erOHDh6tVq1aSpI8//ljBwcFavny5OnTooEOHDmnt2rXatWuXatSoIUmaOnWqmjZtqgkTJigsLCzPro1EEgAAOD17fkVibGys/P39bV6xsbHZ1lG7dm1t2LBBR48elSTt379fW7duVZMmTSRJCQkJSkpKUlRUlPUYf39/1apVS3FxcZKkuLg4BQQEWJtISYqKipKLi4t27NiRp58biSQAAIAdDRs2TAMGDLDZll0aKUmvvPKKUlJSVKFCBbm6uiojI0Njx45Vp06dJElJSUmSlOVLW4KDg637kpKSFBQUZLPfzc1NgYGB1jF5hUYSAAA4PXs+tH2raezsfP7555o3b57mz5+vSpUqad++ferXr5/CwsLUtWtX+xVpEo0kAABwevll+Z/BgwfrlVdeUYcOHSRJlStX1okTJxQbG6uuXbsqJCREkpScnKzQ0FDrccnJyapataokKSQkRKdOnbI577Vr13T27Fnr8XmFeyQBAADyicuXL8vFxbY9c3V1VWZmpiSpTJkyCgkJ0YYNG6z7U1JStGPHDkVGRkqSIiMjdf78ee3evds6ZuPGjcrMzFStWrXytF4SSQAA4PTySSCpFi1aaOzYsSpZsqQqVaqkvXv36p133tHzzz8v6Xpy2q9fP40ZM0bh4eEqU6aMRowYobCwMLVu3VqSVLFiRTVu3Fg9evTQzJkzdfXqVcXExKhDhw55+sS2RCMJAACQb0ydOlUjRozQSy+9pFOnTiksLEy9evXSyJEjrWOGDBmiS5cuqWfPnjp//rzq1KmjtWvXqlChQtYx8+bNU0xMjOrXry8XFxe1bdtWU6ZMyfN6LcbNS6UXEF61Bju6BAB2kvDlOEeXAMBOQvzdHfbekW9tsdu544bWtdu5HY17JAEAAGAKU9sAAMDp5Zd7JO81JJIAAAAwhUQSAAA4vfyyjuS9hkYSAAA4PfpIc5jaBgAAgCkkkgAAwOkxtW0OiSQAAABMIZEEAABOj0TSHBJJAAAAmEIiCQAAnB6BpDkkkgAAADCFRBIAADg97pE0h0YSAAA4PfpIc5jaBgAAgCkkkgAAwOkxtW0OiSQAAABMIZEEAABOj0DSHBJJAAAAmEIiCQAAnJ4LkaQpJJIAAAAwhUQSAAA4PQJJc2gkAQCA02P5H3OY2gYAAIApJJIAAMDpuRBImkIiCQAAAFNIJAEAgNPjHklzSCQBAABgCokkAABwegSS5pBIAgAAwBQSSQAA4PQsIpI0g0YSAAA4PZb/MYepbQAAAJhCIgkAAJwey/+YQyIJAAAAU0gkAQCA0yOQNIdEEgAAAKaQSAIAAKfnQiRpCokkAAAATCGRBAAATo9A0hwaSQAA4PRY/sccprYBAABgCokkAABwegSS5pBIAgAAwBQSSQAA4PRY/sccEkkAAACYQiIJAACcHnmkOSSSAAAAMIVEEgAAOD3WkTSHRhIAADg9F/pIU5jaBgAAgCkkkgAAwOkxtW0OiSQAAABMIZEEAABOj0DSHBJJAAAAmEIiCQAAnB73SJqTo0ZyxYoVOT5hy5YtTRcDAACAe0eOGsnWrVvn6GQWi0UZGRl3Ug8AAMBdxzqS5uSokczMzLR3HQAAAA7D1LY5PGwDAAAAU0w9bHPp0iVt3rxZiYmJSk9Pt9nXt2/fPCkMAADgbiGPNCfXjeTevXvVtGlTXb58WZcuXVJgYKDOnDmjwoULKygoiEYSAADASeR6art///5q0aKFzp07Jy8vL23fvl0nTpxQ9erVNWHCBHvUCAAAYFcuFovdXgVZrhvJffv2aeDAgXJxcZGrq6vS0tJUokQJjR8/Xv/+97/tUSMAAADyoVw3ku7u7nJxuX5YUFCQEhMTJUn+/v765Zdf8rY6AACAu8Bisd+rIMv1PZIPP/ywdu3apfDwcNWrV08jR47UmTNn9Mknn+ihhx6yR40AAADIh3KdSI4bN06hoaGSpLFjx6pIkSLq3bu3Tp8+rVmzZuV5gQAAAPZmsVjs9irIcp1I1qhRw/rnoKAgrV27Nk8LAgAAwL3B1DqSAAAABUkBDw7tJteNZJkyZW4b0/788893VBAAAMDdVtCX6bGXXDeS/fr1s/n56tWr2rt3r9auXavBgwfnVV0AAADI53LdSL788svZbp8+fbq+++67Oy4IAADgbiOQNCfXT23fSpMmTbRkyZK8Oh0AAADyuTx72Gbx4sUKDAzMq9MBAADcNQV9mR57MbUg+c0ftmEYSkpK0unTp/Xee+/laXEAAADIv3LdSLZq1cqmkXRxcVGxYsX0+OOPq0KFCnlanFnnvn3b0SUAsJMiNWMcXQIAO7myd5rD3jvP7vVzMrluJEePHm2HMgAAAHCvyXUD7urqqlOnTmXZ/scff8jV1TVPigIAALib+IpEc3KdSBqGke32tLQ0eXh43HFBAAAAd5tLwe737CbHjeSUKVMkXe/YZ8+eLR8fH+u+jIwMbdmyJd/cIwkAAAD7y3EjOWnSJEnXE8mZM2faTGN7eHiodOnSmjlzZt5XCAAAYGckkubk+B7JhIQEJSQkqF69etq/f7/154SEBB05ckTr1q1TrVq17FkrAABAgffbb7/p2WefVdGiReXl5aXKlSvbfHugYRgaOXKkQkND5eXlpaioKP3444825zh79qw6deokPz8/BQQE6IUXXtDFixfzvNZcP2zz9ddfq0iRInleCAAAgKPkl4dtzp07p8cee0zu7u5as2aNfvjhB02cONGm9xo/frymTJmimTNnaseOHfL29lajRo2UmppqHdOpUycdPHhQ69ev18qVK7Vlyxb17Nkzzz6vGyzGrZ6euYW2bdvqkUce0dChQ222jx8/Xrt27dKiRYvytEAzUq85ugIA9sI6kkDB5ch1JAd+ccRu557YonyOx77yyiv69ttv9c0332S73zAMhYWFaeDAgRo0aJAk6cKFCwoODtbcuXPVoUMHHTp0SBEREdq1a5dq1KghSVq7dq2aNm2qX3/9VWFhYXd+Uf8v14nkli1b1LRp0yzbmzRpoi1btuRJUQAAAHeTi8V+r7S0NKWkpNi80tLSsq1jxYoVqlGjhp5++mkFBQXp4Ycf1gcffGDdn5CQoKSkJEVFRVm3+fv7q1atWoqLi5MkxcXFKSAgwNpESlJUVJRcXFy0Y8eOvP3ccnvAxYsXs13mx93dXSkpKXlSFAAAQEERGxsrf39/m1dsbGy2Y3/++WfNmDFD4eHhWrdunXr37q2+ffvqo48+kiQlJSVJkoKDg22OCw4Otu5LSkpSUFCQzX43NzcFBgZax+SVXK8jWblyZS1cuFAjR4602f7ZZ58pIiIizwoDAAC4W+y5bviwYcM0YMAAm22enp7Zjs3MzFSNGjU0btw4SdLDDz+s77//XjNnzlTXrl3tV6RJuW4kR4wYoTZt2uinn37Sk08+KUnasGGD5s+fr8WLF+d5gQAAAPbmYsdO0tPT85aN41+FhoZmCeYqVqyoJUuWSJJCQkIkScnJyQoNDbWOSU5OVtWqVa1j/vothNeuXdPZs2etx+eVXE9tt2jRQsuXL9exY8f00ksvaeDAgfrtt9+0ceNGlStXLk+LAwAAcCaPPfaYjhyxffDn6NGjKlWqlCSpTJkyCgkJ0YYNG6z7U1JStGPHDkVGRkqSIiMjdf78ee3evds6ZuPGjcrMzMzzpRpznUhKUrNmzdSsWTNJ14tfsGCBBg0apN27dysjIyNPCwQAALC3XCdrdtK/f3/Vrl1b48aN0zPPPKOdO3dq1qxZmjVrlqTryxT169dPY8aMUXh4uMqUKaMRI0YoLCxMrVu3lnQ9wWzcuLF69OihmTNn6urVq4qJiVGHDh3y9Ilt6Q4+ty1btqhr164KCwvTxIkT9eSTT2r79u15WRsAAIBTqVmzppYtW6YFCxbooYce0htvvKHJkyerU6dO1jFDhgxRnz591LNnT9WsWVMXL17U2rVrVahQIeuYefPmqUKFCqpfv76aNm2qOnXqWJvRvJSrdSSTkpI0d+5c/ec//1FKSoqeeeYZzZw5U/v3789XD9qwjiRQcLGOJFBwOXIdyVfXHLXbucc2edBu53a0HCeSLVq0UPny5XXgwAFNnjxZv//+u6ZOnWrP2gAAAJCP5fgeyTVr1qhv377q3bu3wsPD7VkTAADAXWXPp7YLshwnklu3btWff/6p6tWrq1atWpo2bZrOnDljz9oAAACQj+W4kXz00Uf1wQcf6OTJk+rVq5c+++wzhYWFKTMzU+vXr9eff/5pzzoBAADsxmKx36sgy/VT297e3nr++ee1detWxcfHa+DAgXrzzTcVFBSkli1b2qNGAAAAu7Lnd20XZHe0bFL58uU1fvx4/frrr1qwYEFe1QQAAIB7gKkFyf/K1dVVrVu3ti6ECQAAcC/hYRtz8stC7gAAALjH5EkiCQAAcC8jkDSHRBIAAACmkEgCAACnV9CfrrYXEkkAAACYQiIJAACcnkVEkmbQSAIAAKfH1LY5TG0DAADAFBJJAADg9EgkzSGRBAAAgCkkkgAAwOlZWJHcFBJJAAAAmEIiCQAAnB73SJpDIgkAAABTSCQBAIDT4xZJc2gkAQCA03OhkzSFqW0AAACYQiIJAACcHg/bmEMiCQAAAFNIJAEAgNPjFklzSCQBAABgCokkAABwei4ikjSDRBIAAACmkEgCAACnxz2S5tBIAgAAp8fyP+YwtQ0AAABTSCQBAIDT4ysSzSGRBAAAgCkkkgAAwOkRSJpDIgkAAABTSCQBAIDT4x5Jc0gkAQAAYAqJJAAAcHoEkubQSAIAAKfHFK05fG4AAAAwhUQSAAA4PQtz26aQSAIAAMAUEkkAAOD0yCPNIZEEAACAKSSSAADA6bEguTkkkgAAADCFRBIAADg98khzaCQBAIDTY2bbHKa2AQAAYAqJJAAAcHosSG4OiSQAAABMIZEEAABOj2TNHD43AAAAmEIiCQAAnB73SJpDIgkAAABTSCQBAIDTI480h0QSAAAAppBIAgAAp8c9kubQSAIAAKfHFK05fG4AAAAwhUQSAAA4Paa2zSGRBAAAgCkkkgAAwOmRR5pDIgkAAABTSCQBAIDT4xZJc0gkAQAAYAqJJAAAcHou3CVpCo0kAABwekxtm8PUNgAAAEwhkQQAAE7PwtS2KSSSAAAAMIVEEgAAOD3ukTSHRBIAAACmkEgCAACnx/I/5uTbRDI5OVmvv/66o8sAAADALeTbRjIpKUmvvfaao8sAAABOwGKx36sgc9jU9oEDB267/8iRI3epEgAA4OwKesNnLw5rJKtWrSqLxSLDMLLsu7Hdwt9VAACAfMthjWRgYKDGjx+v+vXrZ7v/4MGDatGixV2uCgAAOCMWJDfHYfdIVq9eXb///rtKlSqV7at48eLZppUAAADO4s0335TFYlG/fv2s21JTUxUdHa2iRYvKx8dHbdu2VXJyss1xiYmJatasmQoXLqygoCANHjxY165dy/P6HJZIvvjii7p06dIt95csWVJz5sy5ixUBAABn5ZIPA8ldu3bp/fff1z/+8Q+b7f3799eqVau0aNEi+fv7KyYmRm3atNG3334rScrIyFCzZs0UEhKibdu26eTJk+rSpYvc3d01bty4PK3RYhTA2C817xtuAPlEkZoxji4BgJ1c2TvNYe+94fAZu527foX7cn3MxYsXVa1aNb333nsaM2aMqlatqsmTJ+vChQsqVqyY5s+fr3bt2kmSDh8+rIoVKyouLk6PPvqo1qxZo+bNm+v3339XcHCwJGnmzJkaOnSoTp8+LQ8Pjzy7tny7/A8AAMDdYrHjX2lpaUpJSbF5paWl3bae6OhoNWvWTFFRUTbbd+/eratXr9psr1ChgkqWLKm4uDhJUlxcnCpXrmxtIiWpUaNGSklJ0cGDB/PwU6ORBAAAsKvY2Fj5+/vbvGJjY285/rPPPtOePXuyHZOUlCQPDw8FBATYbA8ODlZSUpJ1zM1N5I39N/blJb4iEQAAOD17rjg4bNgwDRgwwGabp6dntmN/+eUXvfzyy1q/fr0KFSpkv6LyCIkkAABwevac2vb09JSfn5/N61aN5O7du3Xq1ClVq1ZNbm5ucnNz0+bNmzVlyhS5ubkpODhY6enpOn/+vM1xycnJCgkJkSSFhIRkeYr7xs83xuQVGkkAAIB8on79+oqPj9e+ffusrxo1aqhTp07WP7u7u2vDhg3WY44cOaLExERFRkZKkiIjIxUfH69Tp05Zx6xfv15+fn6KiIjI03odPrW9du1a+fj4qE6dOpKk6dOn64MPPlBERISmT5+uIkWKOLhCAABQ0OWX5X98fX310EMP2Wzz9vZW0aJFrdtfeOEFDRgwQIGBgfLz81OfPn0UGRmpRx99VJLUsGFDRUREqHPnzho/frySkpI0fPhwRUdH3zIJNcvhieTgwYOVkpIiSYqPj9fAgQPVtGlTJSQkZLmfAAAAwNlNmjRJzZs3V9u2bVW3bl2FhIRo6dKl1v2urq5auXKlXF1dFRkZqWeffVZdunTR66+/nue1OHwdSR8fH33//fcqXbq0Ro8ere+//16LFy/Wnj171LRpU1NPF7GOJFBwsY4kUHA5ch3Jb46es9u5//lgwZ1ddXgi6eHhocuXL0uSvvrqKzVs2FDS9e/ivpFUAgAAIP9x+D2SderU0YABA/TYY49p586dWrhwoSTp6NGjuv/++x1cHRxl93e7NPfD/+jQD9/r9OnTmjRlup6sf33x1atXr2ralMna+s0W/frrL/L18VGtyNp6uf9ABQVdXyfrt99+1ayZ72nnju3648wZFQsKUrPmLdWj54tyz8MV/QHc3mPVyqp/lyhViyip0GL+eqb/LH2x6YB1f6snq6h7uzp6uGJJFQ3wVq32sTpw9Dfr/iJ+hTWidzPVf7SCSoQU0ZlzF/XFpgN67b2VSrmYKkmq/GBxDXqugWpXLauiAd468ftZzV68VdMXbLrbl4t7mD2X/ynIHJ5ITps2TW5ublq8eLFmzJih4sWLS5LWrFmjxo0bO7g6OMqVK5dVvnx5DRs+Ksu+1NRUHT70g3q+2FsLFy3VO+9O0/GEBL0c09s65vjPPysz09CIUa9r6X9XafCQYVr0+Wea8u6ku3kZgNPz9vJU/NHf1C92Ybb7C3t5aNu+nzR8yvJs94cW81doMX8Nm7RM1Z8epx6jPlWD2hGaOaqTdczDFUvo9Nk/9dzwj1St3Vi99Z91er1PS73Yvq49LgnATRx+j6Q9cI9kwVKlUnmbRDI738cfUKcOT2vt+q8VGhaW7Zi5H87W5wsXaPW6Ddnux72BeyTvXVf2TsuSSN5QMjRQR1a/niWRzE6bqIf14dguKlp7oDIyMrMdM+mVZ1ShTLCa9JqaJ7Xj7nDkPZLf/mi/eyQfC+ceSbvZs2eP4uPjrT//97//VevWrfXvf/9b6enpDqwM95KLFy/KYrHI18/v1mP+/FP+/v53sSoA9uDnW0gpl1Jv2URKkr9PIZ1LuXwXq8K9zsVisdurIHN4I9mrVy8dPXpUkvTzzz+rQ4cOKly4sBYtWqQhQ4b87fFmvggdBUtaWpomvzNBTZo2k4+PT7ZjEk+c0IL5n6rd0x3ucnUA8lLRAG8N69FEHy7Zdssxj1Ypo3YNq+s/S769i5UBzsnhjeTRo0dVtWpVSdKiRYtUt25dzZ8/X3PnztWSJUv+9vjsvgj97bdu/UXoKFiuXr2qwQNelmEYenXka9mOSU5O1ku9uqtBo8Zq+/Qzd7lCAHnF17uQlk3prUM/n9SY91dlOyaibKg+n9RTY2et1obth+9yhbiXWez4Ksgc/tS2YRjKzLw+PfHVV1+pefPmkqQSJUrozJkzf3t8dl+Ebrjm7artyJ+uXr2qwQP76eTvv+uDOR9lm0aeOpWs7s91UZWHH9bI0W84oEoAecGnsKdWTH9Jf15OVfsBH+jatazT2hUeCNHq9/vowyXb9NbsdQ6oEnA+Dm8ka9SooTFjxigqKkqbN2/WjBkzJEkJCQkKDg7+2+M9PT2zfN0PD9sUfDeayMQTJzR7zscKCMh6I3Ny8vUmMiKikl4fEysXF4cH8ABM8PUupC/ei1Za+jW16/e+0tKz/kO+4gMhWjOrr+Z9sUOjp3/hgCpxzyvo0aGdOLyRnDx5sjp16qTly5fr1VdfVbly5SRJixcvVu3atR1cHRzl8qVLSkxMtP7826+/6vChQ/L399d9xYppUP++OnToB02d/r4yMzJ05vRpSZK/v7/cPTyuN5HdOis0LEwDBg/VubNnree6r1ixu349gLPy9vJQ2RL/+50rXbyo/vFgcZ1Luaxfks6piF9hlQgpotCg6w/CPVj6eoCQ/EeKkv/4U77ehbTyvWh5FfLQc69+JD/vQvLzLiRJOn3uojIzDUWUDdWaWX311bZDmvLpRgUX9ZUkZWQaOnPu4l2+YsC55Nvlf1JTU+Xq6ip3d/fcH0siec/btXOHuj/XJcv2lq2e0ovRMWrasH62x82e87FqPlJL/122VCOHD8t2zP6DR/K0VtxdLP9zb/ln9XB9OfvlLNs/WbFdPUd9qmdb1NIHr3fOsn/MzNUa+/7qWx4vSeWbjlTiybN6tVdTDX+xaZb9J37/QxWaZV2LFvmXI5f/2fHTBbudu1bZgrtiSL5tJO8EjSRQcNFIAgUXjeS9x+FT2xkZGZo0aZI+//xzJSYmZlk78uxNU5IAAAD2UMCXe7Qbhz998Nprr+mdd95R+/btdeHCBQ0YMEBt2rSRi4uLRo8e7ejyAACAE2D5H3Mc3kjOmzdPH3zwgQYOHCg3Nzf961//0uzZszVy5Eht377d0eUBAADgFhzeSCYlJaly5cqSJB8fH124cP0ehebNm2vVquwXnAUAAMhTRJKmOLyRvP/++3Xy5ElJUtmyZfXll19Kknbt2pVlfUgAAADkHw5vJJ966ilt2LBBktSnTx+NGDFC4eHh6tKli55//nkHVwcAAJyBxY5/FWQOf2r7zTfftP65ffv2KlmypOLi4hQeHq4WLVo4sDIAAADcjsMbyb+KjIxUZGSko8sAAABOhOV/zHFII7lixYocj23ZsqUdKwEAAIBZDmkkW7dunaNxFotFGRkZ9i0GAAA4PQJJcxzSSGZmZjribQEAALJHJ2mKw5/aBgAAwL3JYY3kxo0bFRERoZSUlCz7Lly4oEqVKmnLli0OqAwAADgblv8xx2GN5OTJk9WjRw/5+fll2efv769evXpp0qRJDqgMAAAAOeGwRnL//v1q3LjxLfc3bNhQu3fvvosVAQAAZ2Wx2O9VkDmskUxOTpa7u/st97u5uen06dN3sSIAAADkhsMayeLFi+v777+/5f4DBw4oNDT0LlYEAACclcWOr4LMYY1k06ZNNWLECKWmpmbZd+XKFY0aNUrNmzd3QGUAAADICYthGIYj3jg5OVnVqlWTq6urYmJiVL58eUnS4cOHNX36dGVkZGjPnj0KDg7O9blTr+V1tQDyiyI1YxxdAgA7ubJ3msPee/8vf9rt3FVK+Nrt3I7msO/aDg4O1rZt29S7d28NGzZMN/pZi8WiRo0aafr06aaaSAAAgNwq6Mv02IvDGklJKlWqlFavXq1z587p2LFjMgxD4eHhKlKkiCPLAgAAQA44tJG8oUiRIqpZs6ajywAAAE6qoC/TYy98RSIAAABMyReJJAAAgCMRSJpDIgkAAABTSCQBAACIJE0hkQQAAIApJJIAAMDpsY6kOSSSAAAAMIVEEgAAOD3WkTSHRhIAADg9+khzmNoGAACAKSSSAAAARJKmkEgCAADAFBJJAADg9Fj+xxwSSQAAAJhCIgkAAJwey/+YQyIJAAAAU0gkAQCA0yOQNIdGEgAAgE7SFKa2AQAAYAqJJAAAcHos/2MOiSQAAABMIZEEAABOj+V/zCGRBAAAgCkkkgAAwOkRSJpDIgkAAABTSCQBAACIJE2hkQQAAE6P5X/MYWobAAAAppBIAgAAp8fyP+aQSAIAAMAUEkkAAOD0CCTNIZEEAACAKSSSAAAARJKmkEgCAADAFBJJAADg9FhH0hwaSQAA4PRY/sccprYBAABgCokkAABwegSS5pBIAgAAwBQSSQAA4PS4R9IcEkkAAACYQiIJAADAXZKmkEgCAADAFBJJAADg9LhH0hwaSQAA4PToI81hahsAAACmkEgCAACnx9S2OSSSAAAAMIVGEgAAOD2LHf/KjdjYWNWsWVO+vr4KCgpS69atdeTIEZsxqampio6OVtGiReXj46O2bdsqOTnZZkxiYqKaNWumwoULKygoSIMHD9a1a9fu+HP6KxpJAACAfGLz5s2Kjo7W9u3btX79el29elUNGzbUpUuXrGP69++vL774QosWLdLmzZv1+++/q02bNtb9GRkZatasmdLT07Vt2zZ99NFHmjt3rkaOHJnn9VoMwzDy/KwOlpr3DTeAfKJIzRhHlwDATq7sneaw905KuWq3c4f4uZs+9vTp0woKCtLmzZtVt25dXbhwQcWKFdP8+fPVrl07SdLhw4dVsWJFxcXF6dFHH9WaNWvUvHlz/f777woODpYkzZw5U0OHDtXp06fl4eGRJ9clkUgCAADYVVpamlJSUmxeaWlpOTr2woULkqTAwEBJ0u7du3X16lVFRUVZx1SoUEElS5ZUXFycJCkuLk6VK1e2NpGS1KhRI6WkpOjgwYN5dVmSaCQBAABkseMrNjZW/v7+Nq/Y2Ni/rSkzM1P9+vXTY489poceekiSlJSUJA8PDwUEBNiMDQ4OVlJSknXMzU3kjf039uUllv8BAABOz57L/wwbNkwDBgyw2ebp6fm3x0VHR+v777/X1q1b7VXaHaORBAAAsCNPT88cNY43i4mJ0cqVK7Vlyxbdf//91u0hISFKT0/X+fPnbVLJ5ORkhYSEWMfs3LnT5nw3nuq+MSavMLUNAACcXn5Z/scwDMXExGjZsmXauHGjypQpY7O/evXqcnd314YNG6zbjhw5osTEREVGRkqSIiMjFR8fr1OnTlnHrF+/Xn5+foqIiLiDTykrEkkAAIB8Ijo6WvPnz9d///tf+fr6Wu9p9Pf3l5eXl/z9/fXCCy9owIABCgwMlJ+fn/r06aPIyEg9+uijkqSGDRsqIiJCnTt31vjx45WUlKThw4crOjo618no32H5HwD3FJb/AQouRy7/c/qi/ZqHYj45z+0st7hZc86cOerWrZuk6wuSDxw4UAsWLFBaWpoaNWqk9957z2ba+sSJE+rdu7c2bdokb29vde3aVW+++abc3PI2Q6SRBHBPoZEECi4ayXtPwb0yAACAHLLjQ9sFGg/bAAAAwBQSSQAA4PTsuY5kQUYjCQAAnF5ul+nBdUxtAwAAwBQSSQAA4PSY2jaHRBIAAACm0EgCAADAFBpJAAAAmMI9kgAAwOlxj6Q5JJIAAAAwhUQSAAA4PdaRNIdGEgAAOD2mts1hahsAAACmkEgCAACnRyBpDokkAAAATCGRBAAAIJI0hUQSAAAAppBIAgAAp8fyP+aQSAIAAMAUEkkAAOD0WEfSHBJJAAAAmEIiCQAAnB6BpDk0kgAAAHSSpjC1DQAAAFNIJAEAgNNj+R9zSCQBAABgCokkAABweiz/Yw6JJAAAAEyxGIZhOLoIwKy0tDTFxsZq2LBh8vT0dHQ5APIQv99A/kcjiXtaSkqK/P39deHCBfn5+Tm6HAB5iN9vIP9jahsAAACm0EgCAADAFBpJAAAAmEIjiXuap6enRo0axY34QAHE7zeQ//GwDQAAAEwhkQQAAIApNJIAAAAwhUYSAAAAptBIIt+wWCxavny5o8sAYAf8fgMFE40k7oqkpCT16dNHDzzwgDw9PVWiRAm1aNFCGzZscHRpkiTDMDRy5EiFhobKy8tLUVFR+vHHHx1dFnBPyO+/30uXLlXDhg1VtGhRWSwW7du3z9ElAQUGjSTs7vjx46pevbo2btyot99+W/Hx8Vq7dq2eeOIJRUdHO7o8SdL48eM1ZcoUzZw5Uzt27JC3t7caNWqk1NRUR5cG5Gv3wu/3pUuXVKdOHb311luOLgUoeAzAzpo0aWIUL17cuHjxYpZ9586ds/5ZkrFs2TLrz0OGDDHCw8MNLy8vo0yZMsbw4cON9PR06/59+/YZjz/+uOHj42P4+voa1apVM3bt2mUYhmEcP37caN68uREQEGAULlzYiIiIMFatWpVtfZmZmUZISIjx9ttvW7edP3/e8PT0NBYsWHCHVw8UbPn99/tmCQkJhiRj7969pq8XgC03B/exKODOnj2rtWvXauzYsfL29s6yPyAg4JbH+vr6au7cuQoLC1N8fLx69OghX19fDRkyRJLUqVMnPfzww5oxY4ZcXV21b98+ubu7S5Kio6OVnp6uLVu2yNvbWz/88IN8fHyyfZ+EhAQlJSUpKirKus3f31+1atVSXFycOnTocAefAFBw3Qu/3wDsi0YSdnXs2DEZhqEKFSrk+tjhw4db/1y6dGkNGjRIn332mfVfNImJiRo8eLD13OHh4dbxiYmJatu2rSpXrixJeuCBB275PklJSZKk4OBgm+3BwcHWfQCyuhd+vwHYF/dIwq6MO/jipIULF+qxxx5TSEiIfHx8NHz4cCUmJlr3DxgwQN27d1dUVJTefPNN/fTTT9Z9ffv21ZgxY/TYY49p1KhROnDgwB1dB4Cs+P0GQCMJuwoPD5fFYtHhw4dzdVxcXJw6deqkpk2bauXKldq7d69effVVpaenW8eMHj1aBw8eVLNmzbRx40ZFRERo2bJlkqTu3bvr559/VufOnRUfH68aNWpo6tSp2b5XSEiIJCk5Odlme3JysnUfgKzuhd9vAHbm2Fs04QwaN26c65vxJ0yYYDzwwAM2Y1944QXD39//lu/ToUMHo0WLFtnue+WVV4zKlStnu+/GwzYTJkywbrtw4QIP2wA5kN9/v2/GwzZA3iORhN1Nnz5dGRkZeuSRR7RkyRL9+OOPOnTokKZMmaLIyMhsjwkPD1diYqI+++wz/fTTT5oyZYo1jZCkK1euKCYmRps2bdKJEyf07bffateuXapYsaIkqV+/flq3bp0SEhK0Z88eff3119Z9f2WxWNSvXz+NGTNGK1asUHx8vLp06aKwsDC1bt06zz8PoCDJ77/f0vWHgvbt26cffvhBknTkyBHt27ePe6CBvODoThbO4ffffzeio6ONUqVKGR4eHkbx4sWNli1bGl9//bV1jP6yPMjgwYONokWLGj4+Pkb79u2NSZMmWROLtLQ0o0OHDkaJEiUMDw8PIywszIiJiTGuXLliGIZhxMTEGGXLljU8PT2NYsWKGZ07dzbOnDlzy/oyMzONESNGGMHBwYanp6dRv35948iRI/b4KIACJ7//fs+ZM8eQlOU1atQoO3wagHOxGMYd3C0NAAAAp8XUNgAAAEyhkQQAAIApNJIAAAAwhUYSAAAAptBIAgAAwBQaSQAAAJhCIwkAAABTaCQBAABgCo0kgHyrW7duNl9T+fjjj6tfv353vY5NmzbJYrHo/Pnzd/29ASA/o5EEkGvdunWTxWKRxWKRh4eHypUrp9dff13Xrl2z6/suXbpUb7zxRo7G0vwBgP25OboAAPemxo0ba86cOUpLS9Pq1asVHR0td3d3DRs2zGZcenq6PDw88uQ9AwMD8+Q8AIC8QSIJwBRPT0+FhISoVKlS6t27t6KiorRixQrrdPTYsWMVFham8uXLS5J++eUXPfPMMwoICFBgYKBatWql48ePW8+XkZGhAQMGKCAgQEWLFtWQIUNkGIbNe/51ajstLU1Dhw5ViRIl5OnpqXLlyuk///mPjh8/rieeeEKSVKRIEVksFnXr1k2SlJmZqdjYWJUpU0ZeXl6qUqWKFi9ebPM+q1ev1oMPPigvLy898cQTNnUCAP6HRhJAnvDy8lJ6erokacOGDTpy5IjWr1+vlStX6urVq2rUqJF8fX31zTff6Ntvv5WPj48aN25sPWbixImaO3euPvzwQ23dulVnz57VsmXLbvueXbp00YIFCzRlyhQdOnRI77//vnx8fFSiRAktWbJEknTkyBGdPHlS7777riQpNjZWH3/8sWbOnKmDBw+qf//+evbZZ7V582ZJ1xveNm3aqEWLFtq3b5+6d++uV155xV4fGwDc05jaBnBHDMPQhg0btG7dOvXp00enT5+Wt7e3Zs+ebZ3S/vTTT5WZmanZs2fLYrFIkubMmaOAgABt2rRJDRs21OTJkzVs2DC1adNGkjRz5kytW7fulu979OhRff7551q/fr2ioqIkSQ888IB1/41p8KCgIAUEBEi6nmCOGzdOX331lSIjI63HbN26Ve+//77q1aunGTNmqGzZspo4caIkqXz58oqPj9dbb72Vh58aABQMNJIATFm5cqV8fHx09epVZWZmqmPHjho9erSio6NVuXJlm/si9+/fr2PHjsnX19fmHKmpqfrpp5904cIFnTx5UrVq1bLuc3NzU40aNbJMb9+wb98+ubq6ql69ejmu+dixY7p8+bIaNGhgsz09PV0PP/ywJOnQoUM2dUiyNp0AAFs0kgBMeeKJJzRjxgx5eHgoLCxMbm7/+8eJt7e3zdiLFy+qevXqmjdvXpbzFCtWzNT7e3l55fqYixcvSpJWrVql4sWL2+zz9PQ0VQcAODMaSQCmeHt7q1y5cjkaW61aNS1cuFBBQUHy8/PLdkxoaKh27NihunXrSpKuXbum3bt3q1q1atmOr1y5sjIzM7V582br1PbNbiSiGRkZ1m0RERHy9PRUYmLiLZPMihUrasWKFTbbtm/f/vcXCQBOiIdtANhdp06ddN9996lVq1b65ptvlJCQoE2bNqlv37769ddfJUkvv/yy3nzzTS1fvlyHDx/WSy+9dNs1IEuXLq2uXbvq+eef1/Lly63n/PzzzyVJpUqVksVi0cqVK3X69GldvHhRvr6+GjRokPr376+PPvpIP/30k/bs2aOpU6fqo48+kiS9+OKL+vHHHzV48GAdOXJE8+fP19y5c+39EQHAPYlGEoDdFS5cWFu2bFHJkiXVpk0bVaxYUS+88IJSU1OtCeXAgQPVuXNnde3aVZGRkfL19dVTTz112/POmDFD7dq100svvaQKFSqoR48eunTpkiSpePHieu211/TKK68oODhYMTExkqQ33nhDI0aMUGxsrCpWrKjGjRtr1apVKlOmjCSpZMmSWrJkiZYvX64qVapo5syZGjdunB0/HQC4d1mMW93JDgAAANwGiSQAAABMoZEEAACAKTSSAAAAMIVGEgAAAKbQSAIAAMAUGkkAAACYQiMJAAAAU2gkAQAAYAqNJAAAAEyhkQQAAIApNJIAAAAw5f8AeJM8jtqAZIQAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "['support_vector_machine_model.pkl']"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.metrics import accuracy_score, classification_report, confusion_matrix, roc_auc_score, roc_curve\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import joblib  \n",
    "\n",
    "# Veriyi yükleme\n",
    "data = pd.read_csv('data_vectorized.csv')\n",
    "\n",
    "# Veriyi ayırma (özellikler ve etiketler)\n",
    "X = data.drop(columns=['Label'])  # Etiket hariç tüm sütunlar\n",
    "y = data['Label']  # Etiket\n",
    "\n",
    "# Veriyi eğitim ve test olarak ayırma\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "# SVM modelini oluşturma ve eğitim\n",
    "svm_classifier = SVC(kernel='linear', probability=True, random_state=42)  # 'linear' kernel kullanıyoruz\n",
    "svm_classifier.fit(X_train, y_train)\n",
    "\n",
    "# Test seti üzerinde tahmin yapma\n",
    "y_pred = svm_classifier.predict(X_test)\n",
    "\n",
    "# Doğruluk hesaplama\n",
    "accuracy = accuracy_score(y_test, y_pred)\n",
    "print(f\"SVM Accuracy: {accuracy:.2f}\")\n",
    "\n",
    "# Precision, Recall, F1-Score\n",
    "print(\"\\nClassification Report:\")\n",
    "print(classification_report(y_test, y_pred))\n",
    "\n",
    "# Confusion Matrix\n",
    "conf_matrix = confusion_matrix(y_test, y_pred)\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.heatmap(conf_matrix, annot=True, fmt='d', cmap='Blues', xticklabels=[\"Class 0\", \"Class 1\"], yticklabels=[\"Class 0\", \"Class 1\"])\n",
    "plt.title(\"SVM - Confusion Matrix\")\n",
    "plt.xlabel(\"Predicted\")\n",
    "plt.ylabel(\"Actual\")\n",
    "plt.show()\n",
    "\n",
    "# ROC-AUC Hesaplama ve Grafik\n",
    "if len(set(y_test)) == 2:  # İkili sınıflandırma kontrolü\n",
    "    roc_auc = roc_auc_score(y_test, svm_classifier.predict_proba(X_test)[:, 1])  # Tahmin olasılıkları\n",
    "    fpr, tpr, thresholds = roc_curve(y_test, svm_classifier.predict_proba(X_test)[:, 1])\n",
    "    plt.figure(figsize=(8, 6))\n",
    "    plt.plot(fpr, tpr, label=f\"ROC-AUC: {roc_auc:.2f}\")\n",
    "    plt.plot([0, 1], [0, 1], 'k--', label=\"Random Guess\")\n",
    "    plt.xlabel(\"False Positive Rate\")\n",
    "    plt.ylabel(\"True Positive Rate\")\n",
    "    plt.title(\"SVM - ROC Curve\")\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "\n",
    "# SVM modelini kaydetme\n",
    "joblib.dump(svm_classifier, 'support_vector_machine_model.pkl')  # Modeli kaydet\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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