{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# scikit-learn-svm" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Credits: Forked from [PyCon 2015 Scikit-learn Tutorial](https://github.com/jakevdp/sklearn_pycon2015) by Jake VanderPlas\n", "\n", "* Support Vector Machine Classifier\n", "* Support Vector Machine with Kernels Classifier" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [], "source": [ "%matplotlib inline\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import seaborn; \n", "from sklearn.linear_model import LinearRegression\n", "from scipy import stats\n", "import pylab as pl\n", "\n", "seaborn.set()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Support Vector Machine Classifier" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Support Vector Machines (SVMs) are a powerful supervised learning algorithm used for **classification** or for **regression**. SVMs draw a boundary between clusters of data. SVMs attempt to maximize the margin between sets of points. Many lines can be drawn to separate the points above:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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mi1uwgCAiAcPYoNfrYTKFPh7McZzXalb8cRlcuvQZKisPoqGhHgAwe/ZsVFS8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\n79ecODGdpKSBT/w7nnQtevYcRc+ewV7SkXLNfL66a9IhOEIuLX0QMXE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PAAAA\ncklEQVSHnxN81PmOoiiVNdc/APYouxZPOo9ouR6bgD8rivIJYAL+AlisKEo0/W486RwadC2kN7UQ\nQggRZtL0QwghhAgzScZCCCFEmEkyFkIIIcJMkrEQQggRZpKMhRBCiDCTZCyEEEKEmSRjIYQQIsz+\nf8nbdptBj806AAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from sklearn.datasets.samples_generator import make_blobs\n", "X, y = make_blobs(n_samples=50, centers=2,\n", " random_state=0, cluster_std=0.60)\n", "\n", "xfit = np.linspace(-1, 3.5)\n", "plt.scatter(X[:, 0], X[:, 1], c=y, s=50, cmap='spring')\n", "\n", "# Draw three lines that couple separate the data\n", "for m, b, d in [(1, 0.65, 0.33), (0.5, 1.6, 0.55), (-0.2, 2.9, 0.2)]:\n", " yfit = m * xfit + b\n", " plt.plot(xfit, yfit, '-k')\n", " plt.fill_between(xfit, yfit - d, yfit + d, edgecolor='none', color='#AAAAAA', alpha=0.4)\n", "\n", "plt.xlim(-1, 3.5);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Fit the model:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0, degree=3, gamma=0.0,\n", " kernel='linear', max_iter=-1, probability=False, random_state=None,\n", " shrinking=True, tol=0.001, verbose=False)" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.svm import SVC\n", "clf = SVC(kernel='linear')\n", "clf.fit(X, y)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Plot the boundary:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [], "source": [ "def plot_svc_decision_function(clf, ax=None):\n", " \"\"\"Plot the decision function for a 2D SVC\"\"\"\n", " if ax is None:\n", " ax = plt.gca()\n", " x = np.linspace(plt.xlim()[0], plt.xlim()[1], 30)\n", " y = np.linspace(plt.ylim()[0], plt.ylim()[1], 30)\n", " Y, X = np.meshgrid(y, x)\n", " P = np.zeros_like(X)\n", " for i, xi in enumerate(x):\n", " for j, yj in enumerate(y):\n", " P[i, j] = clf.decision_function([xi, yj])\n", " # plot the margins\n", " ax.contour(X, Y, P, colors='k',\n", " levels=[-1, 0, 1], alpha=0.5,\n", " linestyles=['--', '-', '--'])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the following plot the dashed lines touch a couple of the points known as *support vectors*, which are stored in the support_vectors_ attribute of the classifier:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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Nt9uluVKQ0+nkL3/5o6rdYDBoJlyz2UzXrt2wWCz+khSTyYTFop30TCYTL7zw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\n7FFnKaFo26SHK0SEOXp0GzdvbsDr1ZO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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.scatter(X[:, 0], X[:, 1], c=y, s=50, cmap='spring')\n", "plot_svc_decision_function(clf)\n", "plt.scatter(clf.support_vectors_[:, 0], clf.support_vectors_[:, 1],\n", " s=200, facecolors='none');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Use IPython's interact functionality to explore how the distribution of points affects the support vectors and the discriminative fit:" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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VIyqxX7arzrg39t7EhMnTPb7Nh434xhje3vuua8JVQAEbF2xh1rh5Xt++EO4o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\nqqrK7Q5o8uRpZGV1BOruaa1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YqqqqVNXLNBoNCxYs9t5APaTVBl+r1coXX2xVZV2GhITQ\npUtX1T9gbGwcCxYsRq9PkKxL4bca7yFbRHV1tWp96SErWqPiYjMmk7r5xYsvflWV0KrRaOjduw+B\ngUEuLRxbe16NXwZfRVEoLS25/49iZuDAQapgGRwczJkzp7HZbMTGxpKc3Mk5b9DhcKjuU2k0GjIz\ns3z4UwjRuOb0kM3IyGxwFis9ZIV/s9lsaDQatzkDn366hrt37zgf1+fVVFdXExurfq+xYyd4c6gt\nwq+C78aN67lz5zbFxWaXHVC3bt2IiXH9F9FoNDz//EvExMRI1qXwWw2zLhtWwykpKX6sHrI6nR6t\nVitJT8KvFRUVcffuHVU1s7lzn3Zbsa937z507dqtXVcz80nwrc+6rL+E1rdvP6Ki1PNfCwruUlxs\nvp/m/eAyWmio+3mD0g9W+IuamhpVwpP0kBVtSWVlJRqNxu0tjQMH9nHmzCnn4/DwCFJT09Bo3H+f\ne/fu67VxthZeDb4bN27k8OHjlJaWuuyAUlNT3QbfefMWEB4eLvdjhd+qT3pqeBZrNpsb7SGbnp5B\nfHy8X2ddCvGwwsJCrl+/pqpmNmrUWAYPzlOt37NnL1JTU50HlJGRkS0w6tbFq8G3srKS2lob6ekZ\nLpfSkpKS3a4vPTeFP6ivZtawdWNtrYWrV29SVaXuIVtfzaxhwlN9OUUh/JHD4aC0tAQArVZdTOLK\nlcvs2LENeNDCMSUlhVh3N2SBrKyOQEevjbcteqJ+vo9it9sVs1m9sxKeJQXpm8fhcFBSUuw8sv+y\nHrJRUWEEB4e73IttK1mX/kK+x95jMpkwGs85DyLrq5n16pXL1KnT3a5fUHBXqpk1k1f6+TaFJIkI\nf9BYD9niYrOqnGJjPWQNhkyKi933ThaipVmtVuf3OTVVXYWvpMTM7t07iYwMxWp1OA8g09Mz3L5f\nfSKU8B6/ynYW4kk0tYesXp/wUEnFxrMupXm78Cfl5WUcOnTQeUBZX80sOTmF559/UbV+hw5pzJs3\nH4OhI1ZrgOQc+AHZo4hWp77UnGvS05f3kK2/fPZwD1kh/E19C0eTqa5iX/fuPVTrOBwODh8+CLhW\nM2ssnyY8PJzs7M7ExcmlfX8hwVf4JUVRqKgof+gsVnrIirbJarWybdsWVTWz4OBgunXrrvoOx8TE\n8swzz0s1s1ZMgq9oUfVZl3VVnkwuZ7TSQ1a0BXa7nZKSEud3e/DgIW4r9p0/fxabzeasZlb/3W6s\nYp+7e7ui9ZDgK3xCesiK9ubzzz/jzp3bqmpm3bv3cFu/+IUXXiY6OkYSVdsJCb7Co5rTQ7bhWaz0\nkBX+rrq62iXfYMCAgURHx6jWM5mKqKgoV1UzCw93P/87Lk7r7aELPyLBVzSL9JAV7c3WrZswGo1U\nVLgmLGVkZLgNvvPnLyIkJES+48ItCb6iUdJDVnja2bNnuHz5IkFBwWg0GjQaDVarlZiYGGbPnubz\n8dRXM3twpcZMz569SEtLV61bU2MlIECjqmaWmOi+J7gUXxFfRoKvaHYP2QfzY6WHrPhyFouFTz9d\nzYABg5gx4ynV8yUlxSxfvpyMjC506dLVJ2Pau3c3Bw/ux2q1uiyPjY1zG3wnT54qjS+Ex0jwbUee\ntIesXq9Hq42XHrKiSWpqali7dhXz5y9q9F5+XJyWhQsXsnz5GgICNHTq1KVZ23JXzaxjx07k5OSq\n1g0NDSU2Ns6l7nxdRzV1rWNAAq/wKAm+bVDzesjqXXZC0kNWeMqmTeuZN2+B8/ukKArHjm3GbD5M\nUFAyQ4Y847xEO3r0WFasWEZ2ducm36o4efI4GzeuV1UzCw4OcRt8+/cfSP/+A5v5UwnxZCT4tmL1\nPWRv3arm4sV86SEr/E5NTQ0hIaHOKWIVFRVs2vQ8U6bsICOjlspKWLv2L6Sl/Y6EhIkADB06nMOH\nDzJw4GAqKytdzmKLiorQ6xMYO3a8aluxsXHOamb1TS/qq5kJ4W8k+LYCj+ohGxkZisVSV5BCesg+\noCgKBw7sp7DwnvNSucPhwGarpU+ffo0WlRees2fPToYPH+l8vHPnv/DVr26h/qJKRAQsXHieDz74\nAUOGjAMgJaUDR44c5urVKyxfvkT1no19jzMzs8jMzPL4zyCEN0jw9RPuesjW35d110M2JuZBD9nO\nnTPRaMKkh2wDV65c5tixIwwfPoq8vCEuzymKwokTxzhwYB8zZ86We9heVFtrczZWdzgcOBzbuXwZ\nCgvr/hQVQVAQTJ9+gt2719CjxwSgbg64Xq+nU6fOqhaOUs1MtAUSfH2ssR6yJlORKutSo9Gg1WpJ\nTU390h6y0gfV1dWrV7h27Spz5853+7xGo6FPn350796TFSuWfWkikGg6h8PhvJXR8PZHSUkJmzYV\nkp//YN3AQEhOhvh4hbKyO87liqIQHR3T6L+hEK2dBF8vsdlsD5VTfHQP2YZVnuqzLqWVXdMoisLR\no90lT3IAACAASURBVIdddto2m439+1dSXX2bjIxRdO3aF6i7Dz5r1hw2blzvtqG4+HKKonDvXoHq\nILKiooJvf/sfCQgIcKlqptVqSUnJYuzYMyQkQEICaLV1AXjHDj0DBz6YgvRwNTQh2hrZsz8hq9Xq\ntpxiSUmJagfS1B6youkOHTrIsGEjnI8vXTrI5cvfZdq0k2i1cOpUBKtWTWbatDcJCQkhIiICRVGw\n2+1y9tuIqqoqwsLC3N5rXbLkQ5cGGGFhYej1CVRXVxMREUG3bt05deoEOTm90Wg0TJnyL0REfIvu\n3c3O15jNGq5cmcuoUakUFpZjt9tVCYNCtDUSfB/Tw1mX9fdmG+sh26FDqtusy/aW9ORrBQV3GTRo\nMFDXzOHSpe/z3HMnnc/n5FRiMKxkyZJUpkz5LwCGDh3G3r27GTFiVIuM2Z/cvHmDe/cKXAquWCwV\nfO1rr6DVus5/1Wg05OUNIzg4qNFqZtnZnfj00zXk5PQGoE+f6Zw6FcpHH71NWNgVamu1wFSmTfu2\n8zW7d+9k+PARCNGWSfBtoL6JtetZrEl6yLYiDZOnDhxYy9Spx92sA+Hh25yPtdp4KivVSW1tkaIo\nlJaWEBER6TbR7IsvtnH79i3n4/pqZna7+8vAgwfnPXKbHTtmc+zYEfr27Q9ATs4EcnImuF23uNhM\nWVmZquuPEG1Nuwy+DofDWU6xqMjkckb7ZT1kHy6nKFmX/qfh5UqL5TY6nfv1goPr5kK39YOkGzeu\nc/PmDZcWjrW1tcyZ8zSdO6urSA0alEdtba3zgNITLRx79cph//59HD16mH79BjS6XkFBAVu3bpYk\nK9EutOngKz1k25+GwbdLl3EcPhzNgAHqTPDKyq4ugbe1JvjUVzOLiAh3W0zi9OlTnDp1AnCtZtbY\ngWPXrgavjDMvbwjnz5/j009Xo9cnkJc31Pn5X7lyiTNnzpCRkcy8eQu8sn0h/E2bCL5Wq5XiYvXU\nnS/rIftwOUXpIds22Gw25xltVlY31qyZQc+eH9Gw58Px47Ho9S85H588eZzu3Xu0wGib7ubNG1y6\ndNGlhaOiKIwcOZq8vKGq9fv06UvXrl2dLRxbMrGvW7fudOvWnXv37rFx43qg7spSamoaM2bMkilz\nol1pcvA1GAzBwNtAJhAK/KfRaPzU0wNzp2EP2boqT6ZH9pBtWE5Resi2fYMGDebgwQPOe5HTpv2R\nFSs6EBy8hZCQEqqqOpGQ8DJ9+z6YWpSfn8+MGbNaashOiqJQWVmJyVTkLAf6sDt3bnPw4H7gQTUz\nnU7ndl2oqxblbxITE5k8eWpLD0OIFtWcM99ngEKj0ficwWDQAscBjwXf5vaQbXgWq9PpiIyMkiDb\nDiUlJbN3724sFguRkZEEBQUxadKPgR+7Xf/kyeNkZWX5dIwNFRTc5fjxY84DyurqKgB69OjF9Okz\nVesbDN2cB5VSzUyI1qs5wXc58Mn9vwcAti9Zt1ENe8g+nPT0ZT1k66ftSA9Z0ZiZM2ezfPkSpk2b\n8aVF9U+ePE5FRQVDhw73yjjqq5mZTCYAt31qLRYLJ04cc1YzS0urawyQnq7uJwsQExNLTEysV8Yr\nhPAdTXMnsxsMhmhgDfCm0WhUVz+vo9QnPRUWFlJYWEhRUZHz/+56yMbHx5OQkIBerychIYGEhAR0\nOp3U3xVN4nA4WLduHTU1NQwfPpzk5LrLsoqicPjwYfLz8+ncuTN9+vTx6HaLi4vZsmULhYWFmEwm\nZwvH5ORkXnnlFdX6dfkKxeh0OqlmJkTb8cjLrs0KvgaDIR1YCfzJaDS+09h6K1euVA4ePCo9ZL1M\nElUaV9/ZqKSkGKgLyjk5uU3uaJSQEM3Nmw/mfldXVzFgwCDVemVlpfzlL38iJCTEJWs+MTGB7OzO\nqrHt3buM6upNaDS1OBz9GT78H3w+hc1oPMC1a+8RFnaP6upUunT5KtnZvXw6BpDvsS/IZ+wbCQnR\njwy+zUm4SgI2Aa8ajcbtX7ZuRESEqoesP2RdivajrgrTkEev2Air1crq1SuwWi3cvn3PuTwoKIh+\n/QaovsfR0TG88so3H1nNTFEU1qx5jVmz3icxsS4jv6ZmNe+8s4nJk5f77H7uoUPL0Ov/H88++6Dc\n444dn3Py5B/JzZ3okzEI0R41+czXYDD8DngaMDZYPMVoNKpv1IIiR1neJ0ezTacoChUV5c6sebPZ\nxLhxE1XBVFEU/vCH36LVRhMSEumSb5CWlt7sg8jjx7fSufMCOnZ07WRls8HSpf/MxIk/avbP9rjs\ndju7do3k6adPqZ77+ONhjBv3uU+TFuV77H3yGfuGV858jUbjd4DvNGtEQviB5cuXcPv2LVU1s/79\nBxIf//+3d99xUd3p4sc/QwcBkaJ0sR5BQRFbFKxYsbIx9pTVbMre7N3k7ubuzd3Nb/tm6727m93c\nTVnXWGJLosEae0FENERQdESJBQSlI21gyu8PFMUZFBBmmOF5v16+XpnvOXPOMyfDPKd8v8+3aUks\nlUrFK6+8RmCgd7v+aBUV7WHq1DqjdgcHcHQ81W77eZSsrDRGjTJOvAD9+39Ffv5NAgODzBKLEF2N\n9PAQNkGn01FSUtKk13xc3AS8vHqYXNfd3cOomllz9YQ7psLZo06MzXO1aW/vSF2dCjC++1Vfb4+r\nq/w8CNFR5K9LWL2kpO2o1ReMqpkNGhRhMvkuWrTU4mPAe/ZM4PLlf9K/f9Or3/p6qK8fbZYY6urK\nSE2FAcYlnklPD+OZZ3qZJQ4huiJJvqJTMlXNLCZmJH369DVat1u3bgQEBDaZI/lexz5TLJ14AaKi\nJpCU9CwuLqsJDm4YDVBVBWvXTiYh4ftmiaGwcBsREQb27YP4eFCpQKeDXbugrk4SrxAdSZKv6HQO\nHtzP6dPGzz179w4zmXwnT443R1jtbvbsP3L69CSOHduNnZ0GO7sxzJnznNnGtDs41DB8OOTnw+ef\ng6NjQ4ev8eOhtlaqZwnRkST5ig73cDWze2VDFWWQybGyfn496du3n9E4cFubwlGlUjFy5BxgjkX2\nbzAMo6ZmMwEBkJh4v12rhbq6SIvEJERXIclXtJvm5sf96qvTHDiwr0mbnZ1dsz1pIyOjiIyM6pAY\nxX1jx65i3bodrFx5gnsjpgwGWLt2BBMnfteywQlh4yT5ilbTarWNcyM/OPmFv38ACQnGV3EBAYGE\nhw9unKBdqpl1Di4uLsTHb2bdut/h6pqKSqWnujqG2Nj/xN3dw9LhCWHTJPmKZmm1WpP1hnNzb7B5\n8ydN2pydnYEAk9sJDAyS8aKdlLu7JzNn/tLSYQjR5UjyFWi1Wm7ezGvSu7i4uBhXV1deeGGV0fq+\nvn5ERw9/oGyor0zhaEZ37pRz7NgvcHNLQaWqp7Z2KIMGvUHv3uGWDk0I0UKSfLuIhnmSK03eTqyt\nrWHjxvVN2jw9PfHy8jL5HNfd3Z2pU2d0aLzCNK1Wy/79S1i16jj3K1teZPv2Mzg5fUZAQJgFoxNC\ntJQkXxtkMBi4fDn77jPZ+72LdTodr7/+Q6N6xN26uTN2bCxeXj0an8vKFI6d04kTG1i8+MHE22De\nvMt8/PFfCQj4o2UCa6WLF49z48a7uLqeR6t1paoqlqef/h9LhyWE2UjytVJarZaSkhJ8fX1NLt+9\neye1tTUA2Nvb371F7INGo8HV1bXJuiqVitjY8R0es3hyWm06np6ml7m5XTJvMG10+XIaev1Kli7N\nb2zT6y+yZs01EhK2yuML0SVI8rUSavVFCgryG3sYl5WVYTAYWLnyJXr1alrJSaVSMXlyPC4uLnh7\ne+Pl1UOmcLQRWq07BkNDNSrjZdbRQzkn532WLctv0mZnBzNm7Cc1dTtjxsy3UGRCmI8k306iurqa\n4uIifHx8Tc7leuZMGrm5NwBwdXUjKCgYHx9f7OxMXyUMGSJFEmxRePhzHD++jri44ibtBQX2ODsn\nWCiq1tHpUk22BwQYyM3dA0jyFbZPkq+FXLqk5urVnLvPZIuprq4CYN68RBRlkNH6924L+/j40q1b\nN7PGKjqPkJD+JCe/za5dv2XatJvY20NqancuXlzOrFlLLR1ei1RWVpls12rh9u3LZo5GCMuQ5NsB\n9Ho95eVllJQU4+XljY+Pj9E633yTw9mz6ahUKry8vAgICMDHx9fkLDwAoaG9OzpsYSXGjXuBiooF\nbN26Dr2+lvDwRBISjGted1ZlZT6UlBTi7d20fc+ehvrdQnQFknzbSU7OZc6fP0dxcTElJcVotVqg\n4Yp17NhYo/VHjhzFsGHD8fb27qD5YoUt8/T0YsqUf7N0GK2i1+s5fz4VvT6CvXsvEhYGY8ZAdTV8\n+SX4+kJVVYylwxTCLCT5tkBdXR2lpSUUFRXh7u5u8uy8tLSUCxeycHR0bJwIwNfXt9kzeW9v46th\nIWxVevoXlJT8nqeeyqB/fwP79jlTVKQhKQlcXGDmTNi8eSyTJr1g6VCtmk6n4+TJrWg0meh03owe\nvbLZqTWFZakMBkNHbt9QWHinI7ffYXJzb3Dy5AmKi4soLy9vbA8Pj2DOHOMOIdXV1dTX1+Hp2d3s\nQyX8/Dyw1uNsLeQYt93165e4cyeBiRNvNWk/dMiZrKwgevbsRnX1aObN+y319XIXqK3Ky0s4eHAF\niYnH8fU1oNVCUlIY3bv/gcjIaYB8j83Fz8/jsUmgy1353qv0dK/4hIODA1FRw4zW02q15ORcoVs3\nd0JDe+Pr23A16+9vun5xQw9lmQNViIdduPAhy5ffMmqfNElDXt4kJk5sKK7h5SWJ4UkkJ/+EF188\n1jgMzcEBFiy4ysaNb1NfP0keb3UyXSb5FhcXs2fPToqLi6itrW1s9/X1M5l8g4NDeO21140KUggh\nWsfZubBNy0TLGQwGunVLNjn+e+bMLA4e3E5s7NPmD0w0y+qTr06no6ysrLH4hEajYeLEyUbrOTs7\nk59/kx49ehAa2hsfn4Yyir6+fia36+DgYHJGHyFE69TWBpssDGIwQE1NoGWCsjEGgwFHxxqTyzw8\noKamxMwRicex2uyi0WhYt24NpaUl6PX6xnZ7e3vi4iYYzRXbrVs3Xn/9hzKHrBBmFh39Mrt2bSMh\n4VqT9n37gomKesVCUdkWOzs7qqqGAPlGyw4f7kl0tBQu6Ww6XfKtra1tnNru3rCdefMSjZKmk5MT\nOp0Wf/+AB65ife5WfTIupahSqSTxWkh9fT0ODg5Ss9cG6PV6UlO3U1V1lZ49Y4iKenxN8F69gigr\ne58NG94hNDQNOzu4ejWGoKAfEhTUxwxRdw2Bgd/l+PFMYmMLGttu3XIgN3cpkZE9LRiZMKVT9XZe\nvfpDCgtvG7WvXPmSyUIVokFn7cF48uQ6KivX4uFxhZoab2pq4omP/5lVdvzorMfYnK5fv0hm5qvM\nnn0GX18DOTlO7N8/galTV+Pu3sxsDw8pLCxEr9fTq1cvo2WPO8b19fWkpGyirq4Af/8xDBliPH6+\nq7t0KZVvvnkfN7cc6up64Og4m7i4FxpPfOV7bB4W7+1sMBioqCi/Ozl7ESUlJRQXFzF9+iyTydTX\n1xd3d/e742R9GsfLSqcn63Py5DoU5QcMHFh9t+U2Gs1FPv64iPnz37dobKL1DAYDmZlv8Pzzpxvb\n+vatY9WqfaxZ85/Mnv1ei7bj52e6j8XjZGencu3a68yefQ4PD8jOdubzz+OZMeOf8vvwgIEDRzNw\n4GhLhyFaoEOT77p168jIyGrSplKpKC8vNZl8TY2fFdbpzp21DyTeBs7OMHTobq5du0Tv3gMtFJlo\ni6ysNGJjTxm129mBr+9RNBoNzs7OHbJvrVbL+fNv8Nxz57g3zfSAARr69NnJhg1vM3Pm7ztkv0J0\npA5NvmFhYdTVGRqvYL29ffD29pZexDauvr4eT88rJpeNHFnOhg2HJPlamZKS64waVQfAsWNQVAT2\n9lBfDw4OJVRVVXZI8k1L20xu7m/p3z+bffugshJmzIDu3RvGsbq5HW73fQphDh2aBePi4hg0yHgM\nrbBtDg4O1NR4A8bP7/PyHPDx6Wf+oMQTGTJkEsnJ/lRWFjBiBMTFNbQbDPDxxzqqqorbvWRqevoX\nhIa+zqxZ959R6vXw8cfw3HMNQ5ccHSvQ6/UyX7WwOvKNFe1OpVJRUxOPRmO8bN++kQwfPsX8QYkn\n0qOHD1lZ0/Hzg5CQ++0qFTz3XC0XLvypXfen1WrJy1vNkCFNOwfZ2cGUKXDq7h3wqipFEq+FlJQU\ns2/fBxw9upG6ujpLh2N15P6v6BDx8T9j7doioqJ2M3JkOXl5DuzfP5KhQ/8sQ46slK9vX8aNM71M\np/uc/ftLcXZOIDZ2RZv/H5eWFpGS8t94eSXj65vL1q3QuzeMHHl/nZAQSE+H9HQv/PxebNN+HkWn\n05GefpC6uhqGD5+Gi4uLyfXKyko4ffpjDIZqeveezsCBXWdGpn37fo2f379YtKiAmhrYvfuPdO/+\nE6Kj51o6NKshyVd0CEdHR+bNe5/r17P55JND+Pj0ZdasKZJ4rZhKZY9e3/Cs92GenjXMn7+bgoJ9\n7NlziZkzf9nq7ev1eo4cWcGqVU3LJJ4+DRkZEBXV8LqiAtLTB+Pq+hOGDZvVxk9j2tmzuykq+hUT\nJ2bg6gqHD/dFp3uZuLiXm6yXmroeO7tf8MwzN7G3h8zMv7BtWyJz577beCX+zTcXuHx5B3Z2rowa\n9SweHi0bjtXZpaRsIi7uT4SENFzturvDwoVqdu9+k6KiMfj6ypjilpD7NaJDhYYOYOrU7zB8eLwk\nXis3YsQy9u/3N2o3GBo6XgH4+2sJC1vPrVu5rd7+kSMbWbDghFEZyhEjIDv7/uvt26P4zneOtXvi\nvX07H632dRYvzsDfv6FT17x5OYSH/5yvv97XuF5hYQFOTj9l1qybjScikZHVLFq0jsOH38VgMJCU\n9AZ2dvEsXfoLvvWtt8jKeorU1A3tGq+lVFdvb0y8D5o+/SZffSXDCFtKkq8QokV69PChquo/SEu7\nPz9sTQ2sW9fwHPaeuLhiMjI+a/X2Kysz8PU1XfTH3h6uXXNgzZoxDBz4Lg4ODpSVlXL+/FdUVJSb\nfE9rpae/z/TpN43aw8MrKSzc+MB6/yQ+3niWJk9PMBgOcOTIB8yb9xEjRjQ8r3Z0hNmzb+Ds/Da3\nbhlv39o4OpaZbLeza36ZMCbJV3RZer2empoaOrjKm02Ji3sJnW4X69e/zJ//7MnBg7BwIXh7319H\nowEHB/dWb1ul6mmykx5AXl4E2dnbmDlzL0FB4SQlfZerV0cRFjaRK1dGsWPHv1N/7/K7jZycik3O\nCnRv2T329lU018fL0bESnW4vPj7G36n4+NucPfvPJ4qxM6ipMV0S9M4dsLOLMHM01uuJkq+iKKMV\nRTnUXsEIYQ719fXs3v0Wx46NJitrMAcPTuH48Q8sHZbV6NcvkmnTfoeX17eYNQvu9UcqL4evvoKN\nG0MZM2ZJq7c7adJLfPFFfwwGSEmBnTvh9m3Iz3cgIOAlhg4dj0ql4ssv32DFirVMnXqLsDCYNi2f\nJUtWs3fvm0/0ubTaPjTXabe2NrTxvz09nyIvz3Sd+OrqQTg6VppcplKBvb31l3YcOPAlDh4MatJm\nMMDmzSMZO3aFhaKyPm1OvoqivAl8AHRMWRshOsju3d/jmWfe5emn1cyYUcTixaeJjn5LEnArxcb+\nlA8+GEdhIWza1DD8x88PgoNL2LfvNaqqqlq1vW7duqHV/hvvvutGWFhDMY2MDBUffBBJbOzzAJSW\nlhAaupeHy4O7uIC//x4qK9ue3J566kU+/XSwUfvhw4EMGLCq8fWIEQkkJU3l4QvtnTv7EhHxGtXV\npgvIFBaqcHEZ0eb4Oos+faJwdPyQDRtmsm1bIFu39mHt2iWMG7fBKuu2W0qbJ1ZQFCURyADWqtXq\np5pZrVUTK4i2kWLpLXfz5lWqqyfw1FOlRss2boxh8uSDJjuGyTE2TavV8t578xg69Fhj6cdJk8DV\nFX772xBCQhYyYsSrLeoB6+XlwqZNMSxfntmkvbRUxd69P2XKlNfJzDzFgAHxTcYa36NWQ0nJafr3\nb3v1tBs3LnHu3E/x80vDyamO27ejCQj4HoMHN50jXKPRcOjQb3BxOYqdXS21tZEMHPg9wsIGc/36\nRW7dWsysWTmN6+t08P77k0hM/Nyi45Lb+3us1+tRqVTSmfIhHTqxglqt/kxRlLC2vl8IS8jKOswz\nzxgnXgAfn2+oqqrC3b31zysBcnLOkZ39Ic7OudTV+REcvJyIiGYGxtoItfok/funMHduQ8eiujpI\nSmoYFjR58g2Cg//EmTPbKC19nwEDRj1yW0eOrGfu3Eyj9h49DMAu4HVCQgagVvciJMS4w9OVK8GE\nhwc+0ecJCRlISMgGqqqq0Om0REV1N7mes7MzM2b81OSy0NBB6HRrWL/+L7i6ZqDTuVBTM46ZM39i\ncwVBbO3zmFOHj/P18/Po6F0I5Di3VETEcK5edaJfP+OHe9XVfoSG9mx23udHHeOvvtpLff23Wb78\nfm/Ws2d3kZX1RyZMeOHJA++krl//Oc8+q2187eQE3/pWw23oqVMhK6thuM6WLb9j7Ni9j9xWdXUu\nns0MhXVzK8PPzwM/Pw9On55DXd2HjVfaALW1UFk5jz59AtrjYz3x35OfXyyjRnXOKQ/lt6Jz6PDk\nK7fqOp7cEm25wMAodux4in79jjRp12igrGwyJSXVJt/3uGN88eKvWLq06TCSoUNL2br1D+Tnz7fJ\nyURyci4xbNhXJpf16QNHj8KYMQ2v/f1TyMrKeeSUgoGBY/jmGyf69DE+MbpzJ7Tx+I8f/w7r12sJ\nDNxLv375XL4cRH7+TKZP/7n8HTyG/FaYR0tOcNrjF0HGaQirEhPzF1avfo0JE04SFlbH6dPdycyc\nwYwZv2jT9m7fvk3v3ukml40bl0Vm5nGioyc+QcTmZTAYSE3dxp07u7C316DTDWXcuFdwc3Nrsl5t\nbRW+vqa7B7u5wZUrMP/uLKH29gb0ev0j9xsTM4X335/IqlVfNqmilZHhiZ/f842vnZycmD37L1RU\nlJOfn4eihBATI1dz1qSiopTk5J/h6pqCnZ2G2too+vd/nb59oy0dmtk8UfJVq9VXgbHtE4oQ5hEQ\n0IeEhCTOnTtBaupFFGUCc+f2b/P2HBzs0WpN36rWaOxwcLCuAQE7drzJjBkfERjYcDu5rm4ba9fu\nZdKkLXh43H8GqihRHDs2hH79zhltIyUFXn31/uurV6OZOrXXI/erUqmYNu1frF37Fh4eR+jWrZKS\nkoF4e68kJmaO0fqent3x9DT9TFZ0XlqtlgMHlvLiiw+WEc1hz56vuX59M6GhgywZntnI03LRJalU\nKiIjxxEfv5KQkLYnXgBvbx+uXx9pcllKyjAGDx79RNs3p4sXTzF69NrGxAsNz3FfeOEkycl/bLKu\nvb09Li6vkJHR9EHtqVMQHt7Q4xng4MEgAgP/o0X7d3d3JyHhL4wb9xUREeeYOnU3MTFPP9mHEp1K\nSsonLFqUbFTQZMaMq2RlvWeZoCzA9h5ECWEBAwe+zaefXmP+/Gzs7RuKDnz5ZRA9e75lVT1Cb9xI\nIi7O+Lm3nR24uKQZtY8Zs4KMjCA2bFiHs3MBtbWBGAxPoVKdpaDgNjU1QUREfIfQUKVVcdjb2+N6\nL3t3Anq9noMH/4yd3T4cHO5QUzOQ/v1fpV+/rjOTUXuprz9L92ZuWLi6ZpteYIMk+QrRDvr2HYaP\nz342bfo/7O2vU1/fk2HDXqRXr2BLh9Yqjx72b3roYlTUZGCyyWW2IinpNZ55Zu0DvbHPcvDgCbKz\n1zx2CJVoSqv1xGDAZClPrbbrPEaQ5CtEO+nevQdTp/6XpcN4Ir17LyAj40OioppWp9LpoLa2ayaZ\nK1cyGTHic6NhUJMn57Fu3bsMGPAxAAUFN8jIWIO9fQ1eXuMZPnyaFJ8wYejQb3PgwFqjySkKChxw\ndk6wUFTmJ8lXCNFIUYaza9e38fT8B2FhDT2ZG2YuiiU+/geN6+XkZJKd/U+cnW9RWxtAePiL9O7d\nuo4yWq2WzMzj2NnZM2TIWAwGA2lpuykvP4pO50xExPInfh7fHnJy9rJ0qel6zW5u5wFITv6Q7t1/\nzdKlRahUcOPGe3z22Szmzl0tJRcf0qtXMNev/4pt237JrFlXcXSE48e9+eab5cyYsczS4ZlNm8tL\ntpCUlzQDGbvX8SxxjGtrazl06B1cXFKws6ununoow4e/Qa9eJmortrMzZ/ZQWvoF9vYaDIbhjBu3\nCmfnhl7b6elf4Or6BnFxtxvXP3TIH73+XaKiprVo+2lpm6mq+l/Gjj2HXg9Hj0ZSUNCNRYtOExys\nxWCAEyd6kJ//QyZM+Lcm7y0vL+Xkyb/h5HQJrbY7gYGLGTy44yqJHTz4PvPn/wBnE53Wt2wZRnj4\nRm7fjmPy5MImy2pr4dNP32LatB91WGyt1Zl+K6qqqkhN/QSdroohQ+YTENDb0iG1m5aUl5TkawM6\n0x+UrTL3MdbpdGzbtpCVK/c3mURg48YhDB36Gb6+xpPam0NDx6PJLFliXFxjw4aniI/f89hbrVeu\npAOJjBlzf5q+7dth+vT7MyTdc/RoDzw9DxMU1DCN3c2bOVy4sIyFC883jgXOzHTn4sW3mDixaZJu\nL9XV1Xz11VgWLMhp0l5fD5988j0cHLqxZMlvTD7D3Lw5lkmTdnVIXG0hvxXm0ZLkaz3dMIXoQlJS\ntrBw4X6j2XsWLTpHWtpfOmSfer2e5ORNHDjwKgcOvEZa2g6juY4vXTpPTMzXJt8fHn6GGzeuP3Y/\nV66saZJ4oaGj18OJFyAurpRz59Y2vs7IeIfFi883KcIRGVmJh8dfKSsreey+28LNzY1u3X7GF1+E\nor07AuvaNUc++mgmkyb9GJWqttl5gO3tazskJmH95JmvEJ1QXV0qPj7G7SoVuLgYF7V4Ujqdv6Hd\n/wAAEYVJREFUjs8/f4GFC7fh69vQlpe3ju3blzNv3l8ar2bt7FTo9aYzjV5v16JhVU5OhUZtzb2t\nYQ5cTeNrNzfj4U4AU6fms3nzJuLjX3ns/tsiOnoeFRUT2bJlNVCOj884EhOnoFKp6NlzEleu/K2Z\neuHGUxQ+qKyslJKSEoKDQ3B6sFi1sHmSfIXohHS65se46vVuzS5rq6NHP2L58m14PFClMShIx6xZ\n6zh9ejojR84GYMCAwezbF8OgQaeMtnHx4gimTXv88+ja2mCjoSYPz417z9WrTvj6tmwYUwc/QsPT\nszvx8d9vsr9Dh/6BXr+f7GxPTp0qYvx4CLo7z/y2bQOJjPx3k9uqqCjjyJE3CA09QmBgEampA9Bo\nFjFlyg+kh3QXIclXiE5IpxvIyZMOjBmjbdJeWqrC3j6+3fdnMBxtknjvCQrScezYXqAh+apUKvz9\n32T//u8xZcpNVKqGW8Z794YQFNSyjkVRUS/z5Zc7mD79RmPb2LGwZo0jzz13PwtXV8OePXNITJz8\nQNtI4IrRNvfvD2DkyMUt+7DtJCnp+yQm/uvulIcN1q93pbq6P66uI4mM/B6BgX1NvvfgwRdZtWpv\n4wlIRMQlCgp+w5Ejrh327Fp0LpJ8hehkTpz4J0OHvk1enpbk5IbEpFLB+fNOpKQsYe7cle2+T5Xq\nUZMe6Jq8ioqaxs2be9iw4QOcnAqorQ0gOvrlFhcUCQzsQ3n5P9iw4feEhJzGYLDjxo0RhIW9ytq1\ne3B1PYdO54JeP5F5815rciUYFfVfbNyYadThqqLiNby8vFv7sdssOzudkSM3N0m8AMuW1bB+/TCm\nTfvfZt978eIp4uKOGD0n9vfXotd/Bkjy7Qok+QrRiWg0GnS6vxEVVUFUFOTmwhdfNCTfS5eG8Nxz\nf+2Q/Wq1I9FodhgNpykuBmfn8UbrBwaGERj4qzbvLzw8lvDwWIqKirCzUxEe7nO3J+7UR74vMLAP\n3brt4pNP/oaTUzZarScBAYuYOLHtc+cWFuZz+vRvcHM7DeipqRlBdPSPHnkycfXqLpYurTK5zMXF\ndIe0e65fP0NcnOmOWK6uueh0umbnlBa2Q5KvEJ1IevoBJky4X982OLjhH8DhwzmUlpbQo0f7X+GN\nH/8qq1cf5oUXDjUm4MpK2Lx5HomJz7T7/u7xvde7qxW6d+/B9Ok/bpf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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from IPython.html.widgets import interact\n", "\n", "def plot_svm(N=100):\n", " X, y = make_blobs(n_samples=200, centers=2,\n", " random_state=0, cluster_std=0.60)\n", " X = X[:N]\n", " y = y[:N]\n", " clf = SVC(kernel='linear')\n", " clf.fit(X, y)\n", " plt.scatter(X[:, 0], X[:, 1], c=y, s=50, cmap='spring')\n", " plt.xlim(-1, 4)\n", " plt.ylim(-1, 6)\n", " plot_svc_decision_function(clf, plt.gca())\n", " plt.scatter(clf.support_vectors_[:, 0], clf.support_vectors_[:, 1],\n", " s=200, facecolors='none')\n", " \n", "interact(plot_svm, N=[10, 200], kernel='linear');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Support Vector Machine with Kernels Classifier\n", "\n", "Kernels are useful when the decision boundary is not linear. A Kernel is some functional transformation of the input data. SVMs have clever tricks to ensure kernel calculations are efficient. In the example below, a linear boundary is not useful in separating the groups of points:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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/roVHxyRsQRg1kZgdwLV6y6qqSgYGBvDw8MTLy8feYY0J/Uf9g0n5GhkyVhxf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\nOrz9bDabOX/+nNWZuAICBhAQYHkF3JGGIU1wzrL8tOtpQpKtj7l9EJq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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from sklearn.datasets.samples_generator import make_circles\n", "X, y = make_circles(100, factor=.1, noise=.1)\n", "\n", "clf = SVC(kernel='linear').fit(X, y)\n", "\n", "plt.scatter(X[:, 0], X[:, 1], c=y, s=50, cmap='spring')\n", "plot_svc_decision_function(clf);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A simple model that could be useful is a **radial basis function**:" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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mlgX797+PBQt68Jd/+beoqanDVVddA+OQnXiCLsYNTMatry8QodTvTB5EUMo3\nytc4LhmGWBq3abkeVyYWLVqNQ4esC2v09vago2N+2u9fuPBkVCzjWbt2Bv39P016XZ/cRNENt7sG\nHo8XHo8XbnctRNED/V4mIipDliOIREIIh2cRDs8iEglBliNQFDlqUThlkdKRolVNqRO5QquAOwEV\ngnno0EF84Qu/n/T6W2+9gc985r/hc5/7NHbseDrn7X73uw/jRz96HLfcsh2RSPJk4hzFiBDVhVKf\nUMpbKIHE4wLMDwCVTkNDIwYHb0UovlAQJieB6ek7MjZ8FoSZNO+lz0HW4TgOPC9AFI0gKLe7Dm53\nHVwuTzSgQ4gFHMlyBJI0h3A4GBNRfQ2YuH/taHhQ8CZsgh4Lk66xAPSNxzlK7pJ99NH/xIsv/gq1\ntfGF0WVZxkMPfRvf//6PUFNTg89//tO46qpr0NjYVKKR0oLddW2dSAHJbTypar46Jf6JtXlpWa/b\nvv3/4Oc/r4HP9xzmzz+HoaEuzM7ejltu+auM3w2Hl0NVNfB8/DmLRDQoyuq8x2SVFJ8c+JG+B2R2\nuXzpxpD38CsS2qxdq/FQ8pOynZILZldXN77xjX/A174WPyn09Z1GZ2d3LMJw/foNeP/9Pbj++pvy\n3FNutUJpIjnwxYmc0eK7vjLVfC0FRocSc3ELDW+//SOo6ksQhGmEw4uxaNHvYtGi9bbuWxRFbN/+\nLUxM/C9MTFzE5s0L4HZnF5G5desX8PjjL+Leew/GjfuxxzbixhuTvTeFYBX4oe/PquuGdS6fgOwa\nKdPhkqUL2iw62sbjHCUXzGuvvQHDw0NJr8/OzqK+3hv7u67Oi9nZ1G6n3LH/EciqklAhFN6XstRY\nnwd6GlNnd51efPFv8YEP/BcaG/XPH8bOne/g5Ml/wtKll9s+qpqaGnR0dGQtlgDQ0NCESy75CX7y\nk79HTc1uADyCwcuxbdtfwOv1Zvy+HaTuupGYy6dA0+QMjZTNHobS3+vVtE6XK7R4aIpByQUzFfX1\n9QgGg7G/g8FZ+Hz+vLfndrsQDofhdtPV788Ka0ExXKfl+qMtx4je4eEzWLz4FyaxJGzdOoann/6+\nI4KZLx0dPejo+JdSDyMOq8oyZpeuVfWixOhKTVMhy1LeLt1Kg1bxpm08TkBF0I8VPT0L0d/fj6mp\nKUiShPff34s1a/J3gfn9AUxPT4GGp9VU6B0HkiNERVB8qTISH/mab0Rvaa7bsWMvYuNGa89GTc3h\nIo+mMtDsKzeiAAAgAElEQVTLq5HEew/c7lrU1JAoXZerBqLoBs+LcW5aWQ6bonSDiETmTFG6xbBw\nqsftmCvV0jwaoMjC1E/4Sy89j1AohNtv/zC+8IU/xp/+6R9BVTXcdtsdaGlpyXv7pIn0FJqb9W04\n9SPLPYgmG8vLuUnB2Rvd7pqvxf5xiqIf4TBp9pyILKePXGXkRmKxcE3TEA7PAuAgiu649VHy33Hf\nLqjjRibo8jrSJt4ayvmBPheoEMyOjvl4+OFHAAAf+MAtsde3bbsa27Zdbcs+/P4AJicnbdlWNmQz\nsefmonT6x+HEjFD+/TY3bboDv/71w9i+fTDudUXRMDd3ZYlG5Tw0rUvxPA9RNJZSjP6PqVy6iR03\nhLjgokLuQRpuX5qiZGm6T4pBdTwWoPiCmY7CXJR036DWEb0COK5cKvToYyTnuaamBn7//XjppRYo\nCnltbAz4r/+6Alu33l+iMRYPGq8ZyRe1cunWJbh0uWiUrpTSpZt9vihNVh1NYyHQeJ84ARUWZjHw\n+0kTabsjWXOlUvtvpi5lV/7Htn79zZicvALPPvsT8PwU6uouwfbtt+TVzYThHGRdNFWqCyn/Z+7s\nYnbp6uuqZmuU1nrFdFl19Im3k1SNYAYCDZiaKoaFma7ma/GS84tFareyClonnHwIBBpx3XV/WLT9\nUTUnljHxqS7ErWu4dJWEVBcl6tY1SOz5SFOACw3jSBWxW6n3b9UIpt8fwOjoSBH3SBKu6W9UnX/w\nTar1V0Jyb8ZyolJ/8OWFM9ZLPtWLdIyuLqUsSM+KOZSKqhHMQMC8hkmsQGefFvUUEXuS8xPLuZWS\nTG5lulxG6dE0BbIsQ1G4qBViFLdnlJZiXoJM1YsikTkAWrT1WXJXF6vqRU55WDSNjoAfgFmYFUvx\nXLL6neJUFRsnu0Jk+ERJ3cr21byNF0PD1WaeBBUlAlWVC66Dmg8cV7kTTj6UUhx0ISTXhIPHU1dw\n9aLC7yGa0jjYGmZFQvIws+vakA9G0It5pqO7ik220FjzNV+Mjig6PHjeBZdLjFWUUVUZeiPc5Dqo\npXbHMUqB2aortHqRHQXpaaGaCq8DVSSYgUDAZGHaba0kruWRfZR7W6p8a77S5D7WSbaOCeanfo4T\nIAgaVFWGKLogCC7LCMvM7rjyD+aiA5qsl/RWndmlm1h8IbEYfXYF6a3vIfrK4tF0jZynagTT663H\nzExiibP8F89TB70AeoSo/TjRiisZ+2q+OjHW3K5ZKutY9wakW6tMHWGpxlkQ5G85Y5pCeVnkLLDE\nDhKrFwGJqS6p7yGr6kW0QZ+AO0vVCCbP87YEcmQSE+LycxY7g5XM1mA5FkdPRSbrON/rlModl1x5\nxipNIX4CpDnXj+Ecqbu6ZFe9CABUlRWkLwVVI5h2kF3RgXK9cSsjT7QUoh+fpiDGjSP1mpYxAcZb\noUL0u+V13p2AlkjlYlhRVvcQ2bfZEtXvH3JvyXLY9P343qLFWhYwrhFnes3x3ZaMKhPMxP562V3Z\n/KJDy+OuiZ+U9Im6/IQSsLpOpbOOU69pxU+AhhWa2NZKgySFTRZE9VoR1XrcQHL1IlVVEImEoh4K\nkYLqRcwlW7HwPAdVVbMOU6e/6ED+pHJZluOxOZHu4pR1k6p8W7wVSoJBFEWq2OhKRmFwnF6QPl31\nIvMDmUFyMXp2H2VLVQmmz0fqyfr9vrSfyzc61HkKD/pJXfMVNoul8wFKToh+qaxRsxUaDs9C0zS4\n3bUpInSdT3OhKTm+9NATCZrKPZxP9SLrh7Hc7iMW9FPB+HykJ6bf77d83w6hLE5KRe5rXOlL2SWn\nW9CHeY3E6lhoeKCxEy7qdkuO0E2cAFmai7PQ1E4rFzJVL0pMd7G+jzK5dKtrvb2qBDMQ8EdzMbui\nr5jLoCUKZaHrX3QIUHbNqY3P2j2x2r/NxAIR5RnFmw/poysTC4lXQpoLLZYdLeOwDrLJldT3kVX1\nonSR3vZkHpQTVSWYfn9DQk9Mq3qvlTMBV1aHlMSSg3YeS/n+6FO54qytiPRpLrobjpb7o8rm4izR\nXaD2bjVT9SL9XkpVvSgcDprK/wmgp3SfvVSZYBKXbPwEqU/A5SCU2Y2tkoSykoKTikWmNBfryS8+\nzYU8TOpBcqUV0TK8bYtAMWoap3bp6vePokSirxnr64LgqdjfZ2UeVQp8Pj8GB/vx7LO/MLkSeAAi\n9BJp9uB01w7r7equORIUon9GAMeJZSeW8cdiFkvOph9jeZ2PQtFdsoIgQhTdcLtrUVPjhcfjhctV\nA1F0g+fJfWJYoRoikSDC4VmEw0FIUjhaa1epKlccTYEtNIxFD1IjUbrkAcvj8cLtroUoeuJcvZVG\n1ViY+/e/j+effxZnzvShpqYGN998M1wuF8q93itAc1Rv7pSm5KCZ3HJ0y51UpdvC4VnogUfx9U/N\n33U6zYWetUNGMmbxNq+LxucTVxYVL5iqquLv/u6rePnlFwAAy5YtxwMP/AVcLleJR1Y49lW1cSIF\nJPdtpis8UIySgwyCfu9wHAe3uwZAYoRu+jQXXUgrp5sLTcLNxlJKKl4wNU3D0aOHsWHDZbj++pvw\n/vu7sWTJUmgacVs600S6GDmIyW2qCl+DLU2IeGnXXGm1JOkaV7pC9MlFxK0qzpRvmgtN3meaUlyq\nyS2vQ4VgqqqKBx/8Fnp7T8LlcuH++7+Kzs6u2Puvv/4qfvSjH4LjgO3bb8edd96V9bYFQcBjjz0F\nADh1qhdvvPGK7eNPjd0CpG9LTXiN5gko9TmgJaDH/LvXT2MVzgU5U0iaix6hmy7NhbYJmY6fGH1W\nXeLcQ9llsxUqBPPNN1+DJEl4+OFHcOjQQTz00LfxzW8+GHv/oYe+jUceeRS1tbX4xCfuxk033YL6\n+vqc9xMINESjZMsPwwrToV0oU5Nf4YHyO878KU4bNyfIJc2FRFqmTnOhIcCFQJ9I0UF1FV4HKBHM\n/fv34cortwIA1qxZi6NHj8S9LwgiZmamwfNc1IWa3378flIaj1Aek1KqUnYcR8Wly5nkji/lkM5T\nOsLhMAZe74d4VgQ0QO6WMf/qTtR6a0s9tKwpNM2FFKEXTHl+5RfMZhf0PETQNZZiQcWsGwzOwuv1\nxv7meR6qqkZLMQH33vtx/N7vfRI1NTW47rob4PXmbl0CgMvlgiRJCa86sW5nRy3PVNWHnIgULVYb\nIDvWKZ1+yKEnSlaWZZx9tA9rptca5+k4cPjMYXR/agHcbndpB1gAmXL8SECRFLNMFUW1qH2aWETc\nmfu4GoWBYQ0VeZh1dV4Eg8HY35qmxcRyZGQETz75OJ54YgeeeGIHxsfH8eqrL5dqqDmS+6SrTxDx\n+YckV5SSy5UjibmhulCWX25osRnY04+Vk6uSztOquVUY/G2/Y/st5dqhkeNH8kIBwOWqieb46bmi\nfExQZTmMSCRkyhWdq/BcUXpqt1bjgwQVFub69Zfg7bffxA033ISDBw9gyZKlsfciEeKOcbvd4Hke\njY1NmJmZKWBvXMK/9JBN5Cu5R4tbEKEwyiE3lNKJdQgQheSfKMdx4Iedzx8u/XXSJ2QjTSX2TpWm\nudDVRYatYZaEa665Hu+991t8/vOfBgA88MBf46WXnkcoFMLtt38YH/rQdnzuc5+G2+1GV1c3PvSh\n2wraX3LT5NJSeaXsdHeyDlunzAtP6ntTc1d3Xmpx01xoCvrRQIuniaYUl2JBhWByHIcvf/mBuNcW\nLOiJ/fc993wc99zzcVv2VVtbi1AohNraGlu2Z0311XwFrI4HIBZl+VdTKgV1a+px8cg4GsWmuNen\npSm4Vnsc2aemaeh7+xSUgxJcQRe0Fh6uy9zoXNvpyP7Sj4X8m+3Pwe40F90bQosw0OdipulBojhQ\nIZjFJBAIYGpqymHB1Eld85WG/EO7sBZ+DsUpZVc4+qRK24PKvAXz0HfFKcy9O4cOcT4A4Jw0ggsb\nLmDJ8mWO7PPUS71YcmgxBC1ae3ZCxMRLExiQB9C1oSvzBijDjjQXNaqsuvek1PdJqfevQ5+AO0/V\nCabeRLqtrS36SvEuuj01X0k6jL0TfH7bSSf89JeyM4pAaJqCcFiKrXcBiFojpZ8cF161GFNrp3Ds\n4FFABRrXNGFJszNiGQqG4DtUD4/ggSxHYq83CA04v3sU2ODIbtPgjAVjleYCIMmda6S5ECKREAAk\nROcWM82FTouu1L+RYlJ1ghkIBDA5OVHUfdpX89Vpsnt4KMXxmF1j9qDF/auLvCH0pAC58wXGM+Nv\n8MN/ld+WbWmahnNnzkGRFLQtaoMoGlPA2JlR9GCB5ffqJ+qiSxnlk/+ZK6SbS3KaSyQSgqapsUL0\nVv0gi5HmQotrWIfMA5QMpkhUnWD6/QHHq/2YJ3dnar6WjnIvPGDlPuY4ES6XCwMHz0LpVxDh59Cw\nvgENLY0pIy9LLaL5MHp6FOE3Q5g/1wmREzH0xhCUjSo6N5D1ybpGL2bUGTQKjUnfnXOF0eBuLvaQ\nS475urrd5GHB7M7VLdLidHOhzcLUynYZKV+qVjDtt1isMFthlRbQk+l4nDrO/C5aqopJAAdZltH3\n2CmsuLASHtEDWQpj5MAIzt84hq7Lui0jL8tNREPBENSXFSwWlsR+9QuwAJPvTmK0cRStPa1obm9G\n77wTaLwYL5iapmFu6RwEgQVvAemCi6onzaUa1y+BKhTMQCCAiYlx0yv2Xnjna74Wt6RfstCQtZ/s\nnyztHevszCz6DwyhrqkOC1b0ZDyvxAU5gtlzU/DN96G1qxVk3dhIfRl8ox/rJtaDE41tdYgdGHxj\nGKGVIdR569JMjuUhoqP7zmOpsDTp9YAYwNjhMSAalN56WxsOPXUI3Rc64RXrMS6PY7BzCIs+uLjI\nIy6vxPhipLnQeD5oGksxqDrB9PsDOHv2tO3bTW3BOGVVOrt+QFtTak3TsO+/9qHx9UZcNrcBE5jE\n/q69aP/MfLQtbLf8zuz0NIZ+NoCF5xdiibgQF+RxHJ9/Egs/thhuj9EPVTxjXXWom1+AY/uPYdGW\neLHIbGHQJ6JcMPUDDm96z9/oh+9T9Thz5BSkSRmNPS1YPn+F4+Ojm/x+a3anudBl1Vm7h6kaogNU\npWAaa5iFW2uphaV82o4b7mmN2gClIy8exqUvXooAHwAEDm2YB+lEBLu+9B5mPjANpUVB47YmtHbP\ni1n5Q88MYO3YWpwZOYOLUxNQBQ2tk604+0wflt5tRJpyivVxcRwHLsvLaKeIppoYNU3D1MVJcDwH\nf0Mgu4HpNAHKaQUCn+xWVQLJB9m+uB08L8YaSBeTYDCIqYtTqPN54HaXvtG7ndV1CktzISiKAo6T\nYw9bpXmAJf9WmYFZfYLZ0JDc4iuf9IFMwkKCY8rxccu8Tll6oYyxUyViGaV3vBeBET/uxJ0Y3TuG\npq5m9B3pw8DHzqJzdQemp6bRcLoBJ46cxNrwWgjR4gkz4zM4feE05n5nDjU1ZDKW5kvAWfOsSP49\nL51Dw8rkABgAGB++gFBfCOAB3zIf/E3JAlaIiAKAJM3FRPTCmXEoe2U0BhuhcRqGfEOou7wWDR3W\n40ukY10HTh08hWVSfErKsDaEhksbLL8zeuY8tH4evMJBawfaV7cnrWNGIhFwHAeXq3Bhi0QiOPn4\ncTQea0Cj1IgR9zAm105i3V2XxmpLlwZnq+tkn+aiRF9XIEnGvFOaNBfaApCKQ9UJJmnxVViUbLlH\niiaSXCqQvgAlYdK4VRVNQWQ0DCjA8fBxjPaPYVXLavTUdGPvy3uhrdIQnApjpn8am8Ib446jnq/H\niuFlGDw9iCWrFgIAmre24tjgcaxQDddjUAni/PpRLGtZnjSWM6+dRntfO9pFkst78fBFHF90HA2L\nG+Br8aG2LnXqRTYiqre2UhQZgIypC1NwvenCPLENnEAKCtSHvDj3+jnM3TGHmiyKcIiiiJY7WnHi\nzROoGayBoHEItYbhvdILf3Oy2A+8M4Cuk93w15D3lGEFvSdOo+v2LoiiiMnzE5jcOYm6czUABwTb\n5hDYGkCg1Vp8s+HEY8dwWe+l4AUeEACfUo/I3giO1R3DyttW5b3dciUxzUWWI5DlCATBBY7jTAFG\nxU9zSbWeylyyFYbfH8DkZH6CSUcpO7tvenrWKdMRaQsD0cs2ODuI6YlpzJfmYyW3EgtDcxh+fxjn\nu0fQEmnFzMwcmttbMBY8b3kcNd5acP0cEJ2D6xvq4f6kB0fePQLhnIAINwduObDs8pVJ3x0+NoQF\nfQvgEUlpOlmRMXVyCi2/bYRnfQ3CvjmMdo6i89rOrKNKE0VUtzrd7lqoqorwyQjaxHZoUMmEpJGZ\nsRmN6Hv/DDo3dWa1Jur1e+Hd7oWikPWzlhRW4cXzE5h3fB68HqPlnsALWDa7BKf29KF5dTPmnpvD\nUm4poFfouwicfe4s3B/zpH1gSMXUxCTaTswjYmnCLbjhed8N5UNKSaJ06Vo3JPC8kGCJJrtznU9z\nST4vFJ4q26k6wSS1ZPVWYvoaZvpF/fyE0ulo1vy3be1OJtiVV2VX2o6qqhg+O4zQujAOv3MYPRM9\nODVxCpfObkCzqxnTNdPwer1YhEXo7x/AkG8YnWIXXC4XIt0RSMckuHhDGMJqGFq3BkGMv3Zenxe+\nDywhnwnPphy7elqNiSUADB4fxOKpReDcHM6PjmJecytaz7fg1Nun0X2NdRGAbCFNkwW4wzVwudym\ntS5jzUsI8jFLVCfTxCgIQlrxCfbOoNuVXDuW4ziIQwLGpFEilgl0a93o3deLBVt6kt7LxPjgOBZp\nCd+L/ix9sz4Eg0H4fL6ct2sXNDxAprLq7Epzya4Qvb59Y9/VRNUJZi4X2B4LjK5qGKncyfoDgf3l\n4PJXzb5dpxDeEcai0UVwDwg4OHoAQ/wQREnENKbhUl1wBVzQz283143d2m4sqyOu1cabm3AhNA7+\nPAc+zEOpUcF1cJDbFdSvzG/y5VTj3ISlMOonvOAELu49juPg7a+DJEm2rO0p9QowaV7rImiaBq7B\nFbNEixGdq0GDMGktthzHpXzPzOjZUQQPzEKYESD7ZQQuC6CpqxnnuHPoQbLYTtdPo7Gu+oomFEK6\nNBdzUFH+aS5sDbOKyJy7Vy6uymzJZCXT5k4Z6RuB71Ef1mvrIXMS6ie9WOlegUPcIUwsnEBgNgD5\nogxxVgS85PhGxVE0bjA6e3RtXYC+06ew9uJaiNFmxFPyFIbWD2Px/CVIDLLJBmWeCu0CeaiYnZtF\nvVYPAJBVGVyTcW/USaSUnB2C6Vvtx2j/GFr5lrjXBzGE1jWtMUtUp9AUl7ol9Zg8OIlGT3yXFE3T\noHQoQCj1b0CpTR9WPHhgEIE3/OgSSDF5XARG+oYxd/McRpePoftkN3iTlyOsRBDeEClh0QR6hMFw\nD+c3Fl0IAcEiQje7NBddQFU1MX2uOqhSwdRJXLCmM6UinnyieQspPFAaxt+4gM3alQCA4MUgmkEm\n79Xqavwi8gv4awKQ22QMTA+grqUOqAPEdhf8lxoBLC6XC4s/uRTH9xwH+jloLg2eVR4sWbo0w9qU\n3mklmfZL2tF7+hSWhpfAV+fDRWEctVodRr1jaGlrjX1uumYGTV57rCJfgw8Xt42jb89Z+Cd9UKFi\npmUG9ZfXw1OT3Oar0BSX+sZanF1+Bu6THviEADgAiqqgt/40ujZ2YXZiBqMnz6NVnBe33/PyOTSs\nSx30oygKtHdUNAvxQtzOdeD4b05g+b0rseeJ99FwNICGuQAGhH4M1A+gp3YRxkcuoKm9+FYmXQ+S\nukvWvi2mSnMBtDgr1ChEr8SC0gASiKSqSizAiJZenU5RlYLpcomQJAmiqE8omgORr/r3nPrFpd9u\nuVvJrkkheogaBDcPWZMhcqTAQHNdCw6ph7BWXov6pnoEVjZA0RTsat+NVetWx21HEAT0XL4IuNym\ncblcaL+9A6f2noYwIuBcz3loEQ6ti1piE5mkSggvtdcqauxqQmMXMDs7CxcvYn5tbv0pcxFRTQO6\nNndhbP4ohk8NgVcFoB3oWDMfPM/B3xzA+WvOoe+d0+iIzIemaRipGYZ4lQvzmppSjmFsaAwdoXbA\nnfyef8wHSZKw5r61CIVCOPb2Ufh/48UH+Zvh2uvG+XfP49jqI1hxe2miZen6yTg7GDI/cBCE1Gku\nsixBnzcVhUR2c5wAQajc4vxAlQqm3uKrqUnPYTOLCn0pFblS7gXfNU1DuDEC/brUBeow6ZpCs9wE\nTdPgqfdgfncn9g3sx0jdCFoaWyAtlbHixpVFyddze9zo2twNAGjXOjC4axCR3iHUhmsR8oQgLZPR\nudGZhsterzfzh7IklYgqigxZDqO1Zx7Qo99PgKbJiESINdrQ4wd6gKGBIfACj7bujowPCIIoQE7h\nBlc4JXbtpLCE+bs6MN/dDl0c5rnmwX/Uj76O01h4+aJCDz0HaHTJlgZzmoueF+p218XWQTWt9OfI\naapSMP1+P86fH4HLxcPnq4++Wh6uynQUlvbiRFRv7tvULf32G+bh2N5jWCGvBAce7kVujPdexBn0\nYfGCJdBEFVPbprD+0xss3ZI57BEAou4mATyf24+e4zh0Xd4FdaOKcDiMeo+vxEn2hcFxXGz8PC/A\n5fKktEQBoLmTuGAlKQRZTh9Y1NLRgjMNffAHk1uVzcyfRUsNcfGO7T6PVeKqqNVifKZGqIF2TLPN\nW1Cu0PTgS+4XIiOqClT60mbVCebs7AwURcaXvvQFLFu2DA899FD0HbutyuLd1NbrlPkej/1RvdlE\n3iaKfXNHCwY+NYx3d7yLtv42qB4Vw7cMY2bRNMJ+GTU9tVi9cq0N10w/dxxkmYxBFwNVJWPJRkR5\nnq/YXpF2lv2ru9aLvl/2oQekcL6iKjjlPo2m6w1XLh9JU/c2zXtOQFfBc3oi7uk6L8WjagRT0zQ8\n/fTP8YMfPIyJiQk0Nzfj3nvvi77r5LqevVZbfK/N8l6nBFIfA8fx6F7bDW2NhomJCYi8C2v8a0DO\np3Wx9PzHoECW46M7eZ6HqkrQNB6aZj6fXPT98ji/TpGviPraajF3L4/DBw5BDLqgNQCdl3XB7TYW\nNoUeEcF9QXi45AhjuU1Keq1asLOmbeHQI97FpGoE89SpXjz44LdQV+fFhg2X4brrrsNVV12LfFIL\n6EBD/NjLb50yOSI5Wew5jkNjY2P0O2Z3c/4QsSNWj6YpUJTk7ZKowEj0v7lYgjd5YOFBJgtDRKtd\nQIHsRbSm1oOuK4w1XlWNIByWY5bo/BXzcbTtKNadWx2rAQwAx8XjmHeVdWea6sDZmra5QJd4F4+C\nBHPPnl34t3/7LlRVw5IlS/GVr/x1QYNRVRUPPvgt9PaehMvlwv33fxWdnV2x948cOYSHHvoONE1D\na2sr/vIv/y7rPLfFi5fgH/7hO1i5cjVeeOFXmJubM1lrVMWOp0V3FxqUl1ACVmutzh8DcQvz4HnE\nOoKoqhwraE0CGkTo665kgtcTvbWoWBviniiiisJDEHQRZVboxZFxSLMyfO0+1Hprc7ZEe+7uwsE3\nDsJ12gVRc0HuVDHvmjb4ApkLTkiSBE3T4qzW/KEj6KfUAT/J0CPexaRgC7O/vx9PPvks6uoKj957\n883XIEkSHn74ERw6dBAPPfRtfPObDwIgN8zf//038PWv/z06O7vwzDNPYXh4EAsWLMxq2xzHYcuW\nqwAAgUADTp06UfB4i0myyAD2uiadnxDsW2vN3h2kC6UgGJarqsrRcnJkDIIgxk3oeki9eRvmKinm\nZO94EdXbLVWviAangph+dwqtcy3wiB5MHJrESMcw2ja1x85/NpYox/FYfENy0+pwOJgysOjiuXEM\nPT0Ib68XnMIhuDCIxlub0b4kf6uUtjZWNDwYV+v6JWCDYC5Y0GOLWALA/v37cOWVWwEAa9asxdGj\nR2Lv9fefgd/fgJ/+9FGcOtWLrVuvylosE7GjY0km7LJerUWm3G5Yc56rjp7o7CxE+IjLlLhZpdgP\nnufFrGpnmpO7daxFNFocPaWI8lBV3X1Lr4gWYs1M/3YKXUpnbGZpcAfgG63HyKHzmLd2XsrvJReg\nVxGJBKNVjMSMgUWRSARD/zqIjaGN4MCR/Q8Axx45hotfGkfjvNT5oemhw8IsB6gzgh2g4BnL4ykk\npD+eYHA2Ls+MBF6QSXZiYgIHD+7DXXfdg+9851+xa9d72LNnV177CQQaMDk5Gf1LLw1H19U2LBgZ\nhtAI0Nf59M84sGcbt6VPMgqMY+BBLGNnxVJPjyBWCCDLEhQlErM4RdEDQcjfQte3LwgiRNENl8sT\n3aYLPK8fHxeb6BVFgiyHIctzkKQwZDkCRYlErV0lmtdGxICWezHXc3NxZBzzIq1Jrwu8AH4w//Ms\nii64XB54PHXweLxwu2tj55rjeGiailOv92L91FqoigxFkaAoMlRFwfLIMgy9MkjNOc0feoSbWZiU\nUFfnRTAYjP2taVosJywQaEBXV3fMqty8eQuOHj2Myy7blPN+AoEApqYmM3+wRGQqPFAOv33DMtZx\nviCEnr7C84b7VVFkqKrZ/epyLE/SqNUZP6Z4C9T4X8K3YTQeR9QaNXsV6LNEE5FmZbgF63VDPpKP\n2x1IFIhU7lz3hVq4xGhHF2hA9F9ZViD3RxAOzyaluNjdI9JJ6HIN0yPexaYgwbS7s/f69Zfg7bff\nxA033ISDBw9gyRKjhdD8+Z0IBkMYHBxAZ2cX9u3bi9tuuzOv/fj9fkxNTds17DTklrhPR7/NwrBO\nE+HjhOTi6EUMPTMIz2k3NA6YWzaHxR9eDG+siER+CAKxJonYKNF1ytzcr3aTrYjqnWKMz6iQpDnT\npC5Qn97ibfVi8tAUAu7kwgSKz7mMdo7joPlJ2Kb+MDQ7MYu5UyG4plyYaJjEEf4o5n24Fc3zm5FL\nFxd6rCn6RaocHuQLpSDBvPTSjbj00o12jQXXXHM93nvvt/j85z8NAHjggb/GSy89j1AohNtv/zAe\neHC2BrsAACAASURBVOCr+Ju/+QsAGtatuwRbtmzLaz8+nx8zM7pgOlHhJp5Mifv2Fh4oDdZpIvq5\nNY5jZmoG578zgi2zm43v7tbwdt/bWHn/6rwiG/UHN57noGkaZDlistSEglyvTqCLKInU1UzWg7Gu\nmWyJSlAULm49FKArR9Tr92K4bQi+C/VxVvy0PANxqbPOrPlXz8fJ35zEMixDODgH9aCCdqUNw9wI\n1ratRXdfN3Z9bzcCf9GEmtqarIstJHsCSgNNLmWrhwiKhucoXLoLMTo6XbGn4Y47bsGTT/4iuk6o\nwokgFE3TLRzrCTvfwgPGmO0TAjIWGYnWYHbfTdVjU3/dOLeHfn4Am9/YnDRuSZWw5/a9WHVTfPH0\n+P0Y10o/R2b3K1kHJBMfec8592sh6Jal0fUhOVJXfwBJtEaTSRZR8znJR0QVRYYkzUEU3RDF3B5g\nVFXF6KFRCAM8BJmH7FMgLhXR2JVb0I2qKohEQhAEsn6ZDWffP4PQ00G07G5G5/n5OM4fB9fJYUXH\nSnJcqoJdH9yLdXesi30nXdk/M+R+Ekrmzi3kmtg/FgmSFIYoeiCKeq9NQEnf2a2saG31WV5cqtYw\nqwX72og5UW3DPhey1bOYa9Ba5F28C9yZTHvUv6dFA3o4S/crsSjptNCJUMqxSTmVq1i3NsnLQvS7\niSJqTnExJnliiRrRucW0RHmeR9u6NmBddiURU5GPK3TBhh4o6xS8+pVfI+QLYknjUrh4I09b4AUI\n57NbE9VFVA8U04vSO9GUOzvoccka16bEAykBVSyYxbjaye5e+9uIFZ905exSEZydxcCeQfSP9GOd\nsh4eIdlqUGuzFWu9P1/8qzS6X3VSFUrIxauRm4gqcQ8sRqEFLhpZ6ryIluI6CIKA9uXtWB5ckfSe\npmlQ/JldrGYR1Zspu92kTnC+TbkLha6gHx2qBlMUqlYwOY7k5Rk3s5PeZ32dqhICejKXszMgr514\n+QQCb/pxGTZg0XgPThw+jtquWiyZZwR19av9aNpm3SDYqNKj5zJau81ImTs15p40BKZ05zgb92sh\npBdRq2pFBlYl/1RVi41V04BT+3tx6gcn4TnmgVqjInKVjGu/eJ1NVXScoeHqJgy8P4guxLdYOyGc\nQOf1ubZd060pPuaWjb2TZwH6/ESURguz9GMpNlUrmPX19ZidnUV9vX39BVNjtihJAnxh66XFv1Hz\nLWc3cHgAC19bgGaxBQDQ1NYEbUbF+TPnMVo/ipbaFhzhj2D29iBW9KxM2qe5Sk8kImHfr96HNBKG\nd7kXq69aDUFwxX7AqcrYmS0r/bwX48ee7H4Vojmazu7bENH4Qgu6iJJAI+tzZdoKzhzuw9QfTuKj\nIx+JvRo+EMZjJx7HHQ9/mNoJs2t5F07cdQxjz41hxfRyKJqCo43HUHeXF4HmBszNzcHj8RQ8/nTu\nXF1Ii22JFodk46Jagn6qVjD9/gAmJycdE0zDGoPpX7s7iTh/lxYawTu3ew5NYnzAR/OSFtR3+vBC\n3fNo29KBnq096KpfkPRdc5Wes4fPYOBrZ3Hd0HWo5WsxhjG8sfotXPnNK1HvN+qLZluBx2xZ2T1Z\n2eF+tRuziOpxUPq5IpN6omhqOPmD47hn+J7oBsg/Hs6D6167Fgfe3Ie1V63Xtx7nyj03eA6HdxwC\nOGDdnevR0taSx4gLs6iWXbsC0lYJxw6cBC9wWLxiKY7+9AjmHg2hLlSL6XnTcN3owfJrkl23hWCk\nEQnQ+2nbIaI0WXXxUd3VRRULpl4eL1cXTWaSCw/Q7341tw0D8luntEIIWbsePTUe9KxYiMUfXGrx\nLhdXJF2WIzj7f/qwfWQ7MWw5Dq1oxUcO34nn/umXuOqr18Qdh3UZu0zFA7g48cxXRJMDkFxUWw9m\nsdSjQAFyD9edND1Mmu6NHnkBdr39HuTNK2IPHorCQRA4vP7Pr2H+jztwx8xt0DgNv/nhOzjy6UO4\n+rPXFvOwAAAulwvLL1sOANj1z+9i2+FtEHiB3BpjwOhj53GCO45lVy9PuQ07hMoOEdWLWNCRXkKP\ne7jYVK1gBgIBU3k8wA5rzTpqlESy0jphJqNZCH7+gUmRtgi0QS0pWEFWZSjzDcGyqtKjF0k/tucY\nNp3aBPBc3E+U4zj4dvkgSVLarjXpiwckrvOlElHeJMbJkChKqeju13ywXldNTMHhoXjV5DlRAxRN\ngVqnRi1o4z7Z/+phXPKDdVgoLwQ4Dhw4bJvaimP/egxHNhzBik0rsw4qsjPI5dzAOSw8vJCIpYlW\nbh5Ov9YHXF34PnIldxElSNIcZNlYzycPOcV9IKNDtEtD1Qqm7pK1g1Ruy+QAmXJBH3PhlnHndZ04\nfOgw1kbic9/2NuzFki3LYq+lK5IeHJ9DI5osn2fr5uoQDoezbvOmY56w9DFZ5T1aiSiZrPRoU0Qn\nOCP/U7cqaSTbtBYAUK5WENwTRB1XZ7zIAa+0voqNH78itn6sT/ITz1/EQvk6fU+x/18eWY5fPPML\nLLtsKTSNj4qgUaTBzsjcseExnH6+F3yIR+16L1ZtW4XzR87hSv4Ky8+7zrliD2vWOJG6ZU06EZWk\nMPQuLokiSr5bfBGl8WHQaapaMAvtWJKp8IBzT2L23qhO1n2tD9Qj8mkZe17eA1efCxqvIbw4gu7b\nFsDlcsWsNqNKjxRzEZK1PxdWbVuFvb692Dx7ZdL2xxeNY6k3tUstW3JJ2dDXJpO3IUStNPomEut1\nVVfaa3zN567Fz3ufxJUvXoHl0nLImoxX5r0K/s9ENDQ2JH3eHUodOctNc5DlMKxc31Yimo/bb/+z\n++D/Dy+uk64Fx3G4+KuLeGPdq5j/sS5MKBfRIDQmfUfxK2nPQamNKV1E9SUTPb0lkyVKvuuUiBbv\nIYI2qlYwA4EAzp0bMq3d5Zqwn03hAadTVgrbrvVxAPatt5JtNLU3ofmTRheLXIuk+/x+jN96EeM/\nu4gmGJPeMc9x+O72Ofakm0pEdYsy8YGIpLUYglSKyFwr8l1XFQQB2//xd3Di/WN46vWngXoOl33s\nMvh8ybViASCyTILymgohwf0d0cJQVhjWUTrXN7ln1Jiwaxqgqno94NTjnRi/iLr/9GCtvC72s2sU\nGnHzoZvx2u7XMdMxjW3n40tphpUwlI3Z5GVm/EhRydedS75buIjq0evVSNUKpt8fwPHjRzJ/MIFK\nKDwApDoOvf6qs9WD8imSvuVzW7GnbTfkV2S4J1wIzw+j6c5mrN661uaxpka3LhPdrwBX8sjcVOO1\nY1112YYVWLYhczTpZb+7CTte2YE7TxlNETRNwy9WPoOtn7wKYrSbCHk90/oxAHDRBxMVmaoVnXj+\nOK6NXJNk+IicCM9+N3oeWIid39+JZQNL0cQ14xTfi/NXjuGSD2/IcFQabOiCWDCZgo+KJaLVvH4J\nVLVg+jE9nX3HkkroJAKkPw6zC9KJ40p2v2ZfJJ3jOGz8yCbgI5ZvOw4pkybBsNLiy++VMjI3ET2/\nkjyIkP042dZMxx/wY9W/rsHP/+1J1O2vATgguGEOG79wOerqyDqocb6M9WMymcsWgqmZvA4ZSv6F\nAR68pbeQi3Boam9G4180YbB3AH0j/eha3YnOpuRUpkrCSRFNvE+rRUerVjAbGhKbSFsLhXVAT6GF\nB4qPXWkiee4dgBrbF2mYTH+RdEC30mTTump25feKEZlrPV41alWmt9idYl7nPNzw9Ruz/rzeXJtg\nVEHKteRfw8YAzjx9Bgu0BdEtGcc7tyRCXuM4dC3tRpdVJpMFdOU+2rNuWKiIGnmhsJwvK52qFUyf\nL33QT+5l4JLJZ33U7u3acRz5YLhu9IcRY31Px3h6pe9Hl+h+zdVKGzo9iMP/cQg1gzWQmiXMv6sT\nKy5fCTsic62uXT5BPaUkk7s4fRBWcsm/7uVd2Ll5J5reaoRX8EKLSubbTTux4K6FUBRzcI/hztU0\nDUN9QwhOBNG9qhs1NTU4++4ZcEcBfoZHqG4WrvVu9Fy2uJinxwLn1g1zEVH9Z61pSkJTbjdocF07\nTdUKpt/vx+SktWDamYdYSvItZ2cHepqI3lPQvE5pjM94ik20qkqZu1qolXb83WMI/sks7h6+K/ad\nA88fwLsPvIMr7jX6gBYSmWs+X7pY6hBht6dWrd0k5oDmkoZjrlZk3p4uolv+5za8s/i34HdxEOYE\nhBeFsfCjC9HU5oMsz8XdX5rG49yZUYz85xAW9y/GfLThhLcXAx39uCFwAzyCBxoPyDNhzLw1iwFu\nAF2Xdjl0VugjlYgqigxZDseugf4bFgQPdcFRTlC1gunxeCBJkehfeoEBvbZmJaxT5lPOTj8P+e9X\nL72mV+lJtHomx6bQ+1QvPANuKF4ZtdfUYumVy2KWQroasMUIkrHDSht4qB93jXw0zoO2bnYdzvz7\nWYQ/HIbHk7q/YybLKlMdWGMio8edqJNsVRbuLjaLqNst4oq7NkP7aCqr3Thfsixj+F/6sXVqG4jn\nnMPa4BrMe6EFvZt6sWrpqtg59Il+XHj/IrQNpXFB0nItzcsDgiDGgrjIPUnPfeYkVSuY8egiYV/C\nvkFhIpQLmfJCc9gSclkv0dcySPQr+V782hSxes71ncPFr4/jxqkbYp87t2cE+z5yABvv25hijQ9w\nOtLUuvJNfh1Fpqen0HrAunbqVX3b8M5r7+KKm5PzSdNhFgWet3IXGySuPRU7MteK5OhiZ2vrGhN7\nYhCWcX/1/qYXl45fCk1QY7/OcHAOHVo7BnsHoCwyPAwcAN9UPaanp1Ff73Okj2i5ogfxVVLz6HRU\ntWAKgoiXXnoe69atRVtbm/4qnHAH2r9AHh+oVEo3srlKT7I701ibGnpsENdPXx+nxW1cO4afG8H0\nrdPwN/hRWKRp6YNkOI6HKljn9smQIbgKc5WmG29256u4Ipo43lLV1k0UUe6igDrRC0AjgqlpEFwi\nJEgQQ6JpDZ4cwyw/g0axKeqB0AvYG4UWnBVRemq30mLtlorKX6W1QNM0vPrqywiH5/D1r38NO3bs\niL5Tbm12ACKaMuKt4/iUB6cgT5f6oj+gKFI0VYS4ZkXRHefSdB+zLl+3PrweJ14/kWL7Qsz9I4oe\niKIntkZHLBSjkICiRCDLYchyGIoimQIVrNoRaRbj9RTcgLq+vh5jG8Ys33tr6Vu45JpMeX/WZDPe\nxPPlctVYnC+YzpcEWQ5DksKQ5Ui0eIT1+cqGmZkZDA4OIBKJpBwvLUFe7m43ppQpgOMQmYtg4vQk\n5npDuDB5AWP8GMxiqKoqZrqnwfOI3l8h0zmLQFVlyLIStaKJ21wvtmAH+uWg4LSBJvEuBVVnYY6O\nnsdf/dUDOHBgHziOw1133Y377vt4qYeVB1ZuZOfTXayq9OhF0vVxWLkzT+4+gf5T/fht6B2gjsOG\n1g3w8GQtT9EU8O5sgz7ic/jSpR9YrYcak2D68RbC0j9ZjmdO7cD2M7dC4EiKxM6mnfB9sQGimPtP\nzqpST7bjNQdvAIaFkE16S6bIXJ1gMIi3/+5NtL3dhtbJFuzt3I3Q9hC2fnZLLKiHtiCkpZcvw95f\n7cbGYxuhHdfQqhA3er/aD+2ihgO9B7Fh+QZMyBcxOG8YXR9YAJ4Xs/R0pC75l58lSo9IscIFVcbu\n3e/hwIF9uOaa6zE42I977rkPXm89nCuSbu8appEmYsb5NJHYnuKq9MQXSU/lznzvP9/F6h0rsSS8\nGM1TTYhMRvDaxdeweekW1Il12FW/GyuvW2m1u4ykCpJJvR6a+H0jSMau89ezeiEanmzEUz98Gq5+\nF6RGCSs+sRKrFuUWZWlXpR4zuTx0pIvMNUcyv/Hnr+Fjr34sWhJPw+qB1Rj7/8aw070TV33mWios\nykQ4jsPSLy7Drz71S6xR1uCCWocLtePwdnjxwdab8fr06zhy2VH4u/xY0r4k6fv55tQ6XXy+WJiv\naTVpKJWCqaoqHnzwW+jtPQmXy4X77/8qOjuTJ5v//b+/gUAggM997o+y3vbNN9+KK67YjKamZnz5\ny1/E5OQUWltbM3+xYApPPE4uZwfYW3wg9fj0NaB0RdKtJsaRM8Poea4bHdx8yJ0yxkIX0BRuxE1z\nN+HN4bfQuLAR3Cc41NbW2nQMyetVicUHzMTnhxa2Hmom0BDADX98U17fTQ6ScbYDSiGRuQO9A1i3\ncy2EqHtcpwWtwK844DP5j+vEruMYe3YUwoSIcFcYy+9dgbautsxfzAJVVaFyClY1rcLCxoWIaBJ6\nXAtj1/vSyKU45T6N5vZmy+8XYrlbi2hyjqgOXeuG9Fi7pYBKwXzzzdcgSRIefvgRHDp0EA899G18\n85sPxn3m6ad/jtOne3HppRtz2jbHcWhqIj8Cn8+PqalJGBefzkcl63J2gHPj1X/8hvtVTxNJVyTd\niqE3hnCddi0AQBRF+Ff4MTE2CS4EnG8exbwH27G607kSZVbRusZEldlKKHZ+aKkr9egkRuaSsSVb\noX17+3Bn+E6L+VND40gDgsEgvF5v4psZ2f3ELiz4125cLm0iW9ulYeebOxH6WggL1y/M+7jMqUP6\nM1UtX4e6hANQoIITsn9Ayc5yTyei1iX/yG+OnhBUQ7xLPJASQaVg7t+/D1deuRUAsGbNWhw9Gl8k\n/cCBfThy5BDuuOMjOHOmL+/9BAKBqGDSSao0EbI+YhZQZ9DTRDiOy1gkXdM0nN5/GjOHpwAvh6U3\nLSP1QxOGyHM8/K2k20VrdyvaOu2xGBLRiyWkc2daWwnZr4fa2YmkHCr1mC13/bx0ru7ESddJLJeT\nW6xNNE1AFDlIUnzRgEyBdXNzcxB+zGOZZPRL5TgO28a34ZePPIeF31mY1/jj6wFz8PkCOLOsH1xv\n8liOtR7FqlVr8tqPeczZFqZILPlH6uYa9Z2jW4SqmnOrS+nOpee+LCZURskGg7NxT6U8z8dulLGx\nMfzwh9/Hn/zJnxW8AO3zpa72Yx+531jGE6gMQyx5kOjXYlwyw/VL3K+R2ETDcUJSdGYkEsE73/oN\nOh/swLYXtmHzz6/EwB+fRe+7vWi/uh29XK/lMUqrpaTXC8WoRkIKu1tF66ZCn8xJpKnLFJXrjoot\nCX4hbkolFmVK/qdHmSo535eq+v+3d97xTdT/H39ldJCWDlYLpTIrlNKWlpZR9gYpQyyCX0VFXOBX\nFKqyREBRhoAI/BQFWbJBtsoXBAQpq2WUttCyoYyWDqAjnbn7/XFNcknuLped2s/z+/g+hFyS++RI\n7v15r9dbhcrKsipjKak6t6tTGUs2ai9YpapEszbNcKH9haqbvUTz/yK6CBX9KiCTyTWvEVuZm3o8\nBR1zuHtVva/4oLS01MT10lXrLQdAQyqVQS53hVQqQ4OX/ZCkSGSFVGlckV1BrZEeNtE35vuOMd9R\ndvGZ+h6gvS7qKnCmMrcCKpWqSpeZskl1LhfOFR62P07pYSoUHlAqlZq/0zSt+fL+/fdfePbsKT75\n5CPk5+ehtLQUTZo0xaBBsSafx9vbB4WFBVU7OastnwdxJ3CUnB1zXvWILz7tVxnnTSRtWyp6X+0F\nuZT5OskkMrQva49z684hYEkAkgdcgvefXqgnYXLFlVQljjY+hrajQq36Gcyd+ygEXxN8dvYj0DSN\n+vXri6ia5M6H2qKox5ZwCxC4oNPCLtg+czuCzgWhcXFjXK13BTkDc9FrYh9NKJ95vZj8nhQSGVBJ\nVwBwh/6Gk5JRJl0ffa9SP4Xg38wfnl954NT/TkP+WI5K7woE9A1EXT/u3KUtYIe/2WFv5pg2D6+N\ndmhRi8+z86FCY9Asxzoi8NUVpzSYYWHhSEj4B71790VqagpatNCOF4iLG424uNEAgD//PIC7d++Y\nZSwBxmA+fJjJesRxOUzD8KsxtSHrfGnVPXIymfoG76aXp2Q/V79AhvmRul520RhLNhFFEUg8kYSO\n4zohIyQdaQlXICmVQhVEod3QCLi7u1vtM/AZHpqmkX7+CgqyC9C6Sxt4eXMPPxaipKQE5zacgeyy\nDE/zn+Bxdg565HSHVCLFybCTaPjfRni+YyvR+VA12vCruKKeG+dv4N7Pd1ArzR0qdwrKaCU6T4tB\nbS/TP5Op0DSFykr2eDPtZsS7jjf6/99AZD3MwtW76Wga0gJhXhGa15raDtSmSzBONzqNfln9AI2M\nOgAJ8LTtM0FpQe16dUPcQpsRz9q1ERYXbva1sRbsfDvXd0I3h8xfiEVRuqFvaxpRmq65+UvASQ1m\n9+69kJh4FuPHvwUAmDZtFg4fPoiSkhIMHfqiznMt2Y17eXmhoMDWIVlh+PKU4otLLDPy+io9TPUr\nt+ExNAhVeZcSGhStYm5sVSXzEkjgInUBVcy8V6tOrYFOfKswD2PVpJnp93Bj7nV0SO+AenRdJPme\nR+7gXHT/uKfo741SqcTxt49i5MWRkNFyUE9VKKaKccjtEEZ6jkT7C+1xbMoxXF16FY92PkCtS8wm\nQNmuBO0+jECdBnU48qFsGO+CnaviWtvdK3dQMrEYcdkvaR6jblPYeGsjBm2OhUxmmz5Hw9wq/3gz\n/0b+8G/kL+p9hfJ7Mpkc7m+7I2lxEtor2wMSoJKuxGH/w2jyTiAqK8sFc8i6kQb7zAK1BMMNH3eh\nF1+0g7+Fis+IMgbUPCOqjkTVTCRC+ZacnELnLBu1EunpV7FmzUrMm7cQjFoODYmEW43GXJjrWwkm\nrKo/H9F8OTvtaw3fVwz6bSKGBSfC+VJ220Hy4mR0Te0KfeN9h76DstnlaNikkahiD1MwNtC5oqIC\np19JwLA7Q3Vel498nJ2UiE6vdhZ1nmNLj2DYT0Mhl8hRXlwOtxLGu3mAB3jk9QjtXdujkCrEVvet\neLvkbZ0iqO2td6Dzpi7w9PTU5Fa1BpO/P5erQObIZ4cxclecwXOf0k9x6tsz6DRC3OcxBUPDY12B\nB2Nk3XuEW7tuQpovQ0VgBUJHtq2qbTC8bur8sjb35/whbsC4V2kOXEaU75rpbjzYkn/a/6qNKE3T\nKCsrhlQqg6urtg1Mpfr39WLWr1+b80vjlB6mvfD29jYo+rFmA7subG1KrjYR27cOcKv08LddCMHO\nu/gN98eVm1fQtrStWpkTJSolbnS8gajAKL3wrja3x+z6TdV+FZf3u/jHBfS51dtgM1wHdVD5VyUg\nUtzJJdkVcknVz4QVBAhAAC6XXwZcgZMlJ/Fa4WuQsH5jEokEI9JfxN51+9FzQk9eYXfDEBt3PtT1\npivn+nwkPihPKwNGiPs8YtA37o4yPP7PNYT/xw0518d1zbiex7SPOE54ng/DkLH12of4PVGu7xkg\nNNxA+x4SAyGLmkiNNpi1a3sJDpG2Ntx5SnPl7Ez/YbFVeoRE0k2lUVAAHn36EP/8/g9c77miUqEC\nooCOsTFV4Vzu3J66Ql5Mr6N++NVYqK3iUQU8pZ6cx1zzTIgiSFlbZ55/JolKwpnDdZG4QJ4u1RhL\n4dYWLVwhtsra3BXFFE2hwrPCKhs99bnYxl0ut51ggrmwrxm35w6oPU1LhPpzc3NBqSjUb1DfqsZW\n33O3xzUW/p4Ji/Ub9n1LNRXdp0+fgpubO9q1i7Lp+p2FGm0wPTw8UFxcbKezqUOzaqwlZ2c8FqIf\nflULkzPHrDNqqWGLRmg4sRHP+bmKPdTya0K9jlqvQKVi9GovH7qMyusqoA4QFhcOz9q1Oc9ZO9gL\nWXQW/CWGObWyxmWiP1dllAplp8rgJnGDzF2GirIKuFAuuI3bCHANAAA8cH9QJQvHggZo0KjwqDA5\n1MbVH+o6wB05p3JQn9JVpTpa/yjavhJSNdTXfJEFsXk0Z0I3OqJreEytzGWiLkzE40HGfeRuykXj\n2wGQ01Jcfi4ZXiO90SyymUXrNaUQyR6I3ayx7zEnT57E6tW/oHnzZnj48BEKC4uwePH3dl6543Cu\nraOd0f2i2ko9R//9tP2UtlWMUXuOEo1nyUxV4Or3s9/XQBuOlUMmc4GLC1evo27fnkpVgYInz3By\nwkl0nN8JL+wehP6/9MON/1zHtVMZnOcJ7R6KYxHHNddBzTW3a6gTJ75loPNbMdgasx2FVCFkMhlo\nT+CGyw2ccDsBLxdv7Gm1F7IPXHDb/bbmNXSVsbzhegP1YxtAJrPsGkskEsSM7oKjbx7DKe/ToGka\nJXQJ9jXeB8nnEtStVx/qwiFtf2i5qP5Qbd9qGXT7Vp0396fbG8wYd/3vsXaTKNN8z7X9ji6szYC6\nhYrp3c3LeQzl0iJ0zYxBU3lTNHF5Dl0fdYHrShdk3c0ye80URaGyspz12xPXG2xv1NeM/VtkHmc2\nYqWlpcjLy8XRo0eRnn4VDx5k4pVXXsK4cWPw5MkTB67cPtRoD5PBNl9YwzwlwBhK++QpdVV6xImk\nOwr9nIth+BVIWZGCERkjIJFKQIOGDDL0eNIdf35/EE2jmsLFxQVsj0oikaDL4i7YtWA3fBJ94Kn0\nQE7zXHiO9kJ4b/EtBG5ubhj00wv4e9cJUEkqqOQUvPt4o0WdIDyQPkTX0O6QSqX4W34Mj9c/RscC\npuH+rNdZZL2ZjR7delntGvWbPgDZb2bjtz/2QO4pR/SwDjoavIbFHsL9oUxeit23ap+xcJZgSZGM\nsPIO0/h/9+A9dFN2BS2perzqta3KgnDi4Ak0eKe+5nziivOcy6sUg360Qb3BoGkaDx48grt7LcyZ\n8w0KC4uQkXEF6elX8ezZU6eS8LMVxGBaGe42EQZ7/Eh020TEi6Q7C+zc6q2UW8g/nA9psQxZ/8tG\nubwc7mDaNtS3sq6ZXXD26Fm068PMmWQXLHh61Ubvb/qivLwcZWWlCPJsbdZnl8vl6PJyV+BlrvUy\nxr3L+52RMywHO/f9BqlUitAR4Wjl38b8C8GDXyM/+L3NLScoXOwhFJYE6zU0mF475/qO2CpkzC5e\nk0oB16dukEnlWlNJM3+iQUOeK9cpkNOvMjXMu7N7V52/vQXQ35Bo7xdZWY8QHz8Z4eER2LFjqdAZ\ntQAAIABJREFUn2ZMXZ8+/Ry5XLtT4w2mTCZFZWVllaExH23ptmGbiKGnaTlMMY323OofvLki6Y5G\nfyd+fssFtNzQAh0rO4IGUPDwGY7Jj6Gzfwx85D5Vzew0PCQeKC+qgFYlRb/yj9k8KBQKjYdtLWOg\nr1frF9AQDT9o7FTGRj8fqq+GpIWCSuU40Xk+9AuRrNV6wUdlnUrdAiqJRjYBqroUx0xMQD/3Xh3b\nWwy9Sm204cCBA1ixYjnmzp2H9u07OHiljqXGG0wvL28UFhbCx8e76hHTDZsxOTtdw2btHw0NiYSG\nVMoYTWMi6c4GV2VmwZNC1N1SFy0rW1Y9Asjd5RisHIxDTw6hb/1+mucm1k5C275hkMtddd7PlhNI\nuCXi7KXzax5CoUH9sKRY0Xl7pBfsXYjUbFBzJJ9MRrvSdjqPX5dfR8OBjTTauOr1GX7XhNpbLBsZ\nZyv4wtxFRYWYMWM6ZDI5duzYC09P7qrzmgQxmF7MiC+twRSP6XJ21oZdtGA47FeduHe2H6gaw4ki\nzA3x2v+uYYCyn056We4rR2lZKVxKtS0hOXiMvGH5aO2jDX1yVZjySbCZYwwMBRMs16vlQ6lU4uz6\nM5CnyEC5U6jVqxaiYzuafC79alL9aIN+WBIQqyBjvfmhbOztVbLxqeuDgg8K8M+Wk2h6twlkkOFO\nwB0oXvJEi6a6g6TZ3zX9DYnx9hbdylxHee98vaDnzp3DF1/MxMSJH2PQoCF2X5uzQgymRh7PNA/D\nMjk7y1DfmCQSV6gnZ+jvbNW7c+b54kcr2QNjykI0xdIPrcJN4YbyRuV4XPEYf7X8C5VeFXDp644u\nQ7oKnouv0MNUY8C8TiVKIs4aFBUW4cRbx/DypZfhKmG85+zfs/Hn2T/wwtzBot5DrMgDF+Kb3423\naVgmTGH/CMlzoc8hsG0gsh9mgVJRaBsYJnh+/Z5mdZEMc4x/w8be49o7BM6XX62oqMDixYuQlpaK\ndes2wc9PnNRhTYEYTC8fPHvGnokpHJI1T86OXwZNLPoqPUz1q/50Djm0labGKiXtv8M1DL/q3lzU\nBA14HslbDMNiru6uUAzxRNQMy/Io5hsDBsbw2FYi7syPp/GfS/+BlOVV+dF+6LSrI9KHXUXr6GDe\n19rKQ9Pv27OmMdC+zjnC3BKJBP4BhipDbLhD87pFdWIqc8VGPbTvZz76a2Zvom7evIH4+MkYOvRF\nfPbZ5w7fWDsjNd5gih0ibR05O/NH4+ir9PCJpGsxVimpf1OzbX7KMPzK7+3U96+PGy9dQ70tD9CY\nYsQBKJrCocaH0Wpca6uuSw2XMVCvWX+zw9xwtN6xLa6b20VXHWOppmVlC1z+32Veg8kX5hazLoqi\nkJeXBw8PD2b4txGMGQPjwhS67S1cBSfOCl/rhRjMD4Fb9n0TahdZv34dfvttJxYt+h5BQa1Ev2dN\no8YbTEYer5D3uHXl7ExH24BtvkoPf16PvcMV0pU0Pz9lLPzKR+d3uiAtOBWpf6VCViJDefNyhI0O\nR20zxnOZt2bDoh61OIC4m5qFeT1jAQuRaxb7PU3cehYl20oQeKsxHnhm4nGnx+g0MwZePqZdb7Yx\nAACZTLwxYF4vgzPrqXB7wpa3aomPehjXf+VaC1+7SE7OY8THx6NVq9bYsWMfXF25NYsJDDXeYHp7\n++DevVvQtmloJ68btonYJ0/JDr+q20TMFUnngn+HK6wraWqexdKBziFd2wLCKUqrY6yoR/xNTTcE\nLpXqelTGrkF5+3JUJlZqhd+ryHC5hoDBATqPceXQTLnO5/eeR9C8lmhe0Zx54AlA/0FjU95mDFo7\n2CbGQP86az8L98xVc4T6rY1Q64Ut0I96qNfAVZkrJE7BjOEzXPOhQ4ewZMlizJr1JTp16mKTz/Bv\ngxhMb2+DmZjG2kRMx7TX2UokXXCFJuSnjO1uLSk2cRTq3lVTJ3SIvW76kx6MhdY6j++CTRc2Y+S5\nOCgkTHj0vvQ+Lr5yEf3bDdScy9B7N93bKdpVoDWWrM/VM6knUv5JQVj3MJPeTwi+vJ/2OGXwfaNp\nmCTUbwv4PDR7wx0tAgyNqG7+naZpHDjwO6RSCZo3b4n169ejrKwM27fvRu3atovaHD9+DH//fQSz\nZs01OLZ06SKkpCRDoVBAIpFg3rxF8PBw7tYVYjA5DKZWJN3abSLChT/M3DnbiqSLxbTqUsPCmKp3\nsfsMRVPh6gO1RORBKK+nzecZD4HXqlUL/dcMxKGtfwEXKVBuNLz7+aB/X8ZYcnnC5l5ntwdunI83\npgKQmJoIdDfrbQ0Q4wmbL9QvQWWlCud/SYLrGVfIlTKUNS1H3bh6aNkpyII1O75qVwht5IMtTkHp\n5IQBIDMzE0uWLNZce7lcjlatgvHLLz9h2LCX0KxZc4P3tpSlSxchMfEMb0702rV0fPfdCnh5md7S\n5yhqvMFkhAsKkJFxBUFBLVk/BJldjBMTftVV6WFEx9kqPc5hdITyLFytLYDa6Fca5PWcAUsKZExB\nbUTZalJiQrlSqQQxr8ZAOoYdXrO+Nml5vQrgoeHj+XQ+PJp4mP2+asRUk3Jhaj705JwTGHx6MFyl\nrkxb0hMgLf0Kbsy8jpYdTTeathjubGu0mz/ddpEmTZrj5ZdH4e7du/D0rI27d+8gPf0K0tJSUFJS\ngmnTvrD6WkJDw9G9e0/s3bvL4BhFUbh/PxMLFsxFfn4+YmOHYfDgoRzv4lzUaINJ0zSuXUvHgwf3\n8e6772DZsmUICwuDPYyl2lDKZOw2EecWSeeDbSwZ4y8D41EZK5m3bsO7WCwtkLEG3KFc7pAkn6a1\ntUQTpAOkyEnJRX26ns7jf4UcQe9BfS16b6EeRXPg27TdTruJiMRIuEndQFf9DwDalATj4I6DaBL5\nnEE4l++6ObtXyYVQu8jdu3cwadIkDBgwEAsXfq+JnpSVleL27Vto3Pg5i8594MAebN++Reex6dNn\no0+ffrhwIYnzNaWlpYiLG4VRo16FSqXCxInvo3XrNmjRoqVFa7E1NdZgPnz4AIsXL8DZs6cgkUgw\nYsRLaNNGrRhj7R+G4ftVf5F0faMjgVSqG8o0paBIWxhj29yUPZV6TIErtKYN5WrbWNhYS5iiy5td\n8Xf+Ufjs8Ub7nPbIdslGcrvLaP1FG7ND0+Z6leYgkUiQczEXEXQEIAFL9IIGaKDWvVpg55XZr9PP\nh9qif9XWCLWLbNmyBZs2/YqFC79DcHCIzuvc3NzRurXlAwJiY4cjNna4Sa9xd3dHXNxouLkx6YDI\nyCjcuHGNGExn5eeff8DZs6cQFdUB169fw0cfTa4yWHz5OGug9hylrDxl9RJJBwyNjrEduGmFMaaV\ny4vF3KIeR6MOdwPqTYm86nHhzYcp1aUSiQS94vug6L1CJJ49Dx9/H/QN6W/RmrUqMpZ7lWKQ13GB\nklJCIWX3j0oACVDpqYJc7gZ2PpQv8qF5pURqMBPSGeErRsrPz8Nnn32KgIBA7Ny5X2OYnIV79+5i\n9uwZWLNmIyiKQkrKJbzwgvNL8Dm1waQoCosXz8fNmzfg4uKCqVNnIiCgseb44cMHsWPHVshkMrRo\n0RLx8VNF3wDff/+/ePHFOISFtcPw4YP0jpovMMANrfkvTVeAoqSgKEA3X1U9wj5so2OuPJz5BUXa\ncnmxbQbWLuqxF4bV0fzfDz5hCv7qUm7VGE/P2mjfJ8qCNetX7dpWPpBNWP8wJGxOQL9s3XFTpVQp\nKjtXGuRD1etVb9TU32ntMQoqVTlUKutu3KyFUIvL0aNHsXDhfEyfPhPdrDSP1Vz0Q9/btm1CQEAg\nunbtjoEDX8B7742FXC7HoEFD0LRpMweuVBwS9Q+Si5ycQuvOpDKR48ePIiHhH0yfPgtpaanYuHEt\n5s1bDICJv7/++mhs2LANbm5umD17Bvr2HYCuXU0v6Rs2bBB27drD8jCtm8OUSpn8JMBfUSqRyBwu\nxsyHfnjNXkaHyxDoo28I2NfNXkU91sQaoUwuYQquCm1rGYLz+5Og/LMIsicylASW4LnRz6FFuyC7\nF6rdvnQbjxdlocuDLvCQeSBDloH0runoNr0HZDLDtXAVUDGREN3NmyG2EZ0XC18xUklJCebO/RK5\nuXmYP38RfHzq2G1N/zbq16/N+Q/q1B7m5cvJ6NgxBgAQEtIW6elXNcdcXd2wcuVaTahBpVKZHXZQ\n9w5aG/UPSa3/qutVan9kao/AnlJ1YjHF07E23D1nxtsMwM5hoXrkhAHr5VfZ3hS/9Jpww7tYD/7E\nir8RvToajagq3dU04NyZc7gx/waej7GvxFqzds0QuC4QiUeSUJ5XjoCOjdGzRW/O5+pea+ENILcH\nb92RcWIwNPDa32JqagqmTPkMY8e+jZdeGmXV8xK0OLXBVCqL4eGhLWuXSqWgKEqjmuLr6wsA2Llz\nK0pLSxAd3dGs8ygUCiiVxSz9TPONJ1ulR/2D4RJJZyuE6PbpCU3PsJ9gurWa4q0Jf5uBfghXXz2G\nYrW22K/ZXSz2CGUKtQRxGQIxQgFP8p/AZ7u31lgyr0CHpx2xd+0euxtMgOkvjBgQyXvcnLYc/o2b\naSPj1O9lDrp5Ya2BpygKK1Ysx/Hjx/Hjj6sRGNjErPcniMOpDaZC4QGlUqn5O03TOrtAiqLwww/L\n8OBBJubOXWj2eby9vfHsWYEowWljGKr0GBccF+7Ts69gOnfOzzn6QLlQ38yYnA57x6++lto8lSOH\nIfOhu5my77W21INP/t8FDHkypOqvutev9lUvVFRUwMXFBc6CtYqRTMvBA5YUsgm1izx4cB+TJn2M\nrl17YOvWXZxhZ4J1cWqDGRYWjoSEf9C7d1+kpqYYlBx/++03cHV1xTffLLLohuflxUwsadjQ/Nlv\n1lbpEbqZ8Qummx5SY+PI8Ku5aHsV+fOr4m5m9s1LOaN8oDihAK0H71bbDUpaCS+JF3S9egnKXcud\n5gZumBe2twdvrKKZ+3vH1y4CAL/99ht++WUV5s9fhNBQ3TF4BNvh1Aaze/deSEw8i/Hj3wIATJs2\nC4cPH0RJSQlatw7G77/vQ3h4BCZOfB8AMHLkK+jevafJ5/Hy8qqaiWnaD4hbpcd6Iuls+PNSpoTU\nuNfhjOFXMYg18KaGI3VfJ1xZavqaDT14udx5e/3U146mJVUbNfXjUkT0jcTfzY5j6F3ddgCaplAQ\n+QzMwG3aoWFwawsnmIJ+OxWzHnHfO/Vzmb9rf4/Pnj3FlClT4Ovri50796NWrVo2W7+QDuy+fbux\nb99uyGQyvPHGOMTE2HlKgoNwaoMpkUjwySfTdB577jltjP7EiXNWOQ/jYbL1ZI0NkTZU6TG8edve\nYxDnheqH1HQnGTC5U+eT4RPCGgbe3HCkJQpF1VFBBuAKGzMevFzuirqf1MVfc46gV05PyCQyFFKF\nOBByAJHxkQ4Ng9tTOMEUjOVDmRYX7f2noKAAEydOhI+PLxo0aIATJ05gwoSJePHFOJt+FiEd2Ly8\nXPz22zb88stGlJWVYsKEtxEd3dGpwu+2wqkNpr3w9vYRNURajb5KjyNF0tkIe6HGWjQkVTdv5/R0\n1HCNDLOGgRcbjuRXKOIvxuK+eTt/U7yYApk2Pdri2a5n2L/5AKRPZZAHydFneH/I5XKHhcEd6VWa\nCjsfykSFdIv8VCoarq6uSE6+pPk8S5YswLp1q/Huu+NNVtgRi5AO7NWraQgNDYdcLodc7omAgEDc\nvHndKqpBzg4xmGBCsnl5j0U8U1ItRNLZ6IeFuCYZMKhvjtqbuqP6zLhwRM7PeCjX+OguAFXXm7tC\n2lnRTS0It114+3ijxwTDBnnLw+CmhXKd1as0hlC7SH5+PnJycvHeexPQunUI0tOv4OrVNFy7dg25\nubkWn9scHVilUqkzhkuhUKCoqMjitVQHiMEEUyV769b1qtAqwA7J6reJMP2U1VcknWugMwAYeqGU\nwI3MOvk8MegX9UgkjtX35AupCbcEqV8rA9uAOCPMxsQ2EoLWas/gy8PrF8g4iyqPEELtIqtW/YyD\nB//EsmU/olmzFgCAqKgOVj2/OTqw+t0LSqXSpjM1nQliMAHUru2NwsJCzmPVXSQ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Alv49df19l/cYQaDTGYBAJBFHxCCtu2bcKYMS/jww/fw4cfvod79+5adB6+CmGAmRrz2WfTsWzZ\nSqSkXMKpUyctOheBYAokh0kgEIzCJ6QA2He4NpkaQ3AkxMMkEAhGcYYwKZkaQ3A0xMMkEAhG4RvC\nDNhuuDZXhTCZGkNwJKRKlkAgiOLRo4eYPXsGfvpprc7jxcVFmjDp7t078ezZU7z55tuOWCKBYBVI\nlSyBQLA6JExKqEkIepgEAoGgplWrVk0BbM7IyIhp1arVKwA8MzIyVlX9eRKAMgB/ZWRkzHHkOgkE\nW0EMJoFAIBAIIiAhWQKBQCAQREAMJoFAIBAIIiAGk0AgEAgEERCDSSAQCASCCIjBJBAIBAJBBP8P\nT6lq1MQN/YwAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "r = np.exp(-(X[:, 0] ** 2 + X[:, 1] ** 2))\n", "\n", "from mpl_toolkits import mplot3d\n", "\n", "def plot_3D(elev=30, azim=30):\n", " ax = plt.subplot(projection='3d')\n", " ax.scatter3D(X[:, 0], X[:, 1], r, c=y, s=50, cmap='spring')\n", " ax.view_init(elev=elev, azim=azim)\n", " ax.set_xlabel('x')\n", " ax.set_ylabel('y')\n", " ax.set_zlabel('r')\n", "\n", "interact(plot_3D, elev=[-90, 90], azip=(-180, 180));" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In three dimensions, there is a clear separation between the data. Run the SVM with the rbf kernel:" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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wtruUlFSxXrjQj5hgZBSwVX4YDAZycw9z9eoVenp6+MpX3iY4OOSxx0uSxI4d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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "clf = SVC(kernel='rbf')\n", "clf.fit(X, y)\n", "\n", "plt.scatter(X[:, 0], X[:, 1], c=y, s=50, cmap='spring')\n", "plot_svc_decision_function(clf)\n", "plt.scatter(clf.support_vectors_[:, 0], clf.support_vectors_[:, 1],\n", " s=200, facecolors='none');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "SVM additional notes:\n", "* When using an SVM you need to choose the right values for parameters such as c and gamma. Model validation can help to determine these optimal values by trial and error.\n", "* SVMs run in O(n^3) performance. LinearSVC is scalable, SVC does not seem to be scalable. For large data sets try transforming the data to a smaller space and use LinearSVC with rbf." ] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.9" } }, "nbformat": 4, "nbformat_minor": 0 }