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{
"cells": [
{
"metadata": {
"toc": true
},
"cell_type": "markdown",
"source": "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#データ処理\" data-toc-modified-id=\"データ処理-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>データ処理</a></span><ul class=\"toc-item\"><li><span><a href=\"#アイリスデータ読み込み\" data-toc-modified-id=\"アイリスデータ読み込み-1.1\"><span class=\"toc-item-num\">1.1&nbsp;&nbsp;</span>アイリスデータ読み込み</a></span></li><li><span><a href=\"#テストデータとトレーニングデータに分ける\" data-toc-modified-id=\"テストデータとトレーニングデータに分ける-1.2\"><span class=\"toc-item-num\">1.2&nbsp;&nbsp;</span>テストデータとトレーニングデータに分ける</a></span></li><li><span><a href=\"#特徴量標準化\" data-toc-modified-id=\"特徴量標準化-1.3\"><span class=\"toc-item-num\">1.3&nbsp;&nbsp;</span>特徴量標準化</a></span></li><li><span><a href=\"#决定境界のプロット\" data-toc-modified-id=\"决定境界のプロット-1.4\"><span class=\"toc-item-num\">1.4&nbsp;&nbsp;</span>决定境界のプロット</a></span></li></ul></li><li><span><a href=\"#SVM\" data-toc-modified-id=\"SVM-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>SVM</a></span><ul class=\"toc-item\"><li><span><a href=\"#linear\" data-toc-modified-id=\"linear-2.1\"><span class=\"toc-item-num\">2.1&nbsp;&nbsp;</span>linear</a></span><ul class=\"toc-item\"><li><span><a href=\"#正則項を大きくする\" data-toc-modified-id=\"正則項を大きくする-2.1.1\"><span class=\"toc-item-num\">2.1.1&nbsp;&nbsp;</span>正則項を大きくする</a></span></li></ul></li><li><span><a href=\"#非線形問題とKernelトリック\" data-toc-modified-id=\"非線形問題とKernelトリック-2.2\"><span class=\"toc-item-num\">2.2&nbsp;&nbsp;</span>非線形問題とKernelトリック</a></span></li><li><span><a href=\"#アイリスの問題の場合\" data-toc-modified-id=\"アイリスの問題の場合-2.3\"><span class=\"toc-item-num\">2.3&nbsp;&nbsp;</span>アイリスの問題の場合</a></span></li></ul></li><li><span><a href=\"#K-Means\" data-toc-modified-id=\"K-Means-3\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>K-Means</a></span><ul class=\"toc-item\"><li><span><a href=\"#Kernel-K-Meansの実装(パクリもの)\" data-toc-modified-id=\"Kernel-K-Meansの実装(パクリもの)-3.1\"><span class=\"toc-item-num\">3.1&nbsp;&nbsp;</span>Kernel K-Meansの実装(パクリもの)</a></span></li><li><span><a href=\"#線形の場合\" data-toc-modified-id=\"線形の場合-3.2\"><span class=\"toc-item-num\">3.2&nbsp;&nbsp;</span>線形の場合</a></span></li><li><span><a href=\"#非線形の場合\" data-toc-modified-id=\"非線形の場合-3.3\"><span class=\"toc-item-num\">3.3&nbsp;&nbsp;</span>非線形の場合</a></span></li></ul></li><li><span><a href=\"#Kernel-PCA\" data-toc-modified-id=\"Kernel-PCA-4\"><span class=\"toc-item-num\">4&nbsp;&nbsp;</span>Kernel PCA</a></span></li></ul></div>"
},
{
"metadata": {},
"cell_type": "markdown",
"source": "https://gist.github.com/lightondust/59f30199ede7827c24141509134a42f1"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "from IPython.display import Image\n%matplotlib inline",
"execution_count": 1,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "# データ処理"
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## アイリスデータ読み込み"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "from sklearn import datasets\nimport numpy as np\n\niris = datasets.load_iris()\nX = iris.data[:, [2, 3]]\ny = iris.target\n\nprint('Class labels:', np.unique(y))",
"execution_count": 2,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": "Class labels: [0 1 2]\n"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## テストデータとトレーニングデータに分ける"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "import sklearn",
"execution_count": 3,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "sklearn.__version__",
"execution_count": 4,
"outputs": [
{
"data": {
"text/plain": "'0.19.2'"
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "X.shape, y.shape",
"execution_count": 5,
"outputs": [
{
"data": {
"text/plain": "((150, 2), (150,))"
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "from sklearn.model_selection import train_test_split\n\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=1)\n# X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=1, stratify=y)",
"execution_count": 6,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "print('Labels counts in y:', np.bincount(y))\nprint('Labels counts in y_train:', np.bincount(y_train))\nprint('Labels counts in y_test:', np.bincount(y_test))",
"execution_count": 7,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": "Labels counts in y: [50 50 50]\nLabels counts in y_train: [36 32 37]\nLabels counts in y_test: [14 18 13]\n"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## 特徴量標準化"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "from sklearn.preprocessing import StandardScaler\n\nsc = StandardScaler()\nsc.fit(X_train)\nX_train_std = sc.transform(X_train)\nX_test_std = sc.transform(X_test)\nX_combined_std = np.vstack((X_train_std, X_test_std))\ny_combined = np.hstack((y_train, y_test))",
"execution_count": 8,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## 决定境界のプロット"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "from matplotlib.colors import ListedColormap\nimport matplotlib.pyplot as plt\n\n\ndef plot_decision_regions(X, y, classifier, test_idx=None, resolution=0.02):\n\n # setup marker generator and color map\n markers = ('s', 'x', 'o', '^', 'v')\n colors = ('red', 'blue', 'lightgreen', 'gray', 'cyan')\n cmap = ListedColormap(colors[:len(np.unique(y))])\n\n # plot the decision surface\n x1_min, x1_max = X[:, 0].min() - 1, X[:, 0].max() + 1\n x2_min, x2_max = X[:, 1].min() - 1, X[:, 1].max() + 1\n xx1, xx2 = np.meshgrid(np.arange(x1_min, x1_max, resolution),\n np.arange(x2_min, x2_max, resolution))\n Z = classifier.predict(np.array([xx1.ravel(), xx2.ravel()]).T)\n Z = Z.reshape(xx1.shape)\n plt.contourf(xx1, xx2, Z, alpha=0.3, cmap=cmap)\n plt.xlim(xx1.min(), xx1.max())\n plt.ylim(xx2.min(), xx2.max())\n\n for idx, cl in enumerate(np.unique(y)):\n plt.scatter(x=X[y == cl, 0], \n y=X[y == cl, 1],\n alpha=0.8, \n c=colors[idx],\n marker=markers[idx], \n label=cl, \n edgecolor='black')\n\n # highlight test samples\n if test_idx:\n # plot all samples\n X_test, y_test = X[test_idx, :], y[test_idx]\n\n plt.scatter(X_test[:, 0],\n X_test[:, 1],\n c='',\n edgecolor='red',\n alpha=1.0,\n linewidth=1,\n marker='o',\n s=100, \n label='test set')",
"execution_count": 9,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "# SVM"
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## linear"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "from sklearn.svm import SVC\n\nsvm = SVC(kernel='linear', C=1.0, random_state=1)\nsvm.fit(X_train_std, y_train)\n\nplot_decision_regions(X_combined_std, \n y_combined,\n classifier=svm, \n test_idx=range(105, 150))\nplt.xlabel('petal length [standardized]')\nplt.ylabel('petal width [standardized]')\nplt.legend(loc='upper left')\nplt.tight_layout()\nplt.show()",
"execution_count": 10,
"outputs": [
{
"data": {
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\n",
"text/plain": "<Figure size 432x288 with 1 Axes>"
},
"metadata": {},
"output_type": "display_data"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### 正則項を大きくする"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "from sklearn.svm import SVC\n\nsvm = SVC(kernel='linear', C=0.02, random_state=1)\nsvm.fit(X_train_std, y_train)\n\nplot_decision_regions(X_combined_std, \n y_combined,\n classifier=svm, \n test_idx=range(105, 150))\nplt.xlabel('petal length [standardized]')\nplt.ylabel('petal width [standardized]')\nplt.legend(loc='upper left')\nplt.tight_layout()\nplt.show()",
"execution_count": 11,
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": "<Figure size 432x288 with 1 Axes>"
},
"metadata": {},
"output_type": "display_data"
}
]
},
{
"metadata": {
"collapsed": true
},
"cell_type": "markdown",
"source": "## 非線形問題とKernelトリック"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "import matplotlib.pyplot as plt\nimport numpy as np\n\nnp.random.seed(1)\nX_xor = np.random.randn(200, 2)\ny_xor = np.logical_xor(X_xor[:, 0] > 0,\n X_xor[:, 1] > 0)\ny_xor = np.where(y_xor, 1, -1)\n\nplt.scatter(X_xor[y_xor == 1, 0],\n X_xor[y_xor == 1, 1],\n c='b', marker='x',\n label='1')\nplt.scatter(X_xor[y_xor == -1, 0],\n X_xor[y_xor == -1, 1],\n c='r',\n marker='s',\n label='-1')\n\nplt.xlim([-3, 3])\nplt.ylim([-3, 3])\nplt.legend(loc='best')\nplt.tight_layout()\nplt.show()",
"execution_count": 12,
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": "<Figure size 432x288 with 1 Axes>"
},
"metadata": {},
"output_type": "display_data"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "線形だとうまく分離できない"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "svm = SVC(kernel='linear', random_state=1, C=10.0)\nsvm.fit(X_xor, y_xor)\nplot_decision_regions(X_xor, y_xor,\n classifier=svm)\n\nplt.legend(loc='upper left')\nplt.tight_layout()\nplt.show()",
"execution_count": 13,
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": "<Figure size 432x288 with 1 Axes>"
},
"metadata": {},
"output_type": "display_data"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "kernel でいい感じに"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "svm = SVC(kernel='rbf', random_state=1, gamma=0.10, C=10.0)\nsvm.fit(X_xor, y_xor)\nplot_decision_regions(X_xor, y_xor,\n classifier=svm)\n\nplt.legend(loc='upper left')\nplt.tight_layout()\n#plt.savefig('images/03_14.png', dpi=300)\nplt.show()",
"execution_count": 14,
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": "<Figure size 432x288 with 1 Axes>"
},
"metadata": {},
"output_type": "display_data"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "カーネル分散を大きくすると、キツイ境界が引かれる(この場合は過学習)"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "svm = SVC(kernel='rbf', random_state=1, gamma=5, C=100)\nsvm.fit(X_xor, y_xor)\nplot_decision_regions(X_xor, y_xor,\n classifier=svm)\n\nplt.legend(loc='upper left')\nplt.tight_layout()\nplt.show()",
"execution_count": 15,
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": "<Figure size 432x288 with 1 Axes>"
},
"metadata": {},
"output_type": "display_data"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "High bias"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "svm = SVC(kernel='rbf', random_state=1, gamma=0.01, C=10.0)\nsvm.fit(X_xor, y_xor)\nplot_decision_regions(X_xor, y_xor,\n classifier=svm)\n\nplt.legend(loc='upper left')\nplt.tight_layout()\nplt.show()",
"execution_count": 16,
"outputs": [
{
"data": {
"image/png": 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tgQDzV6/OWzGTlHXvkbM1KKXUSmAlwLhxsn8klzgdS5QoLdxKuuLkv+codHaytnoLm3Z/PhQAC0be3sYdtbx+eDQ/XvdGWjbxTMZpR2Vjt2gMDAwwvago7NhECBtnvlVkbhyTkBk5Eyit9SZgE8DUqXU6V9ctdJyOJbKKo4kpjjfdZM+1GxqAzk6aNh9H6zlsaAzft0TwX9trh0cza3U9qNz2dIqsbMzq5VPt7dTddVfoeFtXFxPLy4e83w5BsIrN6Y4O5vf3U9TfzwBQXWzcBsqLiuiKM24TWTMTcoW4+DxOKvuN7J4GtIrj4cNwzTXG+Uxx3LYNrrgisyquocEwRZghsLH2La262UiIMGOMIsUp2meH7EyLmtXLRAgTgKr29qwJQpjYVFTQcuwY04uKqBsY4NDkybZeSxDsQgSqAEhmv1E2pgGt4rhjB7zxhhFHtHixcf79+8OruHQE8tQLzUNMEZH7lrTGECbLuaw28Wg9oT736PUA/HjdG2HrVmXD+/mfCwfXrdywlid4n3ybbrULu2zmW4B5wFil1AngIa21bG93CYn2G2VzGtAUqX37jMfd3cbPSoVXcakKpFk5zato5uHvhfdut+5b0hrOXBjGxh21rFrcypoIm/h9S1qHRBmtb6zltcNGfND6bbWhlInv7JrCdZO7uPum9/D5UjdbpMuJjo6wqUCTyJtTPJNAtJubkD8U6nSrXS6+FXacR7CfZPcb2Z14Hnl9pYwYou5uuHDB+DkTgUwkTtZ9S5979HpDcILTdlabuM8XY0pwsbF2tXV/FVv3VxEIwHWTu2g7P5zHttdy35LWsGaG6Yr4/OPH6Qq66QYCAeqOHQOM9aA9NTUAFAUCSd2c4n2TjhS4oqIiWgYGONHfT1Vra+i4z+ej7q67xPkmuAKZ4vM4ye43MttWZBI7FEmkOGoNO3cOhrlu2wbLlqUukH4/VJaeGyJO5ucw9y3dt8SYsvvxujdYv62WkVcM7luyrkFFizJaExStrfurONtZSiCgOLi+icd31PLsvioe31GLz6f5+qKjCc0WkZVNWyDARIKmhIEBDgXddG/29zMj+HO0xAk7mWaKX2srJ2trhzxf19npuG27UKe1hEFEoAqAaPuNhg83qhbzeCAAjzwCnZ2hHNKME8+t4miuOd18s3H88GHjsXXvU6J1Mq3h27c1A/DcwifR+raoY1u54D3+6YVJPLa9Nmxz7WPbjRYZKxe8N+S8kVFG6xtrQRvPBQKK890lLP3mLBr/8iCP76gNtegwRTAekTdT88bbBbS1t9Ni+QNrCQpTWyAQEgefDVFIscQmXsyS0yJQqNNawiAiUAVC5A350qXwVumPPAJvvQXXXQcPPDAYvgqZiZQpji++OFgRmZhrTNY1JytWgdy9G/7f/4MyDfufPY7Wt8Vc/9Eaui+FryvFmo6LNiW4vrGWjTsMwVp1cyurl7ay5JFZ7HlrLGNuXUDfgAq16LCKYLJYb/xXf/rT3G4+sOxLGvD5Qinl0dafUiWW2NhxbkHIFiJQBUi0KbXOzkFx8vkyjx2KvF5kFQdDDRGx1smWLIGfPf0+5y6V89eT9qP1h+Juto1lNY+29ylalNGapa28HjRJrFlmHGv8y4OMuXUBPb0+xlf08runXgmJHqSfbl4UCHAoSguOqiRacAiFg9PTrU4hAlWgRE6pVVQMipP1eTst1LHSGBKtkx06BFW+9/nK7e1s2X8bW9YYz8XbbBttXSnWa6NFGf143Ruhn7WGx3fUUnFlHyNHKCYEK6d7FyeXyWdO6Z3u6CAQCISOD/h8EAhwqbeX4aWlMd9fqDcnYRCnp1udQgSqQIk2pbZ9e7go2SVOyexviqywXnzRePzm9qOoLiPC6Ii6nbOdpYyr6AXiVy2ptsiIJZ7meUyLubkGtWVfFXvfHsOfXX86psXcFKa29nZe9vno6+/nGkApxfDSUuoGBjgNHNaakghThB3rTslQKOInhov8RASqAMlGl91YpLK/ySoKPT3wk2c+YGxJKa0/Ps76xttD60KmkMUSHDtbZCgFVw7v57rJXZw6P5zHdxiV0963x/DWsXLmXdse02JuLvLXdXQwvaiIlv5+RihFjxlTAUwoLqYEmG5JcwCYYLmZZtMs4OabcyLxTEV0xHCRn4hAFSDJWs8zJd0NwErBkV+28+Hh7RRXjmfW6npOXxgGMKQ9OwwVnGjrSum2yNi0exK/v1QcVjk9vqMWpTSrbk5sMRfSJ5F4iuh4HxGoAiUbXXYjSXcDsP/WZhTwH/c9z6zn1oACn0/ztT87GjItJBKcRC0ykpl21JqwlIn7lrSmbDFPRHlREZ/q62NixE01l1Nsbpr+ctNYBOcRgSpgYq272H2NRPubrPhvbaay9Bxbf9DDhsbloePjKnrDsvQiBSfWtaM9jpa9F82ybhVCc3OuKU4T0rSYR7Knpoa6zs6QpdwJ3FSJuGksgvPkZiVWKFhi7W+yLMOE8N9qbMI1xGlwDeng+iZW1J9ka1MVGxproyaNpzIesyoyz2Ve62JP8ZBxKWVUTmcuDAuJ0++eeoUVc0+GnSMe5cHU8JuAKq2ZgmEjP8FgYoMgCEORCkrIGsmaMfx+4E2jcnruhz1AZmtIiRokJrtHynzvY9uNWCPr5tz7liQeT2iRP9jjaYLlOAw2B+zq7AxtmI02lZWM0y5XU2P5OgVXKG5FryEC5VHc0OI9GTOG/84W6O2lacbXYO3a0HvTbbOezPRdsnukrNXV1xcdDQuIBaOyiucGTxTemuxUVjI3/lxNjZnXsYbcAhwONl/MpVClIjpuFk8hNiJQHsSJFu+xGv5ZzRjm76HKKTil17T5OLB2yDlTXSOLNDVY7eXWxImwPVLBXlGmZd16nURuwBxtVXIl1pBbgBZgegzBSBWz47CVtkCA+atXhwmNiI73EYHyGE60eI8miI8+ajy3bl10kfTfcxQwxckekpm+s1ZFU8Z/wA3XdIAyXq8BNJRfMVhtpVvJ5ZoTHR3UdXQMPZ7Ee900/VVeUcH89nYmRqj/tJIS6WlVgIhAeYx0rd3pEk0Qt20z0sphMPDVFMnJk+HNZ5pRyl5xMkk0fWdWRcvrT4b6PS2fc5Ll9Sd5/fBojp65Yki+Xy7cjpmSSaZfKpWIKYRt/f3U9feHjpcAv0z6LPHHksr0p+BtRKA8SKrWbjuuBeGCaLbVsB7rP9tOz/vHWVezhZsfnZOVdbJkIo7Mqsgc/5amqtC14+X7ZZv5x4/T1tc3JGHcTQYEUwhb+vuZbvlDmpHIyigIaSAC5UESta6wm2iCuGyZ8bt57P3WD5hxxXH23/s8zJ6T9F6kVEgl4sj83ay2rI9zIU7RptXa+vrYU1LCtIjqIV7lYLrqBgIB3rx8OXRcAcXFxbZn+vl8PloGBuiDsMgmQcgGIlAeI5c5e5HXtLJtm3Gd90/0Q28vI4s+YNlnS9CzZoPFzKA1YdFFy+ek3z491YijVANl0yGeLdvcnGt9zcDAAC3Btu9FRUWhzrexsOb9zbCaFgYGmD55climnx1jnjB6NNMrKjh8/DhHLUaGc8EGi2LbFuxEBMpj5CpnzySaIG7bZrR2v3i+l8qSs7R+ZjUbyr4RVsmsXtrKa4dHs3FnbaiCWT7nJCh48sVJaVdRyZoa7AyUjYY1ydy64F9eVBRKjzCJDJU1acly2/dYJGNZN4Uz0nFn7unKZFrSTaYNwVlEoDxILnL2TKIJ4m9+A3R2ML6kl9Z/+XeUuo3VOryS0RpumNbBz94YD8D4UZdBwdYYTQhTHVO8x+YxuwJlo2He5FsiRKfORtGZv3q10TK+o4OS/n5mWEwL53w+JuagohkYGGB6URETIUzUMjE0uGW9TXAeESiPkkvnmVUQ/Xe2oHp7Obvs7+C22+JWMjoAV5X1cb67hPPdJTy+vZZ7l7TmbB3IaQu5tcpq6eigr7+fnv5+zH5Riejq7GSiz8f0oiJ+GVF53T56dFby/SKrm7ZAgIkYlWE8EiVQ5GtChZBdRKAEW9i8GU69YN14e9uQ11iTxD/36PW8dng0X1/UynP7q3i/YxhnOkt57d3RORx1dCHPVQpH5NTemIEB6rWmL9jAsC0QCFVB0W7gbe3tjA0EIIE42EmkWMSyhEeSaNpQQmKFaIhACRnhv+coBG8ikXFFybCvZYwR5qAAFL85daUjsUwm0dyF67fVhm3ezdb49gSrJtPgYE05jyYEdR0dlAQCQ6YN2wKBIU5AE6lUhHxCBEpIiwMHYO9Ga8UE0eKKoqEUPLf2DZY8Mos9b40Nta+YWdvJqfPDbWljkQ7RopLMSm/Vza2hvVNWO3yiaquoqCjM7NBmcbuZQmGmnVtfk+z60VPFxUO68dZ1dsYUG2ulYs3TM7P0ANq6uqiL8l4xKQi5xhaBUkotADYCRcD/1Vp/y47zCu7ErJrWVhsbbtPB54NFdadpbq1gQtAgsf2Bgzy2vTYjk0ImFUJkVNKz+6o4E+zka/aisjr//mn3JLpj7OWKTDI3mWYZhykIeyKs5LnqD2XN0zOz9ADqIOnri+NOSJYH72lnb+fMlN6TsUAppYqA7wKfwoj+OqiU2qG1bsn03IK7MNtiADStMjbcpovW0H2pOCROQKiNRSZ7SzNdy7BGJSlluAtXzDV6UW21ZPtFJptHBtO+un5D2v2qIh/HbOcRpxtvrtbRZFpQiIrfD0D9m09YDtawdrMhUPsXJ3caOyqo2cBvtTZ8xEqprcASjC9lggfwr2uHE8eZV9HM7Op3glXT7LTPF7YHaa79e5AyIXLzrlIYiefB1PMjx4/z7M5PsmWX8dozPV/mGz9axt88O5lraqpSikqKrD7O9nyBgC7jD65+NmwsI0cM2setiex7amq4/oJRbVkFaNPuSWxojF7ZOUWiSksqsfxl57r9+E+sCD9Y8QyMLIdqWPvomLTPbYdAVQHW1M8TwA2RL1JKrQRWAowbN8mGywrZpqHB4sxbaNjGIf2qySTbe5DSJdrm3fXbatm40xCsCaMuc+lyL5/s+yJfVI8Hb/7f5JaBxRzpN9ZyUhFXa/Vhvfai+s+hdXhFNrK8gg+9v5iALkPRjaaMccO/Txf3haYaR47o5+6b3kvYcsQJElVaUonlAQ0NcOoUEFkZraBy4Uzj9mAzOTNJaK03AZsApk6tkxAvF2PtcLu2+uVgxWTvv75Ye5A+uWY1m/7FGZdZpHAaB43fPjatgx+ve4NRS3/BHr0CFdB8gfU8w2pAo4F3jh1j6pfe5jc/uDZlkU3UKmT10g2G0OyrYuJVlzh1fjiVV30Z3/nh7DpoPP783JNA/PP8tGmwUmkLBELTHEU5tKoLeUJDA7e8ejcAp3rHAvdDdXC9NMPKKFnsEKiTgHWVtzp4TMgzGhrg1KuRHW4zr5hiEW0PktP7YSKFs3xEP6sWt7ImWBldyWOs8BXRNdDFi6xhD8u5k638M+v5YsU3+UbnQjY0lsStpGKtDyVqFRISnn1VnO4YxrsnyriqrA8NYaJqPY95bvM8VpGfv3o1t1v/XE1XoUyrFR4NDQA8+G8LLUaG+2HGTObNg2uA2enP6qeNHQJ1EJiqlJqCIUzLgc/bcF4hR1in8uZVNPPwD8eQrGXcbdixlmEVj0jBuqwDPDvgpx84yt0otrCeDQSAZy98g+JAO0/uGs6aZUNmuYH4Lenvvum9uOG1ptB8Z9eU0HvHjwommCv4woaZfLS2K2Tg0BrOXBiGz6ejhuDKtFrhcsudI0I/h6qj4P+RtZunODSqoWQsUFrrfqXUV4EXMWzmP9Ba/zrjkQlZx7rJdtAynv2yPRskE6UT2WfJ+nw8lBo8fwnGN7LLQD1PcgDwAW8CM4qL+HX/Rr7IaMxlWKu4aQ1dPcUhN6B1fWh5/UnWb6s1GijWn2SN5TkNrAlWR+u31RIIKE5fGAZoTncMAwWPb6/lox/uZMu+Kva+PSY4BXgJBUy86hLP7nPegOJlcuWaTJkDBwDY+XxvuJGhooJ5dxhC5FR1lAy2rEFprX8G/MyOcwnZ5cAB2Pu0Jf0htMk2e1N5ucCuKJ1YQneio4P3J0/m6rNneRfoC/66HPE6600psloCQMOU8R9EXR968sVJTBn/geEYxBATDbyxfXRwAAAeRklEQVR+eDSbdk+i+5IhbjOmdNJ8tILunmI6fl9CSZGmbEQ/c6e3o3zwxK4pBAIKBayYO2iJd9KA4mWy0dssEx68px0gOFVXE6qMKhdOyYqRIZtIkkSBYFrFITiNt/AF8u5faw6IJWRV7cZ/emtT9WKglGBzwIjXR0ul2NBYG2oxf/T0FSEDhrl2dPdN79H1QTFb9xvvWbOsFTQcPXMF3ZeKKRvRz4q5Jykb3s+8a9vZ2lTF6eAU3tf+7Cgjr+hn5U3vGRVa0BZvdUk6kczhyqrCRmL9PW+xIZU/LsHKiCNHqH/h/ogna6hcOJNK8v+/uAiUxwnLylv1fLCWH4Pdrjy7cPt+mAnFxUwvKuJwby/9WocqqH7gzcuXURghrrP+x12MLK9gxdzGsGrJ7HmF5ab1uUev54ZrOlizrNUQJWDjzlqe+OkUxlX0htnxTZv4Z791PacvDAvb6Nz1+2I+9+j1xoPg/i3r2lMuBcJtVUW2SOS+tPPPe+e6/Ry4+BEA9nZ+BszE+xnTU43AzBtEoDyINfGhsvQczy18MvhVyqUTzRayvXBvzZ+DYDZeGg32ppWWUhIUJDAqq+nDjFikiQMDRkp5Z2eYK08Hq5qt1n1WjbVs3FHLa4eNFHdToM53lxgOPQ33LQm/0a1vrOX1I8brl9efDK1BdV8y9kKtWtzKyOH97Do0gS3BtSfrNF+2BcKxqsIhErkvM6H+VqtB2thvBLDWnd8vbUcEykP47zQs4uGiBG6qlpxO07bmz8FgBl2yNnZrsOsJwPQ7lQATgsfN3kjRUilePzya5ZZv16b54fXDo9m6v4onfjqFzt+XMLqsL+TQW/LILBbNOs3/XPAeSg1a39Gwdf+glfzDV/+eFf/tJKuDYmQaJcpG9IdimVbUnyQQICxOym7ByGVV4QYi/56BqK7JuPj97Gz/Y+PHEysGq6OKEaz9nntcdblGBCrPsVrEwWp6cI8oWcnWPqfyigpqjh0jEAiEHR/w+Zi/enVo6tC6ORWib1CNbGMOMBAIUHPsGBNGD/arqg5eN9pnMmOQorWUv+GajtDrrCI1a3U9nb8v4WJPMXOmt7Pjrw6GEt8B7r7xPXy+Qes7GAJlZgYe2tAUOqcpEM/uq+LJlz4EGAJhipV58wwECKus7BKrbFYVbiJa+kiysV3h1dETMMOojir/MP/XjuxCBCoP8a9rh4tdUSzihcueDRtiNs+L7Ks0Pc56VnlFBfPb25kYkVg7fdgwusrLo6Z8R7OvKwU+1Z10nNOGxlpQUHFlHwBvHq1g1pp6FDD/unMsqjs9JEQ3sjrb0FjLvYtbKSoaFIjNv6gKXSsy4LZsRD+7Dk4IpVBEilUm2FJV5AFJxXY1NLDzV5MBwq3epaWs/eH03A86jxCByhOs/ZcgsjlgdsXJ6Wm5aMTqMDu/q2tI+4pUSCR0qTB2+I9YvXRe2A15SNv7GPl/D22ZBhiV0fYHDg6Zkov2rf2b//IHPPVKDb/6zi/w+eDv/7WW1vevpMgXYMrVPaG0eCDUSuR8dwnzrzsXJl6ZrhNlUlXkI9FiuzpeOkhj10x+9KMazEQGAMak3NOzoBGBcjF+P9AeYQ//nrmRNnf/yp2OH4pGtDG1dHRwe8TUXC6I5jw82/MFSoaNDT2O5WKLmv8HXFXWh8+nUYohDRyjfWu/d3ErT71Sw3+2XcnSb85i7vR2HvmXa/jgchE3/VE7c6e3hwTiviXG1Ju5xtV2fjiz/6IesGedyK1hwFnD70cRu7WEkD4iUC7Ef+tgpbS2egs3ryq12MPdweHjx2nr6xsyveX21uHZsLFHfl5rBbGh8WRCF5t1TcncK7XqZsNyHqvyiPzWXlQEv/rOL1j6TWPN6qX/GIfWipv+6AzbHzhoTDn6oGy4sQYFhNaurHZ1u6qbWGHAXhCnIe0lbGotIQxFBMoFhFLsrdbwH/YEn3Xn2tLAwAATfb4hVUyiqioVgYg3tTjktceP097fzzmg7tixwdcWFYV1tc2FeKbjYjOPpVJ5RD4uKjK6Eo+8ZSHFRUYTK+v0YOQ03n1LWlnyyCzePVEGGO1E7FwnSjTevCBq473stZcQwhGBcgj/nRYvWW+vUSktPOZ5+04qApHK1GLXwACvK8VhrcPSHj7V18e0FKsjuwJn03GxZVJ5BAKw+G9nhR1b/Lez2PFXhkj5fIMCaIpV2/nhIRNG96XipNaJPJ8QEWwzYYSoPmG0mJDqyBFEoHLEgQNw5EiEJTyU7ABGpeTOailfGF5aSsnAANMnTw4dm9jZmXLVZEeVlYmLLVblEU8YAgGYuWou754o48aPnmXHXx1k8d/O4qX/GMfMVXNp3rgvZFE390GNDEYnmc4/c5ox3jqRHQkRyQhczkQw2GZiUJDANDWImcF5RKCyjP+eo9DTA729zKto5rZQy3TIh2QHiF5RtAUCTCspifGO7BM5JnN/U7Yb71mnHU90dFAU3Hfl8/lCe6RGllewKBhxFCuZPNWbbSJhUApKijRXDAsw79p2lIJ517azv2UMJUU6dD3reUyxslrLE1VO6SZEmM+Z179vSSs+X3SBy3pM0oED3PL9/xbeZmIErP1h4W6IdSsiUDYTuXEWIjPw8q9KilZR1N11F3sczMeLHFOi/U2JSNZKb512rOvo4FBQpFsGBkLXr+vsZOSI/pjJ5E++OCmlG200YTBbc1jbuB96rCl03Ayc/avPHWHNssEbfeR5zDWp5RECE01s0k2IsIrSxZ7iUEsQ67Si9XPYHpMU3Ic0aGwwEr7nfXmKa9tMCAYiUBni9wPHjhoPOjuZV9HMNRVY7OCQL5VSKqSzTuO2/VTW8bRZNueWFxWF9lKla6X/HzcOJpMrZRgUzGTyiz3FKd1oI4XhO8F2Gqtubg0dNyuMNctaQ+IEhMQp2nlMEbAKKcSvWFJdW4sUxfuWtLL37THseWssza0VTBh1mRVzwwXOjpik8JYTRpU0b5UIUr4hApUiZsp92KbZhX9n/HDNNe7t/GUz6QhKqvupUhHBdATTOp6Wjg6mB6cH6zLcS3W25wthe5ee3VfF4ztq8fk0X190NOaNNt66iykMz+6rIhBQnO8uCaWYh5oezjnJ+gTrXkMERsMN13SEhDRRxZLq2lo0UdTa2OcVy9qessEk9J9y76DbrvTDVH5yuidaThQyIlBJ0NAAp/5tsG1FZek5KkuxWMHlf0A2SEUE3bL3SmsI6LKwiuHxHbWhdPLIZHKTROsu5mNz7xLAxh21bN1XBWqwjYc1KT3aHqohAqMIvT9RxZJuQoRVcMw29NY2IZECF08EzfOBUSUd/qCatj6z9cQKT7eeKEREoCIIfRmzdJ2FYLRQZaV8HRPicuTEcQZ6/5bTbfCNHy3j/n/+IwYCmpKis4wfNWJIKgQkNh+YRoZYcUgTRl1mzTKjI2+8PVTxBCZyDSqa2KSbEGFe1xSn890lzKztZPsDB8OyAa3TldHG+NovNYdaR1NVejb4eWro/vBMPvEJWLAg9b8rz9vlPYAIVBBrx9nK0nNUAs9t7rG8Qr6WCYNTiSc6OqC/n6v7+0PPFbW2cikQYMawYbwy4Vk+9Ls/57yuYEJRJ+NGzeDzc38etdqITB+3VjGm221IHJIajENCRa8wIvdQxRIY07xhvTnHmrZLdZ+WVRQ/P/dkWECtNRvQKnDWMe763/vp6Grn3NlRHKOGy74r+ZPPVrF0KTQ2QlOTYZJNVVx27zbet3QpIfFubIQRI9ITOyE7FKxAWQUJpA16oVNUVERLcO2pLRAIrWdFrmGZU4mxAmWrWlt5tbqGDRe+hE8FuMrXyYTic5y+9OWoN2MTpYx08TMXhjF+1OWQsSKyFQYE45Caqli1uDXMwg6DQmc9rxWrwJjnM80by+ecjBuvFOuc8YQhmijefeN7oc/l8w29xsoF7zHn8zU0/qQGY9puJrfdYSzvmqLUZHQWob5+UGSSRWtDnMxzWMWuvl4qKTdREALlX2c4eqyCBJEbZd3bBt0rZLude6ouwbDxWOKQpmXgKtQaNlz4Elu6F/H1ime4r+IHPNb5Jb7RuYzHtpeEKqJIAgHYdXCCYX7AWGda8sgs2s4PZ8Xc8Om3TINYrfuRVi9tpfyK/tAa1pMvTrI92DWy6ooUJfXtiGZ9gBpVEbVR39Klg8JiPk51jEoZ74PMxU7ILp4VKOt+pMrSczz3kb8xNChsBbUwHHfJkm0beCbnMMdm3RwLxgbZPoyOtoFAIKyPk2kXj+USTHU881ev5jfBpogDgQBvnj0bem74sGFMq6kxKgbf71lRtovVo35gCMioH/D4pUuMHPHpqOKkNaEOuPOvO0fb+eGcvjCMd0+UhVphRFYYmQSxRt1XFazKVtSfDB2z80YdreoabNiXXLM+cxrOSmNjZiKVqdgJ2cUTAhXMc4R3jJbnJuE9k2QNKRFubKthYo7NujkWjA2ytwPPAPh8Ias4ZG4XjzaGF4HpJSXUXb7MjODdrEXrsA68KyueGyIg40d8n5UL6qKe15wG+/xcY81p9l/UGy43iNqo0HxPvMeRRI7HnG7MaUv2YCqyNXg12ZYUpjiZ03DWaTlIb5rPLrETskdeClRk8z4w2lIwnojOsiJKQva4pDUa6APo76fl2LGoreEBKkbFn8a0xg4BoAx3Xvel1Db1RiOahf2x7bWUDe8Pe122xOnBe9oHN8xW18CMMSlbwZUyDAzWaThzmm7EiPTEyS6xE7KH6wUqVB21RzE1hKU15F+EkJC/lCvFDcHk9DZgLMY0Y7zW8PEwRcPuLrSxLOzP7qui8qpLRoJEjP1IaXPgQPimWZua9y1YMLQSTHd6zy6xE7JLRgKllPos8NfAR4DZWutDdgzKf2f4VN3a6i0AlsZ94KbmfUJ+YOca257SUlouX2a6UtRpzTPFxaEU9XSmRNPdY5TMeaMlOVRedSlkwLCzJXuomV/Fl6C63PYWFalObcbCLrETskumFdTbwKeBf0rnzcGk+7BmfRA0NYTtQZLqSEiM1SoOg3Zx0yXo5jU2iG5+iHT9pTPdFxkdpBQsmnWabsu0X0Zi2NBA/Qv3Bx+sYN6qmXmR+GWX2AnZIyOB0lq/A6BS/Jt9/+ilUJU0r6KZa4CHZzyFZJQ4S7Zt4JkQ2iALVPX1hY6bLr6bgAkWqzhkZhePNYabOjoIBK8/AEzQmiuwr82H9b+SXW0nokUHdQfTxdN2Aj7qZ/m7DxktK0ofQldNYJ1fZjUEe8nZGpRSaiWwEmBSeTlNX95iaUEBYmhwHrfk2UXDjrGd7uigpaNj6PE0xxBrs65JJlE6mfReijxPsvl5SY2toYGp2/+efrYya3EV86bBrFmGyWD3bklhEOwloUAppV4Bro7y1ANa6+3JXkhrvQnYBFA3darOizkAwVMEAgGmR2myGLBUZKkQr+LMtPqJtnYE4VbwZATQlrUtSwt0re+nf/gVFI8bQ1nZoDhJCoOQDRIKlNb6T3MxEEHIN2JVdYYYZV79RK4dAaFpuWQ605qkvbE31HnWaIE+b54x6WG1aUsKg5BNXG8zFwS7GPD5om7eHYi2EzYDkql+kiFy7ehsZylLHplF418e5GJPMc+anWmDhod4ApiSIeDAAeo3fgaogdJS1m6ePuS9ksIg5IJMbebLgCeAccBPlVLNWuubbBmZINhM9ejROXPxRat+0hEnU3TuW9LKkkdmseetsSz9piFS1s6040dd5vNzM0uCCFnEqYHqmpgWcUlhEHJFpi6+bcA2m8YiCHlFvH1Vr67fkFLn2UiirR1tf+AgSx6ZxVvHyrnhf9VDsDOtmX6erjgNJj0ktohLCoOQS2SKTygY7LbRx9pXdf2FzrQ6z0YSLQV8+wMHmf0XhjidtrTmgDSSIPx+I+2h4loqF05JqtOMm1IYpOGg9xGBEgqGXNno7UqFiLzhhrL6guIUrzNtvGsMTuU9QeXCmSm3QHNDCoM0HCwMRKAEIQtk2hIj0qYeCBCa3vv6oqOUDe9n16EJtMXpTDsEM/Gh9IswY3pG++KdTGGQhoOFgwiUIERgV2ZfujfxaJt0H9tey1vHyrluclfIWn73TfE704bw+7nlnYdCdvF8D2yxTiuK1d3biEAJQgROZ/bFsql/fdHRsGy+IZ1pI2/MoYy8JzwhTFbstLrLWpZ7EYEShDSJZbpo6+qi7q67or4+2QosWZt6rBup4cy7P65dPJ+xy+oua1nuRgRKENIkltjEyuhLpQKLFvCalEvPssnWjh5MbiQTq7u1OtIaPvgA9u8ffJ+sZbkLEShBcBmpBLyGaGhg568mB3sxVbD2e1NyP/Acka7VPbJaMs81frysZbkVEShByBFaD30c7SaYqk29/tYazHbq81aNKYgc5lSt7omcf6dPD75XxMk9iEAJQgTZ6Iu1qfMWzvQUhW6qidLNk7KpmxttS0tZ+8PpQ87hdVJxScZz/kV+UZDYJvcgAiUIEdi9oVdruBi4kvOXF7KhsSTpdPN4N2Cjakpvo22hEun809r4tX+/xDa5FREoQbCZaBWYVo8xsQK2NH057XRzIKy9ejwThFinhxLp/FMKjhyBOXOcj20SoiMCJQg2kWiDr9Ywa83g8VTF6ZY7RyS12Vas00OJ5/ybNm3wdU7ENgmxEYESBJuIt8E3bds4WKzj8asmkBigWKTi/CvEPx+3IgIlCFkmLdu4iSlOSW64lRig2Lgh5FZIDREoQcgyaaebm+JUWppSGoR0vI2NkyG3QuqIQAlCDkg13TzUEiONTbfS8VbwCiJQgm3YlQLuVZL99m5YyBN3t42GdLwVvIQIlGAbTqeAO03GG3xDHW7TjypyU8dbQcgUEShBsIlMq8T6N+3ZeCtmAMEr+JwegCAUPH6/Ma1XWmpbKoSYAQQvIBWUIDiIsfnWew0F8w1J3nAnIlCC4BQNDZzqvd+zfZvyBUnecC8iUHmOm5xz2UgB9yrW2CLBOSR5w92IQOU5bnLOiZU8OQwbeeLYIiH7SPKGu8nIJKGU+rZS6l2l1FtKqW1KqVF2DUwQvMiD97QDiZPI4z0W7MUqUiYiTu4gUxffy8C1WuvrgCPA/ZkPSRC8Sf2tNeztnBlXnHbvNqaYTFEy10N2787RIHOEm0Q4VvKGfDFwnowESmv9kta6P/jwNaA68yEJgvfYuW4/kLhyMtdDzBukuR7S0+OdG6abRDgyeWP9euN369+B4Bx2rkF9CXgu1pNKqZXASoBJ48bZeFlBcDfW6KJ4FMJ6iNtMCZK84W4SCpRS6hXg6ihPPaC13h58zQNAP7A51nm01puATQB1U6cW1PeSbDrtxDnncvx+4ImkDRFeTyJ3owhL8oZ7SShQWus/jfe8UuoOYBHwSa2lII5GNp124pxzL+Ym3MqFybv1CiGJ3I0iLMkb7iRTF98CYC2wWGv9gT1DEgQP4Pdzqncsazcnn61XKOshYkoQkiXTNah/AIYBLyvjK8drWus/z3hUgpDn3PLOQylvwi2E9RBpByKkQkYCpbX+A7sGIgieoKGB+heM3RbpZOt5fT2kEERYsA9JkhAEG7nl1bszDn7N5XqIEyGpXhdhwT5EoHKAOO0KA8MUMTZvUsmdDEkVU4KQDCJQOUCcdt7nwXvaOdU7M+FeJ7fgtv1IghANEShByBCjcoofYeQ23LgfSRAikY66gpABO9ft51Tv2LypnKxISKrgdkSgBCED/CeMCKPZs50eSerIfiTB7cgUnyBEkGw01S13joDS0rwWJ9mPJLgZEShBiCCZaKpBU8T0XA7NNmQ/kpAPiEAJQqr4/eztfCJvp/ZMZD+S4HZkDUoQUsSMMcpncTKR/UiCmxGBEoQUMKb28mczriDkMzLFJwhJcuF8gL1XzEypfYYgCOkjAiUIEUSNprp8mQ90NZULk2+fIQhCZohACUIE0aKpHrynnb1VN4s4CUIOEYEShAQ8eE87eztnsvZ7Y5weiiAUFGKSEIQ47Fy3n72dsu4kCE4gAiUIcfCfWCHrToLgECJQghCDB+9ph4oK14pTZGaeZOgJXkMEShBisLdzJpV/PMXpYURl9+7wYFczW2/3bmfHJQh2IgIlCFF48J52KC11ZfVkbTZoipQZ9NrTI5WU4B3ExScIERjGiBVULnRnEKw0GxQKBamgBMFKQ0NeGCOk2aBQCIhACYKFW169G2a4W5xAmg0KhYEIlCAEMdu3uz0INrLZ4Pr1xu/WNSlB8AKyBiUIQQ5c/AjMcP+GXGk2KBQKGQmUUuphYAkQAM4Ad2itT9kxMEHIJaYxwu3Vk4k0GxQKgUyn+L6ttb5Oaz0T2AV8w4YxCUJO2bluP/4TK/KierIizQYFr5ORQGmtuywPrwRk9lvIT2bMzJvqSRAKhYzXoJRSjwC3A53An8R53UpgJcCkceMyvawg2EKoepKgckFwHQkrKKXUK0qpt6P8WgKgtX5Aa10DbAa+Gus8WutNWus6rXXduIoK+z6BIGSAObUn1ZMguI+EFZTW+k+TPNdm4GfAQxmNSBByxM51+6H0iyJOguBSMlqDUkpNtTxcAryb2XAEIXf4T6yAj7gzzkgQhMzXoL6llJqGYTP/HfDnmQ9JELKPVE+C4H4yEiit9WfsGogg5Ay/H/+JJ2CGVE+C4GYk6kgoTKprpHoSBJcjAiUUFn4/9W8+AWPEVy4IbkcESigcDhwwxEmqJ0HIC0SghMJh715DnB6V6kkQ8gERKKEwMKsnQRDyBhEooTDYuxcqKqR6EoQ8QgRKKAjq33wCRpY7PQxBEFJABErwPDvX7ZfqSRDyEBEowdv4/fhPrGDeHVOcHokgCCkiAiV4n+oaZs92ehCCIKSKCJTgXYKbciv/UKb2BCEfEYESvE11Dbfd5vQgBEFIBxEowZtIpJEg5D0iUIJ3kUgjQchrRKAE79HQINWTIHgAESjBm0j1JAh5jwiU4C0aGqh/4X6nRyEIgg2IQAneQ1IjBMETiEAJ3sGsniRzTxA8gQiU4BnqX7hfqidB8BAiUII3aGgwxOl7krknCF5Baa1zf1GlzgK/y/mFk2MscM7pQWSIFz4DeONzyGdwB174DOCNzzEWuFJrPS7RCx0RKDejlDqkta5zehyZ4IXPAN74HPIZ3IEXPgN443Ok8hlkik8QBEFwJSJQgiAIgisRgRrKJqcHYANe+Azgjc8hn8EdeOEzgDc+R9KfQdagBEEQBFciFZQgCILgSkSgBEEQBFciAhUFpdTDSqm3lFLNSqmXlFKVTo8pVZRS31ZKvRv8HNuUUqOcHlOqKKU+q5T6tVIqoJTKK2utUmqBUuqwUuq3Sqn/7fR40kEp9QOl1Bml1NtOjyVdlFI1SqmfK6Vagv+WVjk9plRRSg1XSh1QSr0Z/Ax/4/SY0kUpVaSU+g+l1K5kXi8CFZ1va62v01rPBHYB33B6QGnwMnCt1vo64AiQjxHfbwOfBvY5PZBUUEoVAd8FFgLTgRVKqenOjiotngYWOD2IDOkH1mitpwMfA76Sh38Xl4H5WusZwExggVLqYw6PKV1WAe8k+2IRqChorbssD68E8s5JorV+SWvdH3z4GlDt5HjSQWv9jtb6sNPjSIPZwG+11q1a615gK7DE4TGljNZ6H3De6XFkgta6TWv978GfL2LcHKucHVVqaIPu4MOS4K+8uycppaqBPwP+b7LvEYGKgVLqEaXUceBW8rOCsvIl4AWnB1FAVAHHLY9PkGc3RS+ilJoMfBR43dmRpE5waqwZOAO8rLXOu88APA6sBQLJvqFgBUop9YpS6u0ov5YAaK0f0FrXAJuBrzo72ugk+gzB1zyAMc2x2bmRxiaZzyAImaKUKgOeB+6NmCHJC7TWA8Elh2pgtlLqWqfHlApKqUXAGa31G6m8rzhL43E9Wus/TfKlm4GfAQ9lcThpkegzKKXuABYBn9Qu3fCWwt9DPnESqLE8rg4eExxAKVWCIU6btdb/6vR4MkFrfUEp9XOMtcF8Mq98AlislPrvwHCgXCnVoLW+Ld6bCraCiodSaqrl4RLgXafGki5KqQUY5fRirfUHTo+nwDgITFVKTVFKlQLLgR0Oj6kgUUop4CngHa31BqfHkw5KqXGmC1cpNQL4FHl2T9Ja36+1rtZaT8b4/7AnkTiBCFQsvhWcZnoLuBHDeZJv/AMwEng5aJf/R6cHlCpKqWVKqRPAx4GfKqVedHpMyRA0p3wVeBFjUf7HWutfOzuq1FFKbQF+CUxTSp1QSt3l9JjS4BPAF4D5wf8HzcFv8fnERODnwfvRQYw1qKRs2vmORB0JgiAIrkQqKEEQBMGViEAJgiAIrkQEShAEQXAlIlCCIAiCKxGBEgRBEFyJCJQgCILgSkSgBEEQBFfy/wG2jprHrLRIUAAAAABJRU5ErkJggg==\n",
"text/plain": "<Figure size 432x288 with 1 Axes>"
},
"metadata": {},
"output_type": "display_data"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "宿題:自動でほどよくチューニングしましょう"
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## アイリスの問題の場合"
},
{
"metadata": {},
"cell_type": "markdown",
"source": "カーネル分散を小さくするすると緩やかなカーブを描く\n"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "from sklearn.svm import SVC\n\nsvm = SVC(kernel='rbf', random_state=1, gamma=0.2, C=1.0)\nsvm.fit(X_train_std, y_train)\n\nplot_decision_regions(X_combined_std, y_combined,\n classifier=svm, test_idx=range(105, 150))\nplt.xlabel('petal length [standardized]')\nplt.ylabel('petal width [standardized]')\nplt.legend(loc='upper left')\nplt.tight_layout()\nplt.show()",
"execution_count": 17,
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": "<Figure size 432x288 with 1 Axes>"
},
"metadata": {},
"output_type": "display_data"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "svm = SVC(kernel='rbf', random_state=1, gamma=100.0, C=1.0)\nsvm.fit(X_train_std, y_train)\n\nplot_decision_regions(X_combined_std, y_combined, \n classifier=svm, test_idx=range(105, 150))\nplt.xlabel('petal length [standardized]')\nplt.ylabel('petal width [standardized]')\nplt.legend(loc='upper left')\nplt.tight_layout()\nplt.show()",
"execution_count": 18,
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": "<Figure size 432x288 with 1 Axes>"
},
"metadata": {},
"output_type": "display_data"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "<br>\n<br>"
},
{
"metadata": {},
"cell_type": "markdown",
"source": "# K-Means"
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## Kernel K-Meansの実装(パクリもの)"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "\"\"\"Kernel K-means\"\"\"\n# Author: Mathieu Blondel <mathieu@mblondel.org>\n# License: BSD 3 clause\n# https://gist.github.com/mblondel/6230787\n\nimport numpy as np\n\nfrom sklearn.cluster import KMeans\nfrom sklearn.base import BaseEstimator, ClusterMixin\nfrom sklearn.metrics.pairwise import pairwise_kernels\nfrom sklearn.utils import check_random_state\n\nimport matplotlib.pyplot as plt",
"execution_count": 19,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "class KernelKMeans(BaseEstimator, ClusterMixin):\n \"\"\"\n Kernel K-means\n \n Reference\n ---------\n Kernel k-means, Spectral Clustering and Normalized Cuts.\n Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis.\n KDD 2004.\n \"\"\"\n\n def __init__(self, n_clusters=3, max_iter=50, tol=1e-3, random_state=None,\n kernel=\"linear\", gamma=None, degree=3, coef0=1,\n kernel_params=None, verbose=0):\n self.n_clusters = n_clusters\n self.max_iter = max_iter\n self.tol = tol\n self.random_state = random_state\n self.kernel = kernel\n self.gamma = gamma\n self.degree = degree\n self.coef0 = coef0\n self.kernel_params = kernel_params\n self.verbose = verbose\n \n @property\n def _pairwise(self):\n return self.kernel == \"precomputed\"\n\n def _get_kernel(self, X, Y=None):\n if callable(self.kernel):\n params = self.kernel_params or {}\n else:\n params = {\"gamma\": self.gamma,\n \"degree\": self.degree,\n \"coef0\": self.coef0}\n return pairwise_kernels(X, Y, metric=self.kernel,\n filter_params=True, **params)\n\n def fit(self, X, y=None, sample_weight=None):\n n_samples = X.shape[0]\n\n K = self._get_kernel(X)\n\n sw = sample_weight if sample_weight else np.ones(n_samples)\n self.sample_weight_ = sw\n\n rs = check_random_state(self.random_state)\n self.labels_ = rs.randint(self.n_clusters, size=n_samples)\n\n dist = np.zeros((n_samples, self.n_clusters))\n self.within_distances_ = np.zeros(self.n_clusters)\n\n for it in range(self.max_iter):\n dist.fill(0)\n self._compute_dist(K, dist, self.within_distances_,\n update_within=True)\n labels_old = self.labels_\n self.labels_ = dist.argmin(axis=1)\n\n # Compute the number of samples whose cluster did not change \n # since last iteration.\n n_same = np.sum((self.labels_ - labels_old) == 0)\n if 1 - float(n_same) / n_samples < self.tol:\n if self.verbose:\n print(\"Converged at iteration\", it + 1)\n break\n\n self.X_fit_ = X\n\n return self\n\n def _compute_dist(self, K, dist, within_distances, update_within):\n \"\"\"Compute a n_samples x n_clusters distance matrix using the \n kernel trick.\"\"\"\n sw = self.sample_weight_\n\n for j in range(self.n_clusters):\n mask = self.labels_ == j\n\n if np.sum(mask) == 0:\n raise ValueError(\"Empty cluster found, try smaller n_cluster.\")\n\n denom = sw[mask].sum()\n denomsq = denom * denom\n\n if update_within:\n KK = K[mask][:, mask] # K[mask, mask] does not work.\n dist_j = np.sum(np.outer(sw[mask], sw[mask]) * KK / denomsq)\n within_distances[j] = dist_j\n dist[:, j] += dist_j\n else:\n dist[:, j] += within_distances[j]\n\n dist[:, j] -= 2 * np.sum(sw[mask] * K[:, mask], axis=1) / denom\n\n def predict(self, X):\n K = self._get_kernel(X, self.X_fit_)\n n_samples = X.shape[0]\n dist = np.zeros((n_samples, self.n_clusters))\n self._compute_dist(K, dist, self.within_distances_,\n update_within=False)\n return dist.argmin(axis=1)",
"execution_count": 20,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## 線形の場合"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "from sklearn.datasets import make_blobs\nX, y = make_blobs(n_samples=1000, centers=5, random_state=0)",
"execution_count": 21,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "km = KernelKMeans(n_clusters=5, max_iter=100, random_state=0, verbose=1)\nkml = KMeans(n_clusters=5, max_iter=100, random_state=0)\n\nprint(km.fit_predict(X)[:10])\nprint(km.predict(X[:10]))\nresl = kml.fit_predict(X)\nres = km.predict(X)",
"execution_count": 22,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": "Converged at iteration 11\n[2 4 3 3 1 1 0 1 1 3]\n[2 4 3 3 1 1 0 1 1 3]\n"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "kernel K-Means"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "plt.figure(figsize=(12,9))\nfor value in np.unique(res):\n data_to_plot = X[res == value]\n plt.scatter(data_to_plot[:,0],data_to_plot[:,1],s=3)",
"execution_count": 23,
"outputs": [
{
"data": {
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\n",
"text/plain": "<Figure size 864x648 with 1 Axes>"
},
"metadata": {},
"output_type": "display_data"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "K-Means"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "plt.figure(figsize=(12,9))\nfor value in np.unique(res):\n data_to_plot = X[resl == value]\n plt.scatter(data_to_plot[:,0],data_to_plot[:,1],s=3)",
"execution_count": 24,
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": "<Figure size 864x648 with 1 Axes>"
},
"metadata": {},
"output_type": "display_data"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## 非線形の場合"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "from sklearn.datasets import make_circles\n\nX, y = make_circles(n_samples=1000, factor=.3, noise=.05)\n\nn_cluster = 2\n\nplt.scatter(X[:,0], X[:,1])",
"execution_count": 25,
"outputs": [
{
"data": {
"text/plain": "<matplotlib.collections.PathCollection at 0x7f58efa44e80>"
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": "<Figure size 432x288 with 1 Axes>"
},
"metadata": {},
"output_type": "display_data"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "km = KernelKMeans(kernel='rbf', gamma=5, n_clusters=n_cluster, max_iter=100, random_state=1, verbose=1)\nkml = KMeans(n_clusters=n_cluster, max_iter=100, random_state=0)\n\nkm.fit(X)\nres = km.predict(X)\n\nkml.fit(X)\nresl = kml.predict(X)",
"execution_count": 26,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": "Converged at iteration 5\n"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "Kernel K-Means"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "plt.figure(figsize=(12,9))\nfor value in np.unique(res):\n data_to_plot = X[res == value]\n plt.scatter(data_to_plot[:,0],data_to_plot[:,1],s=3)",
"execution_count": 27,
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": "<Figure size 864x648 with 1 Axes>"
},
"metadata": {},
"output_type": "display_data"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "線形K-Means"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "plt.figure(figsize=(12,9))\nfor value in np.unique(resl):\n data_to_plot = X[resl == value]\n plt.scatter(data_to_plot[:,0],data_to_plot[:,1],s=3)",
"execution_count": 28,
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": "<Figure size 864x648 with 1 Axes>"
},
"metadata": {},
"output_type": "display_data"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "実はKernel K-Meansでもパラメータが違うとうまく分離してくれない"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "km = KernelKMeans(kernel='rbf', gamma=9, n_clusters=n_cluster, max_iter=100, random_state=1, verbose=1)\nkm.fit(X)\nres = km.predict(X)",
"execution_count": 29,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": "Converged at iteration 13\n"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "plt.figure(figsize=(12,9))\nfor value in np.unique(res):\n data_to_plot = X[res == value]\n plt.scatter(data_to_plot[:,0],data_to_plot[:,1],s=3)",
"execution_count": 30,
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": "<Figure size 864x648 with 1 Axes>"
},
"metadata": {},
"output_type": "display_data"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "宿題:うまく分離してくれるパラメータを自動で探すには? \n参考:「初めてのパターン認識」「Python 機械学習プログラミング 達人データサイエンティストによる理論と実践 (impress top gear)」)"
},
{
"metadata": {},
"cell_type": "markdown",
"source": "# Kernel PCA"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "from sklearn.datasets import make_circles\n\nX, y = make_circles(n_samples=1000, factor=.3, noise=.05)\n\nn_cluster = 2\n\nplt.scatter(X[:,0], X[:,1])",
"execution_count": 43,
"outputs": [
{
"data": {
"text/plain": "<matplotlib.collections.PathCollection at 0x7f58ef9f3eb8>"
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": "<Figure size 432x288 with 1 Axes>"
},
"metadata": {},
"output_type": "display_data"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "from sklearn.decomposition import PCA\n\npca = PCA(n_components=2)\npca.fit(X)\nencl = pca.transform(X)",
"execution_count": 48,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "data_to_plot = encl[y==0]\ndata_to_plot1 = encl[y==1]\nplt.scatter(data_to_plot[:,0], data_to_plot[:,1])\nplt.scatter(data_to_plot1[:,0], data_to_plot1[:,1])",
"execution_count": 49,
"outputs": [
{
"data": {
"text/plain": "<matplotlib.collections.PathCollection at 0x7f58ef90aa20>"
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": "<Figure size 432x288 with 1 Axes>"
},
"metadata": {},
"output_type": "display_data"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "Kernel PCA"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "from sklearn.decomposition import KernelPCA\n\nkpca = KernelPCA(kernel='rbf', gamma=4, n_components=2)\nkpca.fit(X)\nenc = kpca.transform(X)",
"execution_count": 44,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "data_to_plot = enc[y==0]\ndata_to_plot1 = enc[y==1]\nplt.scatter(data_to_plot[:,0], data_to_plot[:,1])\nplt.scatter(data_to_plot1[:,0], data_to_plot1[:,1])",
"execution_count": 45,
"outputs": [
{
"data": {
"text/plain": "<matplotlib.collections.PathCollection at 0x7f58f1e60ac8>"
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": "<Figure size 432x288 with 1 Axes>"
},
"metadata": {},
"output_type": "display_data"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "",
"execution_count": null,
"outputs": []
}
],
"metadata": {
"anaconda-cloud": {},
"gist": {
"id": "",
"data": {
"description": "カーネル遊び",
"public": true
}
},
"kernelspec": {
"name": "asd3",
"display_name": "ASD3",
"language": "python"
},
"language_info": {
"name": "python",
"version": "3.6.6",
"mimetype": "text/x-python",
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"pygments_lexer": "ipython3",
"nbconvert_exporter": "python",
"file_extension": ".py"
},
"toc": {
"nav_menu": {},
"number_sections": true,
"sideBar": false,
"skip_h1_title": false,
"base_numbering": 1,
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": true,
"toc_position": {
"height": "505px",
"left": "1342px",
"right": "20px",
"top": "114px",
"width": "289px"
},
"toc_section_display": "block",
"toc_window_display": true
},
"varInspector": {
"window_display": false,
"cols": {
"lenName": 16,
"lenType": 16,
"lenVar": 40
},
"kernels_config": {
"python": {
"library": "var_list.py",
"delete_cmd_prefix": "del ",
"delete_cmd_postfix": "",
"varRefreshCmd": "print(var_dic_list())"
},
"r": {
"library": "var_list.r",
"delete_cmd_prefix": "rm(",
"delete_cmd_postfix": ") ",
"varRefreshCmd": "cat(var_dic_list()) "
}
},
"types_to_exclude": [
"module",
"function",
"builtin_function_or_method",
"instance",
"_Feature"
]
}
},
"nbformat": 4,
"nbformat_minor": 1
}
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