{ "cells": [ { "cell_type": "markdown", "metadata": { "school_cell_uuid": "1b23c3307c5c4698b86a0c930c85433c" }, "source": [ "# 모형 최적화" ] }, { "cell_type": "markdown", "metadata": { "school_cell_uuid": "a37f8ea91a44484498e6daf6a38b760e" }, "source": [ "머신 러닝 모형이 완성된 후에는 최적화 과정을 통해 예측 성능을 향상시킨다." ] }, { "cell_type": "markdown", "metadata": { "school_cell_uuid": "373f26192e304fe384bd20a41c9f854e" }, "source": [ "## Scikit-Learn 의 모형 하이퍼 파라미터 튜닝 도구" ] }, { "cell_type": "markdown", "metadata": { "school_cell_uuid": "e3911c3d1450449293d632b230ca4352" }, "source": [ "Scikit-Learn에서는 다음과 같은 모형 최적화 도구를 지원한다.\n", "\n", "* [`validation_curve`](http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.validation_curve.html)\n", " * 단일 하이퍼 파라미터 최적화\n", "* [`GridSearchCV`](http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html)\n", " * 그리드를 사용한 복수 하이퍼 파라미터 최적화\n", "* [`ParameterGrid`](http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.ParameterGrid.html) \n", " * 복수 파라미터 최적화용 그리드\n" ] }, { "cell_type": "markdown", "metadata": { "school_cell_uuid": "d1aaa13a1e5f44bf944456592ee0cf54" }, "source": [ "## `validation_curve` " ] }, { "cell_type": "markdown", "metadata": { "school_cell_uuid": "a21cfa574b054d6caed1fbfe38fd1280" }, "source": [ "`validation_curve` 함수는 최적화할 파라미터 이름과 범위, 그리고 성능 기준을 `param_name`, `param_range`, `scoring` 인수로 받아 파라미터 범위의 모든 경우에 대해 성능 기준을 계산한다." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "school_cell_uuid": "00aab77c1b8c4f9db19a3c968c50b05a" }, "outputs": [], "source": [ "from sklearn.datasets import load_digits\n", "from sklearn.svm import SVC\n", "from sklearn.model_selection import validation_curve\n", "\n", "digits = load_digits()\n", "X, y = digits.data, digits.target\n", "\n", "param_range = np.logspace(-6, -1, 10)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "school_cell_uuid": "84643397187446979f4c4c810fd4f03f" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 53.1 s, sys: 110 ms, total: 53.2 s\n", "Wall time: 54.1 s\n" ] } ], "source": [ "%%time\n", "train_scores, test_scores = \\\n", " validation_curve(SVC(), X, y,\n", " param_name=\"gamma\", param_range=param_range,\n", " cv=10, scoring=\"accuracy\", n_jobs=1)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "school_cell_uuid": "3dd91079782c4125a1d7b92ee5761fb4" }, "outputs": [ { "data": { "image/png": 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fcIqIiIiIiIiIiIiIrKc6CC8sX2NOipTSlAAcnzyysn/YqJYSSd4PQHQVYhCRXUohBhHZtXpZTN7tUpiSNOm3kghdH9vz1h1btjt8UNwl80YfBk/Xjz18fNI/CbR8n6TMsF2XwA+wLQvbclYSryIiIiIiIiIiIiIi66m6FcDCs11c28UAcZ4CYFs2z8+MrsZwdn4WYwywOgCRURpDaQqSwRwiIruJQgwismt10i5Ft0uvSFdaSXhjtpLI37/IhaOjKzaElsfJ6sGHji/T/omf4/vEZYodBCtlvqp+5aFVHEREREREREREREREVrNtm8pQNYblthCwdkuJu70F5rt3AXBtB892gNXVGHqbtmYRkc2iEIOI7ErGGNq91korCZMPWkkE41VASM6eXzPEcLpxHNta+/BoypIyy/tfey5pmWF5q1pJrFHWS0RERERERERERERkLcvXlisrIYZkpcrC8zOnWOvRubMjW0r0H8TrKcQgIruQQgwisiv1spis26GgJE1jTNFvJWH564cYTJZxZeEavcroQ+CZxjqtJAZVGGzPI6fEWBZ+WMGzXcAalP0SERERERERERERERlfzetXGvYdH9uyKY0hLTIA6n6V45NHRo5rzl9Y+ToctDqOB5UY4jylLMvNXLaIyIZTiEFEdqV21qXo9ojzfisJz3LwwsqaSdTV8gtzzD7ljNznYnOqNvpEcFmR9EMMlu/1W0n4PhWvn24NvQDb1qFVRERERERERERERB6N67j4jo9lQeguhxE+bCkR7X925LiL9y6vVF7w3QALyE1BXuaAobdqDhGR3cDd7gXIeKIoOgx8FngGqAE94DLwVrPZvLida1sWRZEDPAd8HDgETAEJcBeYA77ZbDZb27dC2SuMMbS7S5RpSq9IMFlGaPk4wej2EMOy5nlmj4/+3lO1w/j2ww+NJuufDDpBQFK0cao1Qrdf5qvmqQqDiIiIiIiIiIiIiDyeql8h7aWEbkg3i4nzhMnBvmj/s/ze7J88MKYwJefvfsDHDp7Gtix8xycpUuI8oe679LKYml/d2g8iIvIEFGLY4aIo+hLwt4HPw+iHzKMoegf4e8CvNJtNs4XLI4qiF4GfBH4U+CHgYb8FyyiK3gT+F+DXms1mdBR0/QAAIABJREFUugVLlD2ol3/YSiIZtJKo+MF4rSRKw82rH7B4evSP6pnGiYeOL7McU5Rg22SORVGUeEFIMCjRVVWIQUREREREREREREQeU9WrsNBbJHT7D+JlZUFW5HiOy5HGIep+jXbaeWBcc/4CHzt4GoDQDQYhhpS6X6Ob9bb0M4iIPCnVPN+hoiiqR1H0j4EvA6+xRoBh4BPA/wH8yyiKDm3R+v6tKIq+C3wf+O+BH+fhAQbo/7x9Fvhl4HtRFH1mc1cpe1Un7VL0hlpJBOO1kiiu3+T89Oj+X5aB5+tHHzq+TPt9xGzPIy1SbNehElaxLPAcD8/xHvXjiIiIiIiIiIiIiIgA/QCCYzvYlrUSZIjzwXVpyyLaf2rkuOb8LMaYwRz9h+6SIsUYyMucrMi2YPUiIhtDIYYdKIqiOvD7wM884tAfAd6IouipjV/VA75Ev23E43oe+GoURT+7QeuRj4h+K4kWZZISlykmSwktFyccr5VEfnaW2WOjv/d45QC1QVuItZTpoJVEGBCXGbYXrJxIqgqDiIiIiIiIiIiIiDyp5WvNy2GEOI9X9kX7nx05ZjFpcaN9G+g/cOdYNsYYkqJ/TVvVGERkN1GIYWf6h/QrFqx2GfibwEvAPuBF4K8B7w1933PAb0RRtB2tQr4J/LfATwBngGngAPAy8J/S/wyrucAvR1H0Y1u5SNnd4jwh7XYoMcRJr99Kwh2vlQTA3Q8ucGtmdLWEMxMPbyVhjKFM+2nV0rXJTI4V+AoxiIiIiIiIiIiIiMiGqXn9wtfh4KG7tMgoyn6F4dPTT2Nbo+sSN+dnV74Olqsx5P0QQy+LR44REdmJtuNGtzxEFEVfAv7S0OY/An6q2Wwurtq2ALwXRdGvAL8yNObzwL8P/M+budaBe8A/AH6x2Wy+v8b3zAPfiqLo54GfB/69Vfs84BeiKHqx2Wwmm7tU2Qv6rSS6xEUyaCVhj91KolxY4rzfBhoj90f1Yw8fnwxKdrkOKSVYFmFYw7FsbMteCTOIiIiIiIiIiIiIiDyu0AuwLBvXBs92ycqcpEio2hVCL+Tk1DEu3pt7YNzZ+Vm+8Mzn+nO4Ad0sJs5jJqnTyxOMMVhrBCBERHYSVWLYQaIosoD/emjzZeAnhwIMKwY3/n8OeHto138eRVF141e5ok2/6sKpZrP5nzwkwLCi2WwmzWbzrwO/PLTrFPBXN2GNsscYY2h1l/qtJIoMk6UEljd2K4msuXYriYPuBPv80eGGZcutJKwgICkzbM+n6veTsFWvopM/EREREREREREREXlitmVTGTw0t1yNoZd9+BzomTVaSlxevEp3UHEhcPrjszInNyXGlFxduqGKDCKyKyjEsLP8FPCJoW1/o9lsth82qNlsFvRbS6z21IhtG+mvN5vN/6zZbC48xti/Sb+SxGo/vQFrkj1udSuJXtrtt5Jwxm8l0T43y9VDa7SSmDy57vjlEIPtef0Qg++vnECqlYSIiIiIiIiIiIiIbJSqP2gp4fXDCEnRr6QAEK0RYiiN4fydiwA4to3v9K+HL8UtClOSFinXWze50b5NVmSb/RFERB6bQgw7y7859PoD4MvjDGw2m98G3hjaPNyWYsMMghOPO/YeD36u155sRfJR0Mm6FL1ev5VEkuFaNn4YjtVKwsQJ5/PblPbo744axx86vsxzTFGCbZG6FgaDH1bwnH5XnooXPurHEREREREREREREREZafnBucDxcCyb0hiSov+g3aHafibDiZHjzs7Prnxd92sAdLMeN9vztNMOxkA37TK3eJ073XuUZbnJn0RE5NEpxLBDRFHkAX9+aPOvNJvNR/nt8UtDrz8XRdHBJ1rY5nln6HUtiqKH1/KXj7xWr0WZJINWEgmh5eEE47WSyM9fYvbI6CoME1bIU8G+h44vkw+rMKRlhuU4VMP+CWDoBji28wifRERERERERERERERkba7tEKy0lOj/Gef9lhKWZXFm5tTIcc35C5SDig1VL+RAdR+e7VKakoW4xc3OPHGWAIbFeInLi9dYilsrVR5ERHYChRh2js8BU0PbvvKIcwx/vw38xGOuZ7P1RmyrbfkqZNeIs5i03R5qJeFjjRli6L1/nkuHR7edODN5Est6eD2HMhuEGPyAuEhx/GDlxHG5rJeIiIiIiIiIiIiIyEZZrsawEmLI4pV90YHRLSU6WZerSzdWXgduwMHaDPvCCWzLIi9z5nv3mO/eIytzSlMw373L1aUbdLNRt25ERLaeQgw7xw8MvS6Abz7KBM1mcxa4ObT5pSdZ1CY6MfS6BOa3YyGyO7SzLkUcExcpRdpvJeEFlfFaSRQlFxfmyLzRh7z1WkkYYyjTfoih8GwKSpwgWEnBLp9IioiIiIiIiIiIiIhslNpySwk3wLIsclOSFRkAz02fxLFGVwhurmopAf3KDTW/ylP1AzT8Ghb9qg432/Ms9JYoTElapNxo3eJG6xbp4D1ERLaLQgw7x5mh15ebzWbnMeZ5b515d4ovDL2+1Gw28+1YiOwO7V6bchBiMGlCYLm44XhVGIq5a8weHH24C3E5UX141xWTpmDAchxSqwAsKpUalgWu7eI7o9tUiIiIiIiIiIiIiIg8Lt/1cW0X27IInH6l4d6gpYTv+JyaHn5etG84xLDMtmwmwwaH6vupDB7Sa2ddbrZv00o7GAPdrMeVxevMd+9SlMUmfCoRkfUpxLBzvDD0+vJjzjM39HrHhRiiKDoN/ODQ5n++HWuR3SHOE9JOa9BKoocpDKHtY/mj20MMS86eZ/bo6MDD8/VjONbDD4XFoAqDHfgkRYbt+4RBv4VE1VcVBhERERERERERERHZHMvXoEMvBPrXy5dF+0+NHHNl6TrtdO3nZF3bZaa6jwPVffi2S2kMi3GLm5154iwBDEtxi7nF6yzGSxhjNu4DiYiMwd3uBciKI0Ovh8MI4xoOPxx9zHk20385YtuvbvkqNlCe51jWOI0NZFieP1iAY3jbQneRuNWmm8bkcQ/bgOcHlGW57vzGGOZuXKD39OjAw+nGMYri4WnSrNuDssTYNnEe44R1XBzyPMfDJctUWktEts84x1EREVmbjqMiIk9Gx1ERkSenY6k8jIdLnue4OBRFTq/ISbwEx3Z4burpkWMM8N6t83zqqY89dG4Hh33BJN2sRyvtkBQxN7OYwA2YDBp4tsvN7DZ3nQWmK1NqrSw7lo6jG2sn/N0pxLBz1IdeLz3mPMPjKlEU2c1mc/27vVsgiqKfBH52aPMfNpvNr27HejbKe+8Nd/GQJ/Huu+/e9/pWPE8+P0+r7JG0F6kUDnm3xFpcXHcue6HF7EQGPBhicErw7hZcvrd2ZsjkObTaACTxEh2T4vVi0laBZcGSf08BFhHZcYaPoyIi8mh0HBUReTI6joqIPDkdS2WZMYZb6V2MMSzkSxRlyV3nDqHTrz7ccGu08gerLrz9wXeot8ZryQxQGkOvjImLDys9hLZPxQ2xB4Xdfdtjwq3h2rq9KDufjqO7m9pJ7BzDIYbeY84zatzw3NsiiqKjwP8+tDkF/sY2LEd2iazMKeIYYwxpkUJp8HHA88Ya781d4/zx0Sdqh61JPMt5+ATLaTPXJTMF2Bb+IG0a2L4CDCIiIiIiIiIiIiKyaSzLIrD718N9q/+wXmo+fEr6WHho5Lhr8S1KM/7zrbZlUXMqTHkN/MH7xWXKvWyJXhFjMKRlxny6wFLWfqS5RUQelUIMO0dt6HX8mPPsyBBDFEUh8JvA/qFd/0Wz2fzeNixJdom4TDBJQkaByXMcLFwvGDs80L5zg8XG6FToce/A+hNk/ZNB4zlkFFiuhz9ImQb26BYVIiIiIiIiIiIiIiIbZfla9PK16azMMMYAcDR8auSY1GTcTu898ns5lkPDrTHh1nEsBwx0i5iFbImkTIH+69vpPTp5b2UdIiIbSSGGnetxj/qj7uxu62+QKIps4FeAV4d2/TbwP2z9imQ36eUxZBmJySHP8I0D/nhVGKxewqXK6KImloFjzsxDxxtjVioxZI6FASzPw7UUYhARERERERERERGRrbF8Ldq1XOzBA37ZoBrDU8EM7hoVh6/GNx/7PT3bZcprUHOqWFiUxtDOuyzmbXKTY4yhlXeYTxdIivSx30dEZBQ1rdk5OsDUqteVx5wnXGPu7fT3gX9jaNs7wM82m809EdF74YUX8MZsbyD3y/P8gb5EL774Iq7rkhYpleuzJGHAje48mW8z49SoHTg0ViWG7M/e5V8cG91K4pg7xekTpx46vkhT8rACtk0yGVIvEvYdOc6+6hSBG3CkMbpMl4jIVnrYcVRERNan46iIyJPRcVRE5MnpWCrjuNa6SZInLMRLdLIuVa/CvnASgOfidzl7Z/aBMbfLezz//HNP/N6lMbTTDu20gxk8N1v1qkwEdRyr/7x0xQuZrkzhO3r4T7aejqMbK8sy3nvvvW1dg/7L7RxtNibEMGpc+zHnemJRFP1XwH84tHkW+Ilms7m0DUvaFK7rKsSwgZb/Plt5B9KMwioxeY5nO1Qq9bF/6dz+4AI3Pzb6v8uZ6VM4zuh06rIyL7BtG7sa0qLADUPqg/efqDT031xEdiz9XhIReTI6joqIPBkdR0VEnpyOpTJssjrB3e496mGNuEzJTbFyrfzMgedGhhhudG7TybtMhhNP/P7T3hQTlQZLSYtuFpOUKXfiezT8GnW/TmZybnbnmQga7KtM4tgPv/4ustl0HH18O6FNjNpJ7BzDQYPH/Y0yPK7XbDbLx5zriURR9B8Bf2do8zXgi81m88Y2LEl2mXavTZkk9MoU0pTQ8nDC0ZUVhpks5/1k7VJZUeP4+nOkSf9P16WgxAkCArf//jXvcXNGIiIiIiIiIiIiIiKPpjq4Jh04AbZlUZiStMgAOLN/7arDzfkLG7YG13aYrkxxoDqN73iUxrCYtLnZvk03iwFYSlrMLV5jIV7aETdCRWR3Uohh57g29Hr9O6yjDY8bnndLRFH07wJ/b2jzHfoBhovbsCTZZdI8Je60MMbQS3uURUlgu9jBeCGG/IM5LhweXbHhgFVj2m88dHxZFJR5AZZFOpimUq1jWxau7eK7KoklIiIiIiIiIiIiIlvDdzw8x8OyWHnYLh4EB6YqkxyqHxg57uz8gxUanlTg+hyszTBdmcSxbHJTcLe3wO3OHdIipzQld7v3mFu8Riftbvj7i8jepxDDznF26PWJx5xneNyWNyyJoujngF8Y2rwE/Hiz2Xx3xBCRB3SyHnmvS1Kk5EmCY1mEQQ3LssYa337/PFcOrdFKYt/T6443aQqA7bkkZYZlO1QrdeDDxKuIiIiIiIiIiIiIyFZZvjYdDkIMvTxZ2bdWNYbzdy+Rl/mmredQ/QATfg0LSIqMW5157vYWyU1JXubcbN/mWusmaZ5uyhpEZG9SiGHnGA4bnIiiqPYY85wZej0cjthUURT9FPDL3P+z1QV+stlsvr2Va5HdrR23KOOEeNBKIniUVhLGcG7xMqU9OvBwZmL9jFCRDE6ofJfU5Ni+t3JiqBCDiIiIiIiIiIiIiGy12lCIIStz8rIAIJp5duSYtEj54N6VTVuTbVlMhA0O1Q9Q9UIAulmPm+3btJI2pTHEWcyVpevc7tyhGKxXRORhFGLYOb4z9NoBPvMoE0RR9Czw1NDm7z7Joh7x/b8I/BqwuoZ/Cvx0s9n8k61ah+x+aZHRG7SS6KYxZVESPkIrifLGbWZnRvfamjA+TwXTDx1vgHJQiSFz+4dJP6zh2g6WZRN6461DRERERERERERERGSjBG6Abdk4lk3g9CsRx4NqDCenjq60mRi2GS0lhrm2w3RlioO1aXzHwxjDYtLmVnue7qDtRStpM7d4jYV4CWNGX8MXEQGFGHaSrwMLQ9u+8Ihz/MjQ6xL4ncdd0KOIouh14J8Aq39D5sDPNpvN392KNcje0Um75N0eSZlRpDE2FmFQHbuVRO/seT444o/cF02cWHcek6ZgDJZjk1olALV6A4CKF2JbOnSKiIiIiIiIiIiIyNayLOuBlhLxICDg2A6np58eOa65BSGGZb7jc7A2w3RlEteyyU3B3d4Ctzt3SIuc0pTc7d5jbvEanbS7ZesSkd1Fd+J2iGazmQG/PbT5346iaLy7tn3/ztDrrzebzVtPtrL1RVH0MvDPgeqqzSXwV5rN5m9u9vvL3tNJOpRxTFwkmCQjtF2cMBx7/IVbF8i80Ye3aOrkuuOXqzDgeSRlhu16VPz+j7daSYiIiIiIiIiIiIjIdqn6gxDDoHVDUqSUpv8wXrR/dEuJ29273One25oFDlS9CgfrB5gI6lhAUmTc6sxzt7dIbkryMudm+zbXWjdJ8nRL1yYiO59CDDvL/zP0+hngS+MMjKLoE8APD23+9Y1Y1Drv+yL9ag8TQ7v+g2az+Y82+/1l78lNsdJKopfGlEVBYHvjt5JYbHG+2hu5LyhtTlYPrT9H0j9hKjybEoMThiuluRRiEBEREREREREREZHtUnUrgIVnu7iWgwHiQQgg2n9qzXHN+Qtbs8BVbMtiIqjzVP0A1UHoopv1uNm+zVLSpjSGOIu5unSd25075GWx5WsUkZ1JIYad5Z8C7wxt+/koiuoPGxRFkQP84tDmGyO2rTXeDP3vK2OOOwX8HrB/aNd/3Gw2/7dx5hAZFhcJRa9LWmbky60k/MrYrSTS92e5cGx0K4nnq4dx1mkFYcqSMs8ByNz+99aq/VYSvuvj2s64H0VEREREREREREREZEPZtk1lEAhYrsYQ5/2WEo2gztHGUyPHbWVLiWGO7TBdmeJgbZrA8TDGsJS0udWepztoh9FK2swtXmOht7hSWUJEProUYthBms2mAf7O0OaTwJejKBqudABAFEU+8H8Crw7t+m+azeamNROKougI8PvAkaFdf6fZbP6Pm/W+svfFRUIZJ/RWtZJww/GrH8zNnaNbGR00eGF6dCmt1ZarMNi+R2IysGwqgxCDqjCIiIiIiIiIiIiIyHZbrmoQuv0KxnGeYIwB1q7GMHvvMmmRbc0C1+A7PgdqM0xXpnAtm9wU3O0tcKtzh6TIMKbkbm+BK4vXaaedbV2riGwvd7sXIPdrNpv/XxRFvwH8zKrN/wrwnSiK/i7wB8A14BDwGvC3gBeHpvk68L9u8lJ/nX67i9WuA/Uoiv67x52z2Wy+/WTLkt2sMAVZ3MEEHr1s0ErCDbCD0ZUVhpkk5X1rAXgwbOAYeLZ+eP01pEn/T9chNxluGFIZnAjWvOr4H0ZEREREREREREREZBPUvCp3uEfg+NiWRWkMaZERuD5n9j/LH1782gNj8jJn9u4lXjjw3Das+H5VLyR0Azpph6WkTVpk3O7coeqFTAT9hwpvtedZclvMVKcJ3PHuEYjI3qEQw870V4HjwGdWbTsJ/PwYY2eBn2k2m/lmLGyVoyO2HQb+9hPMeRZQiOEjLC4STJqSmvz+VhL2eEVjstkPmD3qjdz3jLsf3x69b5kBTNpPomZe/z3DSh3bsnBsRydKIiIiIiIiIiIiIrLtXMfFd3zSIiV0A7pZTJwnBK7PscnDVL0K3az3wLj/6zv/lJePvMRrJ17mQG1mG1b+IduyaAR1ql6FpaRNJ+vRzWJ6eULdr9Hwa8R5wtWl69SDer96g9o9i3xkqJ3EDtRsNlvAjwG/+YhD/wR4vdlsXt/4VYlsvl6RQJISFykmyQmsR2slcfPiORYmRmezzuxfv5WEyTJMWWI5Npnd77lVrfU7uaiVhIiIiIiIiIiIiIjsFMvXrEO331oizmMAbMvm9MzolhJZmfGNK9/i737tF/mlb/865+58sNKGYrs4tsO+yiQHazMEjocxhlbS5mb7Np1BEKOdtJlbvMa93iKlKbd1vSKyNRRi2KGazWar2Wz+68BPAQ/W/bnfd4C/AvxIs9m8sdlrE9kMy60kAHp5TJnnhI43fiuJsqQZr/HjbyBqHF93jjLpt5IwrktaZtiuSzXonwgqxCAiIiIiIiIiIiIiO0XVXw4x9NshZ2VBXvaLdI/zUN/Z+Vn+wbd+lf/pG/+QN6++Q1Zkm7fYMfiOx4HazErFhcKU3Ostcqtzh6TIMKbkXm+BK4vXaSedbV2riGw+tZPY4ZrN5peBL0dRdAT4QeBpoAb0gDngzWazeeEJ38N6jDFPP8l7igyLixSTZmQmx0kSLHikVhLF3HVmD43+3mNWg9ogjfowZZoCkHs2hoIgrOLaLmBR8dYfLyIiIiIiIiIiIiKyFUI3wLEdKAsC1yfJU3pZQiNweeHAc9T9Gu10/Zv9N9u3+Y13f5vfOfcVPnvsU/zg8U8zEdS34BOMVvVCQjegk3ZopR3SIuN25w4VL2QyaABwqzPPYtJiprpvJcQhInuLQgy7RLPZvAb8v9u9DpHN0itiSBJSk+NlFlXLww3HDw7cPd/k5lFv5L4z06NLZ61mypIy66dUExcwUKn2T4gqXohtqXCNiIiIiIiIiIiIiOwcVa9CK2lTcQOSPCXOExpBjcD1+csf/0n+7+9+me6gJcN6OlmPP7z4Nf7og2/wiade5LUTr3B04qlN/gSj2ZZFI6hT9SosJW06WY9eFhPnCXW/RsOvkeQJ15ZuUA/qTIeTuI5ueYrsJborJyLbrjAlWdIFIC1zTF4Q2i52MH6C8v2luTX3nZl6et3xy1UYLMchMwVYFrVBiKGmVhIiIiIiIiIiIiIissMst0FerkaQFilFWQLw/Mwz/K3P/zW++OwP0fBrY89ZmJJvXf8ef/+bv8QvvPWP+P6t9ylNufGLH4NjO+yrTHKwNkPg+BhjaCVtbrZv0xmEM9pJm7ml69zrLW7bOkVk4ymWJCLbLikTTJKSmZwiT7AJCIPq+K0k7tzj/FQOOA/sO1CGTPuN9edIBq0kfIeSAjeoEAxO/KoKMYiIiIiIiIiIiIjIDlPxQizLxrVdPNslK3OSIqFq969p1/wqf+7Ua/zI05/lOzfO8sblN7nWujn2/BfvzXHx3hzTlSk+f+JlXjnyA9vSvsF3PA7UpullMYtJi7wsuNdbpJ12mAomCFyfe70FWkmb6coU9WD80IaI7EwKMYjItouLFNJ+iIEsx7fcR2ol0W6e48ohf+S+aPLEWHOYrB9iyFwLgGqljmWB7/gqQyUiIiIiIiIiIiIiO45t2VTcgG7WI3RDsrRNL0seeDDPtV0+feTjfOrwx7i4MMcbl97kvdvnMGO+z93eAv+s+Qf83uwbvHrkB/j8iZeZrkxt/AdaR8ULCd2AdtqllbbJipzb3btUvJDJoP8w463OPItJi5nqvm0JXIjIxtCdORHZdmUSgzHkZQFFiY/zSK0kzs3PUk5bI/edmXl2/ffPc0xRgm2TOgYMVGsTgKowiIiIiIiIiIiIiMjOVfWr/RCDF9BK2yRFgjEGy3rwmrllWZzad4JT+05wp7vA1+be4s2r3yEt0rHeK8kT3rj8Jl+9/BYvHnye10+8ytNTx0a+12axLItGUKPqVWglLdpZj14W08tiGn6dRlAjyROuLd2g7teYrkzpQUWRXUj/rxWRbWeSpP9FngFge+7YrSTKbo9zYQd4sHJDo3A5HEyvP8fg/UvXJjcFtutSDfvlpqq+QgwiIiIiIiIiIiIisjMtP4gXOB6OZVOYkrRIV9olr2WmOsWXoh/ji6de581r3+Frl9/mXrw41nsaDN+/9T7fv/U+RxtP8frJV3jp0Au49oMtnzeLY9tMVSap+VUW4hZJkdJK23SzLo2wQd2r0E47dLIek2GDqXAC2xrvvoOIbD+FGERk+xUFACYvAXD88aswxOcu8MHh0a0kTlcPj5UALdN+yjT3LMAQhjVsy8K2HAJn9NwiIiIiIiIiIiIiItvNtR181yfNU0I3oJP16OXJuiGGZaEX8kMnP8NrJ17h3dvneOPSm3ywcGXs97/ausGvfe+f8Vvvf4XPHf80nz32SWp+9XE/ziPzHI8DtWniLGYhaZGXBQu9RTpph8lggtD1Wegt0kraTFemaAT1LVubiDw+hRhEZAcZdOB6hNJTF6++T3ZqdHryzIHn139HYyjTfgWI1Om/b7XW751V9StbWgZLRERERERERERERORR1bzqfSGGOE8eeQ7bsvn4wYiPH4y4snSDr15+k3duvEdpyrHGt9I2vzv7x/zhxa/x6cMf47UTr3CofuCR1/G4Qi/kkBvQybosJW2yIme+e5fQC5kaBBdud+6wmLTYX9lH6D1Y3VlEdg6FGERk1zJ5QZO7wIOJ0qCweLr21LpzLLeSwLHJrAIsi2p1AoCqTmJEREREREREREREZIerehXu9RYI3ADLssjLgqzI8BzvseY7NvEUf/njX+LPP/cFvn7l23zzyrfpZr2xxuZlzp9efYc/vfoOz888w+snXuH5mVPYW/DAoGVZ1P0aFbdCK2n1Ax1ZzI0spu7XmAjqpHnKtdZNan6Vmco+XEe3SkV2Iv0/U0R2rfyDOS4cHn0Ye87djzNGf6vlKgyZb2Mw+EGI73qARdWtbORyRUREREREREREREQ2XOD6uLZLXuYEjk+cJ8R58tghhmUTYYMff+6H+dFnPse3r3+fNy6/xa3O/Njjz925yLk7FzlQm+G146/w6SMfx3/CNY3DsW2mKpPU/CqLcYu4SGmnHbpZj4mwQd2r0Em7dNIeU+EEU+EEtr3+/QQR2ToKMYjIrnX5g7N0jzkj9505dHqsOcq0X4khcyzAUK30qzCEXqCTFhERERERERERERHZFapehaWkRegGxHlCL09oDNooPCnP8fjMsU/y6tFPcO7uB3z10ps071wYe/ztzh3+ydl/we/O/hGfOfpJPnf8ZSbDxoas7WE8x2N/bZo4i1lMWmRlwUJvkU7SYTKcIHR9FuJFWmmb6crUhv19iciTU4hBRHYlYwzN5AajDmNOCc81jq07R5nnmKIE2yIdZCFqtf6JU81TFQarPrHxAAAgAElEQVQREZHtYIyhLEuMMdu9FPmIyPN85DZrC0qdiojsBTqOynazLAvbtvUzJyIfeVV/EGLwQoiXSIuMoixw7NEPAj4Oy7I4PfMMp2ee4VZ7nq/Ovc23rn2XrHzwfGCUbhbzlQ++wR9f+lNeOnSG10+8yvHJwxu2vrWEXkjgBnSyLktJm6zMme/eJfRCpgbBhdudOywmLfZX9vX/DkVkWynEICK7Unlzntn9o/c9bSYJxihJVaYpALljUVLiOC5hWAP6qVURERHZfMYYut0uS0tLtNvtkTdCRDbTqMDMxYsXdSNERGRMOo7KTuG6LvV6nYmJCarVqn4GReQjp+KGWJaNC3iOS1bkxHlCza9uyvsdrO/np1/4cf7VZ3+YN6/+GV+b+xZLSWussaUpeefGu7xz411OTh7ltZOv8rEDp3E2sTqyZVnU/RoVt0IrbdNJu8RZzI0spu7XmAjqpHnKtdZNan6V6crUE7fjEJHHpxCDiOxKN86f5d7+0YewMweeHWuO5RBD5tqAoVKtY1n9ElM6OREREdlcxhhu3brF4uIiRVFs93JEREREZJfL85yFhQUWFhZwHIfJyUkOHjyoMIOIfGRYlkXVC+mkXSpuSFa0NzXEsKzmV/jCM5/jh05+hu/ebPLG5Te5snR97PGXFq9y6TtXmQon+Pzxl3n16CeobGIlBMe2mQonqHlVFpMWcZ7QTjt0sx4TQZ2aV6WTdumkPabCCabCCbWeFtkGCjGIyK7UXLoMoyoxGIimn1l3vDHmwxDDIK9QrU70/1QVBhERkU1ljOHatWssLS1t91JEAAhDlQoVEXkSOo7KTlMUBXfv3iXPc44cOaIgg4h8ZFS9Cp20S+iGLCX9EENpDPYWHAcd2+GTh1/kE0+9wOXFq7xx+S2+d7OJYbx2kQvxEr917l/y+xfe4JUjP8DnT7zC/uq+TVuv57jsr+4jzhMW4yWysmAhXqKTdpkMG4RuwEK8yFLSZro6RcOv6feJyBZSiEFEdp2y1eb8RAo8WC3haF6h7q4fQjBpCgZK2yK3DGBRrTYAhRhEREQ2kwIMIiIiIrJVls85FWQQkY+K5WvbvuPiWg65KUjzhHATKxsMsyyLk1PHODl1jHu9Rb4+9zZ/evUd4jwZa3xaZHxt7m2+Pvc2Z/Y/x+snX+XUvhObdhwP3YCgtp9O1mMpaZGVOfPde4RuwGTYwLNhvnOHpbjFTHXfplaJEJEPKcQgIrvOvfeb3Ng/ut3DmamTY81RrFRh6J/4hGEV13WxLZvQDTZmoSIiIvKAW7dujQwwhGFIo9GgVqvhuq4uMsuWKcuSOI7v2xaGocqFioiMScdR2W7GGPI8p9Pp0Gq1Hvh5XFpawnVdDh06tE0rFBHZOo7tELoBcZ4QugHtrNv/eptuvO+rTPIXTv8of+7U67x97bt89fJb3OndG2usAd6bP8978+c5XD/Iaydf4ROHXsRzNv7WpmVZ1P0qVS+klbRpp/2/t7idUPerTAQN0iLleusmVb/KTGVKLalFNplCDCKy6zTnL0Bt9L4zh06PNUeZ9FOfmdu/QVKt1vt/ehXdNBEREdkkxhgWFxfv22ZZFseOHaNer2/TquSjrixLHMe5b5vrurr5JiIyJh1HZSfwPI9KpcL+/ftpt9tcuXIFYz4sX764uMjBgwd1zUdEPhKqXmUQXOiHGHp5wtQ2rylwfT5/4mV+8PinOTt/nq9efovZu5fGHn+9fYt//P3f4nfOfYXPHvsUP3js0zSCNW4SPAHbspkMJ6h6VZaSFr08oZ126WYxE0GNmlejm3bppj0mwwb7wkmd84hsEoUYRGRXMWnGOb8F+A/s2596zPgT685R5jmmKDFAOjgKVmv9cWolISIisnm63S5FUdy3TQEGEREREdlI9XqdY8eOMTc3t7KtKAq63S612sbf8BIR2WmqfpW7vQUCJ8CyLApTkhYZ/g6oHGBbFi8eeJ4XDzzPtdZNvnr5Lf7s+rsUplh/MNBOu/zBha/ylYvf4JOHX+S1E69wpLHxlXY8x2Wmuo84T1iM+y0mFuIW7bTHVNggdAMW4yVaSYfpyiSNoK6gnMgGU4hBRHaV9oULzB0cfbJ1unpkrDnKNAM+bCXhuh5hWAVQPysREZFNNNxGIgxDBRhEREREZMPV63XCMLyvtcTS0pJCDCLykeA7Hq7tkpc5gRsQZzFxFu+IEMNqRxqH+Esf+9f4iee+wDevfJtvXPkW7bQ71tjCFLx97bu8fe27nNp3gtdPvsqZ/c9hb3CQIHQDgppPJ+uxlLTIy5z57j1CN2AybODZMN+9y1LSZro6pYckRTaQQgwisqucu9qkPDr6ROSFI2fGmqNM728lUQn7N09CN8CxnTXHiYiIyJNpt9v3vW40Gtu0EhERERHZ6xqNxn0hhuFzURGRvazmV1mMl6gshxjyhAl25r/BG0GNH3v2dX7k6R/knZvv8salN7nRvj32+Av3LnPh3mVmKvt47cQrvHzkJQL3wUrOj8uyLOp+laoX0kratNMucZ4QtxPqXpVGWCctUm60blH1KkxX9+24wIjIbqQQg4jsGqY0vM8d4METgHpmc6Syf/05jFmpxJAO8gq1+qCVhF/dsLWKiIjI/Ywx5Hl+3zY9CSciIiIim6VWq3H79oc3wfI8xxijct8i8pFQ9SosxkuEbgBAWubkZYG7gx/i8xyXV478AC8ffokL9y7zxqU3OTt/HjPm+Du9e3y5+Xv87uwf85mjn+Bzx19mX2Vyw9ZnWzaT4cQgINKilye0sy7dvMdEUKfm1ehmPbqLMZNhg33hJLZtb9j7i3zUKMQgIrtGcuUaHxwcfZJ12t0/1j9CTZaBMeS2wTgWFhbVaj+BqlJPIiIim6csywe2ua7+OSIiIiIim8NxHryGVJblyO0iIntN6AbYVv8GeuB4JEVGnCfUd8GDfJZl8ez0SZ6dPsl85y5fm3ubt659h7TIxhof5wl/fOlP+ZNLb/Lxg6d5/eSrnJg8umEhNtd2manuI8kTFuIWWZmzELdopz2mggahF7AYL9FKOkxXJmkEdQXoRB6DrhqKyK5x8dK7pAdGJxdfODxeK4kiSQFIveVWElVsx8G1XZV4EhER2UTGPPjshP4RLyIiIiKbZdTTr6POSUVE9iLLsqh6Fdpph9AN+iGGLN4VIYbV9tem+YtnvsgXn/0h3rz6Dl+be5uFeGmssQbDd281+e6tJscnDvPaiVd56VC0YS2lAzfgYM2nm/VYTFrkZc587x5hFjAZNPAcmO/eZTFpMVPdp4coRR6RQgwisms0k+vAg/8ADXJ4evLoWHOYNAEgH5ynVKvLrSR0AiEiIiIiIiIiIiIie0PVH4QYvJDFpE1SpLTTLhU32LAb+Vul4oX88NOf5bUTr/Lu7fd54/JbXFq4Mvb4uaXr/Or3vsxvnWvw+eOf5jPHPrkhoQLLsqj5VSpeSCvp0E47xHnSr3rhVWmEdSgybrRuUfUqTFf36WFKkTEpxCAiu0Jxd4HZ6dFp+WfNJI61/klXWRSUeUGBIXf731+tDUIMSkGKiIiIiIiIiIiIyB5RdSuAhWe7uJZDbgoW4iUWAN/xCN2Aihvg7aKb6o5t89KhM7x06Axzi9d44/JbfPfmWUrzYAvLUZaSFr9z/o/4gwtf5dNHXuK1E69wsDbzxOuyLZvJsEHNr7AYt+nlMe2sSzfv0Qjq1L0a3axHdzFmIqyzL5zcdUESka2mEIOI7AqXZ79HpzH6l/qZA8+PNYdJ+60kchewLHzXxw9DLMum4oYbtVQRERERERERERERkW1l2zYVL6SX9dhf20cvi+nlCWmRrfxvKWnj2g4VNyB0A3zH3zWtH49PHuHnXvqL/IXnv8DX577FN6/8Gb08HmtsVuZ888q3+eaVbxPNnOK1k6/y/PTTT/zZXdtlpjpFkqcsxkukZc5i3KKTdJkMG1S8kKW4RTvpsK8yyUTQ2DV/3yJbTSEGEdkVzi7NQePB7U4Jzx94dqw5iqQfYkgHR75qpT9h1Qt1oiAiIiIiIiIiIiIie8p0ZYrreYprQyOo0wjq5KbstzzIYpIiJS8LWmmXVtrFtqxBhYaQwA2wd8F188lwgp94/gv86KnX+Pb17/HG5be43bkz9vjmnQs071zgYG0/r594hU8d/tgTV6cIXJ8DtRm6WcxS0iI3BXd6CwSZz1Qwgee43OneYylpM1PZp3bXIiMoxCAiO56JE87XE0Ydsk6mVYIxTigMUKYpxhgy1wagWlsOMegEQURERERERERERET2lsD1OTF5hG7eo5v26GY9XKDuVah7FUpjSPKEXp4Q5wmlKelmMd0sxgKCQcuJ0A12fPsD3/H47LFP8erRT3LuzkXeuPwm5+78/+zdd3hc5Znw/+/pZ5o0KpaNi2zcccXGNs2YugSSkIQSko0TIEAa7G4IEFJefsmGX/Zlya5DCmFDKIElZCnJhoTAYnrAphgXMM29yEWWLMsq005//5DRMpZsj2TJluH+XJevi/PMeZ5zz6DRjM65z31vLHl+Y7aJ/37vSZ5c9zeOHz6DE4fPoMzu5s7KEimKQsKMETMsMk6WdjeL47s0+E0kjFjH2oHHjkwjMSNGVSyNqZu9Pp4QHzaSxCCEGPB2rH2P3eXd/7qaWDGqpDUi14UowlMj0FQ0NOx4EpAkBiGEEEIIIYQQQgghhBAfTqqqkjQTJM0EURSR9wudCQ1+6BMzbGKGTRSBE7idVRr8KOj4b98BOpIEOhIabAxt4F5eVBWFCdWjmVA9mobMThbXLWV5/Tv4oV/S/JyX5/mNL/PipleZNuQYTq6dzfCyIQcRj0qZnSJuxmkttJP3C2S9PHm/QMpMkDST5L08W70CZVaSilj5gE8YEeJQGLi/ZYQQYo9Vu9ZDd98RoogJQyeWtEbo7mklYXSUv4rZcVRNwzoCMkiFEEIIIYQQQgghhBBCiIOlKApxI9Z5Y5/ju2S9HDk3jxu42LqJrZtgp/ACn7xfoOA7uIHX+a/VyWCoGvaehAZTMwZsu+bByUFcMOlcPjb2VF7b+gavbFlOu5spaW4Qhayof4cV9e8wKj2cubWzmVQzDlVRexWLrmpUxdM4vktroQ039Gl1MmTdPOV2iphh0+a0k3GzpGPllFupAfu6CnEoSBKDEGJAi4KAtUY73f26GlowSRnxktYJnY4kBm9PvkIsLq0khBBCCCGEEEIIIYQQQnx0WbqJpZtUxtL4gU/Wy5H18hQ8B0PTMbQkZVYSPwopeIXOygxeGOC5OdrdHKqiENNtbN3C0i3UAXjhPWHGOWP0ScwbdTxvNaxi0ebX2da+o+T5m1q2sqllKxV2OSfVHsfsodOwDbtXsVi6SU2ymqybp81px48CduVbsDyTcqsMU9Npzu2mrdBOdbySuCnXMMRHkyQxCCEGtNZNG9hR1f2vqgnxoSWtEYUhoe/jRQGRYaCgkEh0JDEkJIlBCCGEEEIIIYQQQgghxEecrumUa2WU22WEYUjOy3dUafAK6EDSjJM044RRtCeZoSOpIYwisl6erJdHgc4KDbZuoam9q1rQX3RVY8ZRkzl2yCQ2t2zlpbrXebdxLRFRSfN3F1p5fM1zPLN+EbOGTeOkEcdRFa/oVSwJM0bMsMk4GdrdLI7v0ug3kTBipOwUhD47Mo3EjBhVsTSmbvbqOEIcqSSJQQgxoL1Xvxqqu3/smBFTSlrj/VYSng4oCpZuolk2uqrLB78QQgghhPhIOuecc9i4cWPn9p133sm8efMOY0Rd7dy5k7lz5xaNrVy5EsuyDlNEQgghhBBCfDSoqkrSSpC0EkRRRN4rdCY1EAbEDZu4YRNF4ARuR0KD5+BHAXnfIe87AFiaga3bxAwLXR04lyQVRWFUxQhGVYygOd/Cy3XLeH3bmziBW9J8J3BZXLeUl+uWcsygccytnc3RFSN63P5BVRTK7BRxM06b007OK5D18uT9AikzQdJMkvfybPXylFkpKmLl0h5bfGQMnN8YQgixlyiKWBs1A12zNavyKtUlZjgGTscXJlfr+AIRjyVRFGklIYQQQghxpNu6dStnnnnmIT3ms88+y/Dhww/pMYUQQgghhBDicFEUhbgZI27GqKaSgu+Qc/PkvDxu4GLrJrZugg1u4FPwC+T9Al7g4wQeTuDR6rRjqFpnQoOpDZybCytjaT454UzOGjOXpdtX8nLdMprzLSXNjYB3d67l3Z1rGZoazMm1s5g+5JgeJ2zoqkZlLE3SdGkptOMGHq1Ohqyb70hyMGzanHYybpZ0rJxyK9XjhAkhjjSSxCCEGLDyjQ3UVXb/QTzeGFTSGhEQuR5hFBIYCgoQT5QBksQghBBCCCGEEEIIIYQQQvRER7sIi0rSeIFH1suTc3MUfAdT0zG1JGVWEj8M9rSccCn4Dl4Y4LlZ2t0smqJi6xYx3cLULdQBcEHe1i3m1s7mpBHH8d7OdSyqe52Nu7eUPH97ewOPvPM4T659gRNGzOT44TNImvEexWBqJjWJKnJenrZCO34U0JxvIesalNvlmJpOc243bYV2quIVJHq4vhBHEkliEEIMWKs3vUNY3v2Xl2OGTippjcjzicIQRwlRdAtd0TBjcRRFxTakDK0QQgghhBBCCCGEEEII0RuGZpDWDNJ2GUEY7Gk5kSfvFdBVSJoJkmaCMIoo+A55v4DjOwRRSHbPvgpg63ZncoSmdq3MfCipisrkmvFMrhnPtrYdLK5byps73iWIwpLmt7tZnl7/Es9vfJljh0xm7sjZDEmWdlPm++JGDFu3ybhZ2p0MTuDRmG0ibsQos1MQ+jRkdmIbNtWxCmmbLT6UJIlBCDFgrXF2dDuedGBYxdCS1gidAgDent92cSuBquvEDBtVObxfhoQQQgghxMFJpVJ85StfKXn/+vp6/vrXvxaNfeITn2DQoOITSrqu77M0ZyqV6nmgQgghhBBCCPEhp6kaKStJykoSRiEFzyHr5ci6eSAgbtjEDZsoAidwKHgdSQ1BFJLf04JCoaMaQczoSGjoaVuGvjasbAgXT/kk5447jVe2LOe1rSvIevmS5vphwNLtK1m6fSVjK0cxt3Y246tHl1x1QlUUyqwkcSNGm9NOziuQ8/Lk/QKpPckhBa/AVq+elJWkIpZGV7WDebpCDCiSxCCEGJC89gwb0wHQNdFgXJguud9T6HpEUYSnq3taSXScdJZWEkIIIYQQR77y8nKuv/76kvd/7bXXuiQxXHzxxUydOrVoLBaLoR7mu3/625NPPnm4QzigQYMGsXr16sMdhhBCCCGEEKKHVEUlbsaImzEGJaDgO+TcPFkvhxd4nVUX0pThBj55v0DBK+CFPk7g4gQu0I6h6sR0C9uwMTXjsD2flJXk7LHzOP3ok3hjxzssqltKQ2ZnyfPXNW9iXfMmquOVnFw7i+OGTsHUSqueoKsalbE0SdOlpdCOG3i0ORlybp4yO0XcsGl3MmTdHGm7jDI7JTdwig8FSWIQQgxIG9avxLW7/6CdOHhcSWtEYUjoebgEYJioqNhxSWIQQgghhBBCCCGEEEIIIQ6V95MWKknjBh45N0fOy1PwHUxNx9SSlFtJ/NDf03bCwfFdvNDHc33a3Cy6onasY9hYmlnyjY59ydB0Zg+bzqyh01jXvJnFda+zqml9yfObcs38edVTLFz3N44ffiwnjjiOtF1W0lxTM6lJVJHzCrQV2vCjgOZ8C1nXoMwuw9IMmvMttDkZKuNpkmait09TiAFBkhiEEAPSqvYtYHcdN72I0UeNLWmN0HUB8NQIRVWwdRPNsjB1U8oqCSGEEEIIIYQQQgghhBCHmKkZmLFy0rFy/DAg5+XJuTnyvoOu6iRNnaSZIIhCCr7T+c+PQjJenoyXR1UULM3qbDtxqCsPKIrCuKpRjKsaxc7sLhbXLWPZ9rfwQq+k+QXf4W+bXuOlzUuYUjORubWzqE0PK2lu3LCxdYuMm6XdyeAEHjuzu4gbNmV2GYQ+jZkm2vR2quKVWHppFR+EGGgkiUEIMeBEnse6pEN3rSTGOAk0pbQEhPeTGFyjIyMzHkuiKFKFQQghhBBCCCGEEEIIIYQ43HRVo8xKUmYlCaOQvFcg6+XJuXkAEkaMhBEjisDxnY62E75DEIXk/QJ5v4ACWJqJbVjYun3Ib2AclKjiM8eczdlj5/H6tjd4uW4ZrU57SXPDKGJlw3usbHiP2vKhnFw7myk1E9AO0N5QVRTKrCQJI0ar007OK5DzCuR9h5SZIGkmKPgO29rqSVpJKmNpubFTHHEkiUEIMeA0bN1INtb9h/SEilElrxO6Ln4UEOkaKgrxREdZpoQR74swhRBCCCGEOKCtW7fyzjvvUF9fTy6Xw7ZtJk2axAknnLDfeZ7nsWnTJtavX09TUxOZTAbDMCgrK6OmpoZjjz2W8vLyQ/QsShMEAStXrmTNmjXs3r0by7KoqKhg8uTJjBtXWku4QyGXy7F8+XI2btxIJpMhmUxSXV3NzJkzGTx4cJ8dZ+3ataxevZqdO3fiui4VFRWMGzeOadOmoWkD5wRiQ0MDq1atYvv27WQyGTzPIxaLkUwmGT58OLW1tQwbVtpdYQeybds23nvvPXbv3s3u3bsBSKVS1NbWMn78eAYNGnRQ62cyGVasWEFjYyPNzc3ouk5lZSVDhw5l+vTpmGb/3YXW2/f6B23YsIF169axa9cuWltbSSaTVFZWcswxx3D00Uf3W+xCCCGEEAOBqqgkzDgJM04Uj3B8h6yXJ+vm8EO/I0nBsABwAo+C15HU4Ic+hcClELhAO6aqYxs2Md3C0IxDFn/csDl11AnMrZ3N241rWFT3Oltat5c8v651O3Vv/Zlyu4yTRsxk9rBjiRvdlKv+AE3VqIylSZoerYU2nMCjzcmQc/OU2Snihk3GyZB1c1TYZZTZqUNetUKI3pIkBiHEgLN+H60ktCBi/OjJJa0R+j5REOIoIYphYqkGeiyGpmpSPkkIIYQQQvSJqVOn4u6p/gXwxBNPMGbMGKIo4tFHH+W3v/0tq1ev7jJv7ty53V7Y3Lp1K08++SSLFy9m+fLlFAqFfR5bURQmTZrEl770Jc477zx0vWd/3p9zzjls3Lixc/vOO+9k3rx5+9z/8ccf59prr+3cnj59Og8//DAAhUKBu+66iwceeIDm5uZu5w8bNoxvfOMbXHjhhagHuKvofTt37mTu3LlFYytXrsSyrH3O+cEPfsBDDz3Uuf2Vr3yF66+/HoAdO3bwi1/8gr/+9a84jtPt/BkzZnDttdcyZ86ckmLcWxRFPPLII9x7772sX999b9yKigr+/u//nq9+9avEYh1V4vb1s9RfXNfl97//PX/84x9Zs2bNAfevqqpi1qxZnH322Zx99tk9SgZoamrinnvu4ZlnnmHz5s373Xf06NGcfvrpXHjhhT16/s8++yz33nsvK1aswPO6L+Ebj8c5+eST+frXv86UKVNKXhv6/r3+QU1NTdx111089dRTbNu2bZ/7jRgxgosuuohLL7208+dGCCGEEOLDSlEUbMPGNmyq4hW4vkvOy5P18ji+g6UZWJpBOUn80CfvOxS8Ak7g4YY+rpOhzcmgK2pnQoOpmSiK0u+xa6rG9CHHMH3IMdS1bGNR3VLeblxFGEUlzW8ttPE/a1/gmfWLOW7oVE6uncWgROV+55iawaBEFTmvQFuhDT8KaM63kHENyu0yLM2gOd9Cm5OhMp4maSb64qkK0a8kiUEIMbBEERvsPN21kqjNmdjmvk9YflDodJxg8vbc4GSbMVRdl1YSQgghhBCiX7W0tHDNNdfwyiuv9GjeT3/6U+64446S94+iiHfeeYfvfve73H333dx+++3U1tb2NNyDtn79eq666io2bdq03/22bdvGjTfeyLPPPsvPf/7z/SYi9IdnnnmGG264gWw2u9/9VqxYwZe+9CWuueYavvGNb/ToGLt27eIf/uEfWL58+X732717N7fffjtPPPEEd9xxB6NGjerRcQ7WmjVr+Id/+IcDJhR80K5du1i4cCELFy7k0Ucf5ZhjjjngnCAIuO2227jnnnv2m5DzQRs2bGDDhg3cfffdvPzyy1RVVe13/4aGBq677jpef/31A66dy+V4+umneeaZZ/jMZz7DP//zP2Pb+7+zbX96+15/XxRF3HHHHdxxxx3kcrkD7r9lyxZuvfVWHnjgAX76058ye/bsXh1XCCGEEOJIZOompm6SjpXjhwE5N0fOy5PzCuiqTsrUSZkJgiik4DvkfQfHd/CjkIybI+PmUBUFW+9oOWHr5iGpSFCbHsYX0sNoyZ/GK1uX89rWNyj43SdU780LPV7dupxXty5nYvUY5tbOZkzlyP0mYsQNG1u3yLpZ2pwMbuCxM7uLuGFTZqUAaMw00aa3UxmvwNYP7d9lQvSE1AwRQgwobnsrzal9tJKIl17CNHQdwijC1zs+0OOJjg9oSWIQQgghhBD9JZ/Pc/nll/fqomZjY2Ovj7t27Vo++9nPsmHDhl6v0Rvr169n/vz5B0xg+KDnn3+e733ve/0XVDeeeOIJ/vEf//GACQwf9LOf/YwHH3yw5P2bm5u59NJLD5jA8EGbNm3ikksuoaGhoeQ5B6uuro4vfelLPUpg6I329na+9rWvcfvtt5ecwLC3MAz3+/j69ev5/Oc/X1ICwwdFUcSf/vQnvvzlL9Pa2tqr2A7mvQ4dlTC+9a1vceutt5aUwPBBjY2NXH755SxcuLBXxxZCCCGEONLpqkaZnWJIqoZR6eHUJKtJmglURUVTVBJGjOpYmqOSNVTF0iSMGKqiEkYROa9Ac76F+vZGmrLNZNwcQRj0e8zpWDnnjjud751yNZ+eeDbV8f1XVtjbqqb13LX8QX7+6j28vu1NvMDf576qopCykgxJDiKx53pIzivQkG2i1ckQRhEF32F72w4as7vwD8HzF6I3pBKDEGJAafZaun8gijhm5KdOqeEAACAASURBVNSS1oiiiNDzcCMfxTDRFQ0zlgAUYgfoISWEEEIIIURv3XLLLbzzzjsAxGIxLr74Yk4//XRGjRpFMpmksbGRd999ly1btuxzjWQyyQknnMCcOXMYM2YMtbW1JJNJbNsml8uxY8cO3n77bR5//HGWLFnSOa+lpYVvfetbPPzww4ekykE+n+eqq65i9+7dAEyYMIHPfe5zzJkzh0GDBhGGIXV1dfzP//wPDzzwQFGJ/8cff5xPfepTnHbaaf0e55o1a/jP//zPzgvip59+Op/85CeZNm0alZWVZLNZVq9ezSOPPMJTTz1VNPcnP/kJZ5xxBjU1NQc8zvXXX8/atWuLxtLpNF/84hc57bTTGDasIyG7vr6eF198kQceeICdO3fS0NDA97///T56tgd200030dJS/DfXnDlz+NSnPsXkyZMZMmQItm1TKBTIZDJs3LiRVatWsWjRIpYvX47v7/tk6fuCIOCqq64q+vmEjpLAZ511FmeeeSbTpk2joqICXddpbW1lw4YNvPnmmzz99NMltbfIZDJ85StfYfv24h7DNTU1fOELX+DUU0/lqKOOwvd9tm7dylNPPcWDDz5YlDCwfPlyrr32Wu66664elxU+2Pf69ddf3yUJobKykgsvvJATTzyR0aNHk0qlyGazbNiwgaeffppHHnmks6WF67rccMMNjB49mnHjxvUodiGEEEKIDxNVVUmaCZJmgmjPxfmslyPn5vFDn5hhEzNsKgDHdzvbTvhRQCFwKQQuLXS0Y4jpFrZuYWhGv8Vr6SYnjpjJ8cNnsKZpPYvqlrKueVPJ83dkdvLHd/+HJ9f+jRNGzOCE4TNIWclu99VUjYpYOQkzTmuhHSdwaXcy5NwcZXaKhBEj42TIujnSdhnlduqQVKcQolSSxCCEGFC2x11A6zJ+VEYjlSwvaY3QcSACVwtRNBVbs9Bsi5hhy4ewEEIIIYToN+9ftJ08eTK33347Q4YMKXo8lUoxZsyYbudOnTqVefPm8Xd/93cYRvcnzeLxONXV1UyZMoXPf/7zvPjii1x33XW0tbUBsGrVKv70pz/x+c9/vg+fVffev9CsKArXXnstV155Japa/F27srKSY489lnPPPZcvf/nLRReQ77333kOSxPC3v/0N6Hjtf/aznzF37tyix5PJJIMHD2bevHk88MAD3HTTTZ2PZbNZ/vCHP3DVVVft9xh/+MMfWLx4cdHYnDlz+PnPf05lZfEdVpWVlUyePJn58+dz3XXX8eKLL7Jo0aKDeYolq6+v73Ks//N//g+XXHJJl33j8TiVlZXU1tZy6qmn8rWvfY1du3bx4IMPkkjsv3/urbfe2iWBYfTo0SxYsIBJkyZ12b+srIwRI0Zw6qmn8k//9E+sWrWKO++8E03r+nfh+2666Sa2bdtWNHbWWWfxr//6r6RSqaLxQYMGMWPGDL7whS9w9dVXs3r16s7HFi1axP3339/ta7A/B/Ne/93vftclgeFzn/sc3/ve94jFiisHvv/zeeKJJ3LppZfy9a9/vbPiSqFQ4LrrruPRRx/t8t4TQgghhPgoUhSlM2mBOLi+S9bLk/VyuL6LpZtYugl2Ci/0KXgF8r6DG3id/1qdDLqq7UlosDE1o8cJr6VQFYWJg8YycdBYdrQ3sqhuKW/seKfkqghZL8ezGxbzwsZXmD5kEnNHzmZoanC3+5qawaBEJXmvQKvTjh8G7M63knGzpK0yLN1kd76FdidDZSxN0tr/930hDhVJYhBCDBheLkNDeh+tJPRBJa8Tuh5RFOEaKioQjydRFKWzdJIQQgghjnyh6+Lu3kcFJ9EvzIo0qmke7jAGvBEjRnDfffd1uZB6IPPnz+/xsebNm8dtt93GpZdeShRFANx///2HJInhfd/+9re54oor9rvPscceyze/+U1uvvnmzrFXX32VxsbGkqocHCxd17nzzjuZMWPGfvebP38+ixcv5tlnn+0ce+yxx/abxBCGIbfffnvR2Lhx4/j1r3+934v9ZWVl3HbbbcyfP5+33nqrxGdycJYtW9b5cwIwc+bMHl28r6qq4uqrr97vPnV1ddxzzz1FY+PHj+f+++8nnU6XdJyJEyeyYMGCfT6+bt06/vznPxeNnXDCCfzsZz/bZwIQdLw377nnHi666CLq6+s7x3/1q19x8cUXY9s9q9rXm/d6S0tLl+d2xRVXcMMNNxxw7siRI7n33nu54IILaGpqAmD16tU899xznHXWWT2KXQghhBDio8DUTUzdpCJWjh/45Lw8WS9P3itgqDqGlSRlJfGjkMKeCg1O4OKHAe1ujnY3h6oo2LpFTLexdAu1HxIahqRquGjyxzln3Km8tvUNXtmynIxbWiu8IApZXv82y+vf5uiKEcytnc0xg8Z2ezNnzLCxdYuMm6PdzeAFPjtzzcQMm3Kr4zttY7aJVqedqngFtt7/Ff6E2B9JYhBCDBi7sjuhrPsvAceMmFzyOqHr4BGgGBoqKna8o5xSXJIYhBBCiCNe4Dis+8WvaF7yOuGestri0FBNk8o5sxn7T1ejHYJ2BUeqH/7whz1OYDgYxx9/PLNnz+68M3zdunVs2bKFESNG9Puxp0+fzuWXX17SvhdffDE///nPO6sxRFHEW2+9xZlnntmfIQJw2WWXHTCB4X2XXnppURLDxo0baW9v3+f/05deeqlLRYAf/vCHB6xWAGBZFjfddBMXXHBBUXJBf3n/wvf7pk4trV1fT9x1110Ewf/ePWZZFj/96U9LTmAoxf3331+0bVkWP/7xj/ebwPC+6upqbrzxxqJkjJaWFv7yl79w8cUX9yiO3rzXH3jggaKKJBMnTuS6664ref7gwYO55ppruPHGGzvHfve730kSgxBCCCHEAeiaTpmWosxOEYYhOS/f+U8HkkaMpBEjjCIc3+loO+E7hFFIziuQ8woogKVbnW0nNHXflcN6I2kmOHP0yZw66nje3PEei+pep769seT5G3dvYePuLVTF0pxUO4tZQ6di7ZWIoCgKKStB3LBpczKdSR0F3yFpJEhZCRzfYXvbDpJmgspYGl2TS8ni8JB6c0KIAaPeyHU7XpmNGFQ9tKQ1Qt8nCkIcAhRDx9IMdDuGqZnyYSuEEEJ8CKz7xa9oWrRYEhgOg9B1aVq0mHW/+NXhDmXAOvrooznllFMO+XGnT59etP3mm28ekuNedtllJZdWjcfjXRIJVq1a1R9hFVFVtUfVBmbNmoX1gSSdKIqK2g/s7amnniranjx5MrNnzy75eJMmTerR/gdj74v8eyc1HCzP83jssceKxj7zmc8wbty4PjtGFEU8+eSTRWOf+MQnepS0c9ZZZzF+/PiisSeeeKJHcfT2vf7www8XbX/1q1/db9uM7nz6058uajuxbNkyXPlMFEIIIYQomaqqJK0ENclqRqaHMyRVQ5mVQld11D0tKSpj5RyVrKE6XknSTKArGhFQ8B12F9qoz+ykMbuLdqejokFf0lWd44ZO5Z+O/zJfPe4LTBo0jp7Uf9iVb+Gx1c/wf1+6nb+ufpbmfNcqlpqqURErZ3CiCksziaKIdjdDQ2YnGS8PQMbNsqWtnuZ8C2EU9tGzE6J0ckVPCDEguE6ebRXdfxSPD0u/a+f9CxqeDqBgGzaqoUsVBiGEEOJDIHRdmpe8frjD+Mh7vwqGtJboqq+rCjQ1NbF69Wrq6urIZDJks1l8v+sJsr2TFtavX9+ncXRHURROPvnkHs0ZPXo0ixcv7tzevXt3X4fVxYQJExg8uPvesN3RNI1Ro0YVJS7sL86VK1cWbX/sYx/rcYznnHNOZyWN/jR69Oii7aeeeorly5czc+bMPll/5cqVRVUGgB5XNziQDRs20NJSfBL2k5/8ZI/XOe+884raOqxcuZIgCEpOKOjNe33z5s3s2LGjc1vXdc4444wer2OaJlOnTu38mXFdl5UrVzJr1qweryWEEEII8VGnKApxI9Z5/cDxXbJejpybxw1cbN3E1k2wU3iBT94vkPcLeIGPG3i4gUerk8FQNWy9o12DqRklJ3sfKLbRlbWMrqxlV243i+uWsnT7W7hBaQmsju+wqO51FtctZXLNeObWzmJkenhRbIZmMChRSd4r0Oq044cBLflWsm6WtFWGpZu05FtpdzJUxtKkrORBPy8hSiVJDEKIAaGhuY5wH0kMEweP73a8O6Hr4kchga6ho5BIdJT3jBs9628qhBBCCCFET02eXHoLtH1pbm7mwQcf5LHHHmPDhg29WqO9vf2g4ziQoUOHUl5e3qM5ZWVlRduZTKYvQ+rWxIkTezxn7zj39Xo6jsO6deuKxqZMmdLj4/VmTm8cd9xxVFdXd1Zg8DyPSy65hAsuuIALLriA6dOnH9TJ1mXLlhVtJxIJJk2adFAx7+2tt94q2lYUpUslklLsXRUkm82yfv36LhUa9qU37/WlS5cWbY8aNaqookJP1NTUFG1v2bJFkhiEEEIIIfqApZtYukllLI0f+GS9HFkvT8FzMDQdQ0tSZiXxo5DCnjYMBd/BCwM8N0u7m+2o5qDbxHQLU7dQ+yChoSpewacm/h1njzmF17ev5OW6ZewutJY0NyLi7cbVvN24muFlQzi5djZTB09E/0A7jJjRkYCRcXO0ux3VJXbmmrENm/SexIWd2V20ORmqYmlsud4iDgFJYhBCDAhbg13djicKIcNLLD8aRRGh6+JEHqpuYag6eiyBqmhdej8JIYQQ4sijmiaVc2bTtGjxgXcW/aZyzmypwrAPPbnjvzt/+MMf+MlPfkJra2kno/alra3toOaXoqcJDAC2XXyiy3Gcvgpnn3oT5wfbScC+42xpaSEMi8uqjhw5ssfH682c3jBNk2uvvZbvf//7nWOe5/HQQw/x0EMPUVlZyezZs5k5cyYzZsxg8uTJ6Hrpp40aGhqKtidOnIiq9m0X08bG4p7AQ4cOJZns+d1g3SUr7Ny5s+Qkht6817ds2VK0vW7dOiZMmNDjdbpzsL8zhBBCCCFEV7qmU66VUW6XEYYhOS/fUaXBK6ADSTNO0owTRtGeZIaOpIYwish6ebJeHgWwdauzSoN2kN+PbcPmlJFzOGnELN7buZZFda+zqWVryfO3tu3gobcf43/WPs+JI2YyZ9ixJMw40JEgnLISxI0Y7U47GS9PwSuwwyuQMpOkrASO77C9vYGkmaAylpYW3qJfyU+XEOKwCwKfurIAuunsNLaQQNVK+2CPXBcicNUIRdewNRPNMombsT4p3ySEEEKIw2/sP10N/G9LA3HovJ9E8v7/A9FVKpXq9dy7776bn/zkJ30Sh+d5fbLO/hiG0e/H6Av9GWd3F457c0H9YH5ueurCCy9k9+7d/PSnPyUIgqLHmpubWbhwIQsXLgQgHo8zZ84czj33XM4++2zi8fh+1967zUM6XXpbwFLtXRWjN0kq0FFtQ1XVoiSUniQC9Ob/2d6vT186FIlLQgghhBAfZaqqkrQSJK0EURSR9wqdSQ2EAXHDJm7YRBE4gduR0OA5+FFA3nfI+x2J0ZZmYOs2McNCV3t/iVZTVaYMnsCUwRPY2lrP4i1LeXPHe4RReODJQJuTYeG6F3l2w8vMPGoyJ9fOZnCyunPtdKychBmntdBOIXBpdzPkvBwpO0XSiJFxs2S9POV2irRdhqr0bfKyECBJDEKIAaBx12bc2D5aSaRHlbxO4LqEUYRvKGhAPJZEUVVpJSGEEEJ8iGiWxYRvX0vouri7+++CkOjKrEhLBYYD0DTtwDt144033uDf/u3fuozPmTOHU045halTpzJkyBCqqqqwLKtLpYDf/OY3LFiwoFfHFr3ndpNI1ZukCU3T0DStS1JBf7nyyiuZO3cuv/rVr3j++ef3mfSSy+V44YUXeOGFF7j55pv52te+xmWXXbbP6grZbLZo+0BJD72x9zF6245BURRs2yaXy+1z7f3pzXu9P9u8HKqfHSGEEEII0fFdMm7GiJsxqqmk4Dvk3Dw5L48buNi6ia2bYIMb+BT8Anm/gBf4OIGHE3i0Ou0YqtaZ0GBqvf9be3j5UXyu/DzOHXsar2xdzmtbV5DzCiXN9UOfJdveZMm2NxlXdTRza2czvupoFEXB0AyqE5UUvAKtTjteGNCSbyXrZCm3y7B1k5Z8K+1OhspYmpTV84RuIfZHkhiEEIddXa4eujn3ZHohYyaU3ms0dFzcyEc1DHRFw4onAIW43rsTW0IIIYQYuFTTxB5cc+AdhTgCLFiwgCiKOrcrKyv5xS9+wezZs0uan8/n+ys0sR/d3Y2fzWZJJBI9Wiefzx/yi9ATJ07kl7/8Jc3Nzfztb39jyZIlLFu2jM2bN3e7f0tLC7fccgsvvfQSd9xxB2Y3CU17P+8PJgj0lb2P0duf/SiKKBSKT+z29P9bT+2dfDRmzBjOOOOMPlm71N8VQgghhBCi73W0i7CoJI0XeGS9PDk3R8F3MDUdU0tSZiXxw2BPQoOD47t4YYDnZml3s2iKSmzPOpZu9aqydJmd4mNjT+X0o09iRf07LK57ncZs9228u7N210bW7tpITaKKk2tnMeOoKZiagW3YWLpF1svR5mTwQp+mXDO2YZPek7iwM7uLVqed6lgFttxUKvqIJDEIIQ6rMArZFC/QXSuJo9tNdLO0D7wwCIiCAIcAxbSwNQPVtrENq8/7sAohhBBCCNFXmpubWbp0adHYzTff3KOLklJK/vDoLomhubmZmpqeJVjt2lX6icW+VllZyfnnn8/5558PQFNTE8uXL2fx4sU8//zzNDQ0FO3/8ssvc/PNN/PDH/6wy1p7t4/oj/YJe7/mPWkB8UFtbW1FrSSg960pSlVRUVG0XVVVxfXXX9+vxxRCCCGEEIeWoRmkNYO0XUYQBntaTuTJewV0FZJmgqSZIIwiCr5D3i/g+A5BFJLx8mS8PAp0VmiwdavHrRpMzeD44ccyZ9h01jZvYtHm11mza0PJ8xuzu/jTewtZuO5vzBk2gxNHzKTcTpE0E8T0GO1uhqybo+AV2OEVSJoJyqwkru+yvb2BhBmnMpbG0I6MFoRi4JIre0KIw2rVmhVk99VKIjGs5HVCp6OUq6cDKNi6jWYYJAypwiCEEEIIIQau5cuXF11MHTp0KKeddlqP1li/fn0fRyVKUVFRQVlZWdHYqlWrerxOb+b0l+rqas4++2x+9KMf8fzzz3PrrbdSXV1dtM/DDz9MY2Njl7lDhgwp2l69enWXRIGDtXeCyPbt28lkMj1eZ82aNV3GBg0a1Ou4SrF37Bs2lH4iWQghhBBCHHk0VSNlJRmSHMTI9DCGJGtIWUlURUNVFOKGTVUszVHJwVTHK0gacTRFJQLyfoHmfCv17Y3szDaTcbP4Yc+qtymKwviqo7l85sVce+KVHD/sWAy19Hvbc16BFza9wi2L/oMH3/oLW1rr0VSVtF1GTaIaW++oNJZxs+zI7CTj5ogiyLo5trTW05xr6fO/B8RHiyQxCCEOq1fffbHbcTWIGH/01JLXCV0HN/KJDA0VFTvecYdOXJIYhBBCCCHEANbU1FS0PW7cuB7Nd12XlStX9mVIokSKojBt2rSisddee63H6yxZsqSvQupTmqbx8Y9/nDvvvLOonK3v+7zyyitd9p81a1bRdiaT4d133+3TmKZOLf4bMYoi3nrrrR6vs2LFiqLtRCLBmDFjDiq2A9n79Wlqaurz10cIIYQQQgxMqqISN2MMSlQxMj2MoanBpO1yDM1AUTpaUqRjZRyVqqEmUU3KSmKoOhHgBC4thXZ2ZHbSkGmirdCOG3g9On5NsprzJ53Dd0+5mnPGnkqZ1bWq3L6EUcgbO97lV0vu4z+W3M9bDatQFZXqeAXVsTSGqhFGIS2FNhqzTRR8B4hoKbSypW07bU6mqH2iEKWSJAYhxGH1Zq6u2/HaVoVYWbrbx/YWRRGh6+FEPqpuYGoGejyGoRlSskgIIYQQQgxo+Xy+aFvXe9b1ceHChWSz2b4MSfTA3hemn3rqKXK5XMnzXdfl8ccf7+uw+tSkSZOYOHFi0dj27du77DdlyhTi8XjR2MMPP9ynsYwePbpL24rHHnusx+vsPWfatGlomnZQsR3IpEmTusT+xz/+sV+PKYQQQgghBh5FUbANm8p4mhHlQxlePpTKWLqzsoGp6ZRbSQYnqxmSrKbcTmHpJgBe6NPmZmnM7mJHeyMt+VYKvlNykkDCjHHa0Sfynblf5/NTzmN42ZADT/qAza3beGDlo/zb4l/z4qaOBO6aRDVpO4WqKHihT1NuN0253XihTxAGNGV3sa19B3mv0KNjCSFJDEKIw2bbjs00xbovgTReL72PbOR5EEW4Soiia9iqgWZZUoVBCCGEEEIMeOXl5UXbGzduLHmu67rccccdfR2S6IHzzz+/6OJ3JpPh9ttvL3n+b3/72y7VOAaiRCJxwH0Mw+DTn/500dijjz7KunXr+iwORVE499xzi8Yef/xxtm7dWvIazz33XJd2Ep/4xCf6JL79URSFCy64oGjsoYce6tF7XgghhBBCfPiYmkE6Vs7QsiHUpodTnagibsRQFBVd1UmZCQbFKzkqVUNFrBzbsFEUBT8KyXh5mnK7qc800pxvIeflCaMDt3DQVI1jj5rM1XMu5euzv8jUmgkodN/2uzsthTaeWPs8//el23ls9TMUfJchyUEkzTgKUPAdGjJNtBTaCKMI13epb29gR2YnXg+rSIiPLkliEEIcNo3b932yZmLtpJLXCVyXIAoJjI5fabFYAkVVJYlBCCGEEEIMeGPHji3a3rBhQ5dS9/tyyy23sHbt2v4IS5RoyJAhnHXWWUVjv/3tb3nmmWcOOPfll1/mtttu66/QuujJhf4PymQyvPfee0VjRx11VLf7XnHFFUVJHY7jcO2119LS0tKrY3fni1/8YtF2oVDgBz/4Ab7vH3Buc3MzP/7xj4vG0uk05513Xp/Ftz9XXHEFsdj//p3qeR5XXXXVQb0+u3bt6ovQhBBCCCHEAKCrGmVWkiGpGkamhzE4OYiklURVNDRFJWHEqI6lOSpZQ3WsgoQRQ1NUwigi5xVozrdS395IU7aZjJvDD7u/ifR9iqIwKj2c+dPP54a5X+eUkXOw9lSEKIUbuLy8ZRkLFt/B/W/+N7tyuxkUr+qsKpFxc+zI7CTj5ogiyLk5trTWsyu3mzA8cLKF+GiTJAYhxGGTtstQwq5ljoY3BZQPHlbyOpHj4EQ+mmFgqjpmLIGqqJ0flEIIIYQQQgxUU6ZMoaKiomjs29/+NvX19fucUygU+NGPfsTvfve7/g5PlOA73/lOURsF3/e55ppruO2227q0C4GOChp33nkn3/jGN3Bdl2Qy2e+tDAAWLFjAeeedxyOPPEJbW1tJcxzH4bvf/W5RyxJd1znllFO63X/EiBFceeWVRWOrV6/m7//+77skQuzL6tWruf7662lubu728bFjx3ap+LB48WKuu+46MpnMPtfdtm0bl19+Odu2bSsav/rqq7Ftu6TYDlZ1dTXXXHNN0diGDRu44IILWLp0acnrZDIZHn30US644AJ+/etf93WYQgghhBBiAFAVlYQZpyZRxcj0MIamBlNul6GrOqqiYBsWFbFyjkrVMChRRcpMoqs6EVAIXFoKbezI7KQx00SbkzlgBYSKWDmfGH8G3z/lKs6bcBZVsdLafQNEwHs713Hnsv/iP16/n00tW0jbKQxVJ4xCWgptNGSbKPgOENFaaKOudTttTqbkVhjio6dnzTaFEKIPjTpmBrOfjbGk5n97IWlBxKmxcShKaaWLwiAg9AMcfBTDxlYtVNvaU26p9PJHQgghhBBCHA6qqnLZZZdx6623do5t2bKFT3/601xyySWcccYZDB8+HN/3aWho4KWXXuLBBx/svBBrGAYf+9jH+Otf/3q4nsJH3rBhw7jxxhv5/ve/3znmeR6//OUvufvuuzn++OMZOnQoiqJQX1/Pq6++WpQU8N3vfpebbrqJINj/XVJ9Yc2aNdx444386Ec/4vjjj2f27NlMmjSJkSNHUlZWhmVZ5HI56urqWLJkCQ8//HCXi/4XXXQRVVVV+zzGN7/5TVasWMGSJUs6xzZs2MD555/PWWedxVlnncXUqVOpqqpC0zRaW1vZuHEjK1eu5JlnnuHdd98FOpJD9uUHP/gBS5cuLYrtySef5I033mD+/PnMmzePIUOGEAQBW7Zs4amnnuK//uu/yOVyRevMnTuXL33pSz16DQ/WZZddxrvvvsuf//znzrFt27Yxf/58Zs2axcc+9jFmzJhBTU0NqVSKfD5PW1sbdXV1rFq1imXLlvHKK6/gui4Axx133CGNXwghhBBCHHqKomAbNrZhUxWvwPVdcl6erJfH8R0szcDSDMpJ4oc+ed+h4BVwAg839HGdDG1OBl1RsQ2bmG5hama311As3eLk2lmcOGImq3auZ1Hd62zYXVdyrPWZRv7wzhMkzTjHD5/BtMHHEEQBfujTlNuNrVuU2ykMFZqyu2grtFMVryBmHJrEYnHkkCQGIcRhoygKV33h/yP9m/+feqUdNYwYrlRSfdKEkteIXI8oivA00PdkH6qGKa0khBBCCCHEEeOyyy7j6aef5u233+4ca21t5Ze//CW//OUv9zv3pptuoqmpSZIYDrMLL7yQbDbLv/zLvxSN53I5nn/++X3Ou/zyy/nsZz/Lj370o6Jx0zT7Jc73eZ7HokWLWLRoUY/mTZ06lRtuuGG/+2iaxu233843v/lNFi9e3DkeRRFPP/00Tz/9dK9i/qBkMsmdd97JFVdcUVS1ZMeOHSxYsIAFCxYccI0ZM2awYMGCw5L8/uMf/xjbtnnooYeKxpcuXdqjigxCCCGEEOKjydRNTN0kHSvHDwNybo6clyfnFdBVnZSpkzITBFHYkdDgOzi+gx+FZNwcGTfXUc1Bt7B1G1s3UZXi4v2qojKpZhyTasaxvb2BxXVLeaP+XYKohalb4QAAIABJREFUtOTrjJvj2Q2LeWHjqxw7ZBLHHnUMcSNOwXcoZBySZpyUlcQNXOrbG4ibcapiaQzN6I+XTByBpJ2EEOKwMspSDJ9+MsceczojR04nHDoYenASKXAcXHwUQ0dXNKx4AkVBsvaEEEIIIcQRw7Zt/uM//oMpU6b0aM4tt9zCBRdc0I+RiZ645JJL+M1vfsPw4cMPuG8ymeSmm27iO9/5Dp7n4Xlel8f7mmEc3MnAT37yk9x3330kEokD7ptKpfjNb37DlVde2auEDFVVD9hiY8yYMTz44IPMmjWrR2srisJnPvMZ7r33XtLp0kvk9iXTNLnpppv413/9VwYNGtTrdSoqKpg8eXIfRiaEEEIIIY40uqpRZqcYkqphVHo4NclqkmZHy21NUUkaMapjaY5K1lAVSxM3YqiKShhF5LwCzfkW6tsbacrtJuPmCMKuSQpDU4P57ORP8N1TvsGZo08mYcS7iaR7QRSwrP4t7l7+MI+veY5tbfVEUUTGzdGQ2UnGzRJFkHNzbGmtZ1duN2EY9uVLJI5QUolBCHHEioDI83AiH9WIYWkGmmVj6xaa2v89ZYUQQgghhOgrNTU1/P73v+e3v/0t9913H83Nzd3uZ9s25557LldffTUjRow4xFGKAzn11FN5/PHHefbZZ1m4cCGrV6+msbERz/NIp9NMmDCBU045hfPPP5/y8nKgo+rG3vojieHmm2/m4osv5sUXX2TJkiW8++67OI6z3znxeJwzzzyTL3zhC8ycObNHx9N1nW9/+9vMnz+fO++8k+eee44dO3bsd8748eM588wzueiii6isrDzgMYYMGcIDDzzAM888w3333cfy5cvxfX+fz+Wkk07i61//OlOnTu3Rc+kv559/Ph//+Md55JFH+Mtf/sI777yzz/jfN2zYME466SROO+00Tj311INOThFCCCGEEB8eqqqSNBMkzQRRFFHwHbJejpybxw99YobdeQOo47udbSf8KOiokOA7tACmZhDTLWzdKqqMkLKS/N2YUzht1Im8ueNdFtW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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "train_scores_mean = np.mean(train_scores, axis=1)\n", "train_scores_std = np.std(train_scores, axis=1)\n", "test_scores_mean = np.mean(test_scores, axis=1)\n", "test_scores_std = np.std(test_scores, axis=1)\n", "\n", "mpl.rcParams[\"font.family\"] = 'DejaVu Sans'\n", "plt.semilogx(param_range, train_scores_mean, label=\"Training score\", color=\"r\")\n", "plt.fill_between(param_range, train_scores_mean - train_scores_std,\n", " train_scores_mean + train_scores_std, alpha=0.2, color=\"r\")\n", "plt.semilogx(param_range, test_scores_mean,\n", " label=\"Cross-validation score\", color=\"g\")\n", "plt.fill_between(param_range, test_scores_mean - test_scores_std,\n", " test_scores_mean + test_scores_std, alpha=0.2, color=\"g\")\n", "plt.legend(loc=\"best\")\n", "plt.title(\"Validation Curve with SVM\")\n", "plt.xlabel(\"$\\gamma$\")\n", "plt.ylabel(\"Score\")\n", "plt.ylim(0.0, 1.1)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "school_cell_uuid": "700b3f8cb09b4dfd8e8adfcf332baa4e" }, "source": [ "## `GridSearchCV` " ] }, { "cell_type": "markdown", "metadata": { "school_cell_uuid": "8c933c8e35424d7aabfbe7120117771b" }, "source": [ "`GridSearchCV` 클래스는 `validation_curve` 함수와 달리 모형 래퍼(Wrapper) 성격의 클래스이다. 클래스 객체에 `fit` 메서드를 호출하면 grid search를 사용하여 자동으로 복수개의 내부 모형을 생성하고 이를 모두 실행시켜서 최적 파라미터를 찾아준다. 생성된 복수개와 내부 모형과 실행 결과는 다음 속성에 저장된다.\n", "\n", "* `grid_scores_ `\n", " * param_grid 의 모든 파리미터 조합에 대한 성능 결과. 각각의 원소는 다음 요소로 이루어진 튜플이다.\n", " * parameters: 사용된 파라미터\n", " * mean_validation_score: 교차 검증(cross-validation) 결과의 평균값\n", " * cv_validation_scores: 모든 교차 검증(cross-validation) 결과\n", "* `best_score_` \n", " * 최고 점수 \n", "* `best_params_`\n", " * 최고 점수를 낸 파라미터\n", "* `best_estimator_`\n", " * 최고 점수를 낸 파라미터를 가진 모형" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "school_cell_uuid": "2b2dde7edf34472c816d7e463aaec718" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 9min 58s, sys: 16.2 s, total: 10min 15s\n", "Wall time: 4min 13s\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/home/dockeruser/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:813: DeprecationWarning: The default of the `iid` parameter will change from True to False in version 0.22 and will be removed in 0.24. This will change numeric results when test-set sizes are unequal.\n", " DeprecationWarning)\n" ] } ], "source": [ "from sklearn.model_selection import GridSearchCV\n", "from sklearn.pipeline import Pipeline\n", "from sklearn.preprocessing import StandardScaler\n", "from sklearn.svm import SVC\n", "\n", "pipe_svc = Pipeline([('scl', StandardScaler()), ('clf', SVC(random_state=1))])\n", "\n", "param_range = [0.0001, 0.001, 0.01, 0.1, 1.0, 10.0, 100.0, 1000.0]\n", "param_grid = [\n", " {'clf__C': param_range, 'clf__kernel': ['linear']},\n", " {'clf__C': param_range, 'clf__gamma': param_range, 'clf__kernel': ['rbf']}]\n", "\n", "gs = GridSearchCV(estimator=pipe_svc, param_grid=param_grid,\n", " scoring='accuracy', cv=10, n_jobs=1)\n", "%time gs = gs.fit(X, y)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "school_cell_uuid": "6402c33eb53444ea896fac8b44127511" }, "outputs": [ { "data": { "text/plain": [ "[{'clf__C': 0.0001, 'clf__kernel': 'linear'},\n", " {'clf__C': 0.001, 'clf__kernel': 'linear'},\n", " {'clf__C': 0.01, 'clf__kernel': 'linear'},\n", " {'clf__C': 0.1, 'clf__kernel': 'linear'},\n", " {'clf__C': 1.0, 'clf__kernel': 'linear'},\n", " {'clf__C': 10.0, 'clf__kernel': 'linear'},\n", " {'clf__C': 100.0, 'clf__kernel': 'linear'},\n", " {'clf__C': 1000.0, 'clf__kernel': 'linear'},\n", " {'clf__C': 0.0001, 'clf__gamma': 0.0001, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.0001, 'clf__gamma': 0.001, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.0001, 'clf__gamma': 0.01, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.0001, 'clf__gamma': 0.1, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.0001, 'clf__gamma': 1.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.0001, 'clf__gamma': 10.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.0001, 'clf__gamma': 100.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.0001, 'clf__gamma': 1000.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.001, 'clf__gamma': 0.0001, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.001, 'clf__gamma': 0.001, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.001, 'clf__gamma': 0.01, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.001, 'clf__gamma': 0.1, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.001, 'clf__gamma': 1.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.001, 'clf__gamma': 10.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.001, 'clf__gamma': 100.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.001, 'clf__gamma': 1000.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.01, 'clf__gamma': 0.0001, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.01, 'clf__gamma': 0.001, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.01, 'clf__gamma': 0.01, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.01, 'clf__gamma': 0.1, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.01, 'clf__gamma': 1.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.01, 'clf__gamma': 10.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.01, 'clf__gamma': 100.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.01, 'clf__gamma': 1000.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.1, 'clf__gamma': 0.0001, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.1, 'clf__gamma': 0.001, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.1, 'clf__gamma': 0.01, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.1, 'clf__gamma': 0.1, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.1, 'clf__gamma': 1.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.1, 'clf__gamma': 10.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.1, 'clf__gamma': 100.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 0.1, 'clf__gamma': 1000.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 1.0, 'clf__gamma': 0.0001, 'clf__kernel': 'rbf'},\n", " {'clf__C': 1.0, 'clf__gamma': 0.001, 'clf__kernel': 'rbf'},\n", " {'clf__C': 1.0, 'clf__gamma': 0.01, 'clf__kernel': 'rbf'},\n", " {'clf__C': 1.0, 'clf__gamma': 0.1, 'clf__kernel': 'rbf'},\n", " {'clf__C': 1.0, 'clf__gamma': 1.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 1.0, 'clf__gamma': 10.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 1.0, 'clf__gamma': 100.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 1.0, 'clf__gamma': 1000.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 10.0, 'clf__gamma': 0.0001, 'clf__kernel': 'rbf'},\n", " {'clf__C': 10.0, 'clf__gamma': 0.001, 'clf__kernel': 'rbf'},\n", " {'clf__C': 10.0, 'clf__gamma': 0.01, 'clf__kernel': 'rbf'},\n", " {'clf__C': 10.0, 'clf__gamma': 0.1, 'clf__kernel': 'rbf'},\n", " {'clf__C': 10.0, 'clf__gamma': 1.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 10.0, 'clf__gamma': 10.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 10.0, 'clf__gamma': 100.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 10.0, 'clf__gamma': 1000.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 100.0, 'clf__gamma': 0.0001, 'clf__kernel': 'rbf'},\n", " {'clf__C': 100.0, 'clf__gamma': 0.001, 'clf__kernel': 'rbf'},\n", " {'clf__C': 100.0, 'clf__gamma': 0.01, 'clf__kernel': 'rbf'},\n", " {'clf__C': 100.0, 'clf__gamma': 0.1, 'clf__kernel': 'rbf'},\n", " {'clf__C': 100.0, 'clf__gamma': 1.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 100.0, 'clf__gamma': 10.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 100.0, 'clf__gamma': 100.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 100.0, 'clf__gamma': 1000.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 1000.0, 'clf__gamma': 0.0001, 'clf__kernel': 'rbf'},\n", " {'clf__C': 1000.0, 'clf__gamma': 0.001, 'clf__kernel': 'rbf'},\n", " {'clf__C': 1000.0, 'clf__gamma': 0.01, 'clf__kernel': 'rbf'},\n", " {'clf__C': 1000.0, 'clf__gamma': 0.1, 'clf__kernel': 'rbf'},\n", " {'clf__C': 1000.0, 'clf__gamma': 1.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 1000.0, 'clf__gamma': 10.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 1000.0, 'clf__gamma': 100.0, 'clf__kernel': 'rbf'},\n", " {'clf__C': 1000.0, 'clf__gamma': 1000.0, 'clf__kernel': 'rbf'}]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "gs.cv_results_[\"params\"]" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "school_cell_uuid": "84216f9849b54a63a35abecf7090a493" }, "outputs": [ { "data": { "text/plain": [ "array([0.20868114, 0.91819699, 0.95269894, 0.95826377, 0.95826377,\n", " 0.95826377, 0.95826377, 0.95826377, 0.11908737, 0.12020033,\n", " 0.1213133 , 0.10350584, 0.10127991, 0.11185309, 0.10183639,\n", " 0.10127991, 0.11908737, 0.12020033, 0.1213133 , 0.10350584,\n", " 0.10127991, 0.11185309, 0.10183639, 0.10127991, 0.11908737,\n", " 0.12020033, 0.13967724, 0.10350584, 0.10127991, 0.11185309,\n", " 0.10183639, 0.10127991, 0.11908737, 0.68614357, 0.91207568,\n", " 0.40567613, 0.10127991, 0.11185309, 0.10183639, 0.10127991,\n", " 0.70339455, 0.93266555, 0.9638286 , 0.90984975, 0.11908737,\n", " 0.10127991, 0.10127991, 0.10127991, 0.934335 , 0.95659432,\n", " 0.97161937, 0.9115192 , 0.12966055, 0.10127991, 0.10127991,\n", " 0.10127991, 0.95548136, 0.96160267, 0.97161937, 0.9115192 ,\n", " 0.12966055, 0.10127991, 0.10127991, 0.10127991, 0.95993322,\n", " 0.96215915, 0.97161937, 0.9115192 , 0.12966055, 0.10127991,\n", " 0.10127991, 0.10127991])" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "gs.cv_results_[\"mean_test_score\"]" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "school_cell_uuid": "a962063a593d436aa4f662b0844100ef" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.9716193656093489\n", "{'clf__C': 10.0, 'clf__gamma': 0.01, 'clf__kernel': 'rbf'}\n" ] } ], "source": [ "print(gs.best_score_)\n", "print(gs.best_params_)" ] }, { "cell_type": "markdown", "metadata": { "school_cell_uuid": "b2d7c60bbb2640d2950667c5aa7652d0" }, "source": [ "## `ParameterGrid` " ] }, { "cell_type": "markdown", "metadata": { "collapsed": true, "school_cell_uuid": "e309a8580715444a9136eed33e850c54" }, "source": [ "때로는 scikit-learn 이 제공하는 GridSearchCV 이외의 방법으로 그리드 탐색을 해야하는 경우도 있다. 이 경우 파라미터를 조합하여 탐색 그리드를 생성해 주는 명령어가 `ParameterGrid` 이다. `ParameterGrid` 는 탐색을 위한 iterator 역할을 한다." ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "school_cell_uuid": "e19d25d2ec2c4cfba41b54c417278d58" }, "outputs": [], "source": [ "from sklearn.model_selection import ParameterGrid" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "school_cell_uuid": "a0cbec4b337f488bb1aa7c572fe70d43" }, "outputs": [ { "data": { "text/plain": [ "[{'a': 1, 'b': True},\n", " {'a': 1, 'b': False},\n", " {'a': 2, 'b': True},\n", " {'a': 2, 'b': False}]" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "param_grid = {'a': [1, 2], 'b': [True, False]}\n", "list(ParameterGrid(param_grid))" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "school_cell_uuid": "29c941318d43480dab325091261398fe" }, "outputs": [ { "data": { "text/plain": [ "[{'kernel': 'linear'},\n", " {'gamma': 1, 'kernel': 'rbf'},\n", " {'gamma': 10, 'kernel': 'rbf'}]" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "param_grid = [{'kernel': ['linear']}, {'kernel': ['rbf'], 'gamma': [1, 10]}]\n", "list(ParameterGrid(param_grid))" ] }, { "cell_type": "markdown", "metadata": { "school_cell_uuid": "d279553f4b4b473bac40e1b1ce0bb528" }, "source": [ "## 병렬 처리" ] }, { "cell_type": "markdown", "metadata": { "school_cell_uuid": "201719a4d29e4fe59323f9b250aef480" }, "source": [ "`GridSearchCV` 명령에는 `n_jobs` 라는 인수가 있다. 디폴트 값은 1인데 이 값을 증가시키면 내부적으로 멀티 프로세스를 사용하여 그리드서치를 수행한다. 만약 CPU 코어의 수가 충분하다면 `n_jobs`를 늘릴 수록 속도가 증가한다." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "school_cell_uuid": "ae206bf4356b40208f712bea425eac11" }, "outputs": [], "source": [ "param_grid = {\"gamma\": np.logspace(-6, -1, 10)}\n", "gs1 = GridSearchCV(estimator=SVC(), param_grid=param_grid,\n", " scoring='accuracy', cv=5, n_jobs=1)\n", "gs2 = GridSearchCV(estimator=SVC(), param_grid=param_grid,\n", " scoring='accuracy', cv=5, n_jobs=2)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "school_cell_uuid": "aae29beadc59428791efef7ab4e18e0c" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 13.6 s, sys: 410 ms, total: 14 s\n", "Wall time: 14.1 s\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/home/dockeruser/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:813: DeprecationWarning: The default of the `iid` parameter will change from True to False in version 0.22 and will be removed in 0.24. This will change numeric results when test-set sizes are unequal.\n", " DeprecationWarning)\n" ] }, { "data": { "text/plain": [ "GridSearchCV(cv=5, error_score='raise-deprecating',\n", " estimator=SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n", " decision_function_shape='ovr', degree=3,\n", " gamma='auto_deprecated', kernel='rbf', max_iter=-1,\n", " probability=False, random_state=None, shrinking=True,\n", " tol=0.001, verbose=False),\n", " iid='warn', n_jobs=1,\n", " param_grid={'gamma': array([1.00000000e-06, 3.59381366e-06, 1.29154967e-05, 4.64158883e-05,\n", " 1.66810054e-04, 5.99484250e-04, 2.15443469e-03, 7.74263683e-03,\n", " 2.78255940e-02, 1.00000000e-01])},\n", " pre_dispatch='2*n_jobs', refit=True, return_train_score=False,\n", " scoring='accuracy', verbose=0)" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time\n", "gs1.fit(X, y)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "school_cell_uuid": "f7a1ec6798d743f1a8c394e1ad330101" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 240 ms, sys: 120 ms, total: 360 ms\n", "Wall time: 8.45 s\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/home/dockeruser/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py:813: DeprecationWarning: The default of the `iid` parameter will change from True to False in version 0.22 and will be removed in 0.24. This will change numeric results when test-set sizes are unequal.\n", " DeprecationWarning)\n" ] }, { "data": { "text/plain": [ "GridSearchCV(cv=5, error_score='raise-deprecating',\n", " estimator=SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n", " decision_function_shape='ovr', degree=3,\n", " gamma='auto_deprecated', kernel='rbf', max_iter=-1,\n", " probability=False, random_state=None, shrinking=True,\n", " tol=0.001, verbose=False),\n", " iid='warn', n_jobs=2,\n", " param_grid={'gamma': array([1.00000000e-06, 3.59381366e-06, 1.29154967e-05, 4.64158883e-05,\n", " 1.66810054e-04, 5.99484250e-04, 2.15443469e-03, 7.74263683e-03,\n", " 2.78255940e-02, 1.00000000e-01])},\n", " pre_dispatch='2*n_jobs', refit=True, return_train_score=False,\n", " scoring='accuracy', verbose=0)" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time\n", "gs2.fit(X, y)" ] }, { "cell_type": "markdown", "metadata": { "school_cell_uuid": "68be21ea8e1d456cac6176a346927692" }, "source": [ "실제 하드웨어의 코어 수가 부족하다면 병렬로 실행되지 않으므로 실행시간이 단축되지 않는다." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.0" } }, "nbformat": 4, "nbformat_minor": 1 }