{ "metadata": { "name": "" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "#Bias, Variance, and Cross Validation\n", "\n", "In the last lab, and in homework 2, we alluded to cross-validation with a weak explanation about finding the right hyper-parameters, some of which were regularization parameters. We will have more to say about regularization soon, but lets tackle the reasons we do cross-validation.\n", "\n", "The bottom line is: finding the model which has an appropriate mix of bias and variance. We usually want to sit at the point of the tradeoff between the two: be simple but no simpler than necessary.\n", "\n", "We do not want a model with too much variance: it would not generalize well. This phenomenon is also called *overfitting*. There is no point doing prediction if we cant generalize well. At the same time, if we have too much bias in our model, we will systematically underpredict or overpredict values and miss most predictions. This is also known as *underfitting*.\n", "\n", "Cross-Validation provides us a way to find the \"hyperparameters\" of our model, such that we achieve the balance point.\n", "\n", "Read http://scott.fortmann-roe.com/docs/BiasVariance.html" ] }, { "cell_type": "code", "collapsed": false, "input": [ "%matplotlib inline\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "import brewer2mpl\n", "from matplotlib import rcParams\n", "\n", "#colorbrewer2 Dark2 qualitative color table\n", "dark2_cmap = brewer2mpl.get_map('Dark2', 'Qualitative', 7)\n", "dark2_colors = dark2_cmap.mpl_colors\n", "\n", "rcParams['figure.figsize'] = (10, 6)\n", "rcParams['figure.dpi'] = 150\n", "rcParams['axes.color_cycle'] = dark2_colors\n", "rcParams['lines.linewidth'] = 2\n", "rcParams['axes.facecolor'] = 'white'\n", "rcParams['font.size'] = 14\n", "rcParams['patch.edgecolor'] = 'white'\n", "rcParams['patch.facecolor'] = dark2_colors[0]\n", "rcParams['font.family'] = 'StixGeneral'\n", "\n", "\n", "def remove_border(axes=None, top=False, right=False, left=True, bottom=True):\n", " \"\"\"\n", " Minimize chartjunk by stripping out unnecesasry plot borders and axis ticks\n", " \n", " The top/right/left/bottom keywords toggle whether the corresponding plot border is drawn\n", " \"\"\"\n", " ax = axes or plt.gca()\n", " ax.spines['top'].set_visible(top)\n", " ax.spines['right'].set_visible(right)\n", " ax.spines['left'].set_visible(left)\n", " ax.spines['bottom'].set_visible(bottom)\n", " \n", " #turn off all ticks\n", " ax.yaxis.set_ticks_position('none')\n", " ax.xaxis.set_ticks_position('none')\n", " \n", " #now re-enable visibles\n", " if top:\n", " ax.xaxis.tick_top()\n", " if bottom:\n", " ax.xaxis.tick_bottom()\n", " if left:\n", " ax.yaxis.tick_left()\n", " if right:\n", " ax.yaxis.tick_right()\n", " \n", "pd.set_option('display.width', 500)\n", "pd.set_option('display.max_columns', 100)\n", "import warnings\n", "warnings.filterwarnings('ignore', message='Polyfit*')" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 1 }, { "cell_type": "code", "collapsed": false, "input": [ "import random\n", "import copy\n", "def scatter_by(df, scatterx, scattery, by=None, figure=None, axes=None, colorscale=dark2_cmap, labeler={}, mfunc=None, setupfunc=None, mms=8):\n", " cs=copy.deepcopy(colorscale.mpl_colors)\n", " if not figure:\n", " figure=plt.figure(figsize=(8,8))\n", " if not axes:\n", " axes=figure.gca()\n", " x=df[scatterx]\n", " y=df[scattery]\n", " if not by:\n", " col=random.choice(cs)\n", " axes.scatter(x, y, cmap=colorscale, c=col)\n", " if setupfunc:\n", " axeslist=setupfunc(axes, figure)\n", " else:\n", " axeslist=[axes]\n", " if mfunc:\n", " mfunc(axeslist,x,y,color=col, mms=mms)\n", " else:\n", " cs=list(np.linspace(0,1,len(df.groupby(by))))\n", " xlimsd={}\n", " ylimsd={}\n", " xs={}\n", " ys={}\n", " cold={}\n", " for k,g in df.groupby(by):\n", " col=cs.pop()\n", " x=g[scatterx]\n", " y=g[scattery]\n", " xs[k]=x\n", " ys[k]=y\n", " c=colorscale.mpl_colormap(col)\n", " cold[k]=c\n", " axes.scatter(x, y, c=c, label=labeler.get(k,k), s=40, alpha=0.3);\n", " xlimsd[k]=axes.get_xlim()\n", " ylimsd[k]=axes.get_ylim()\n", " xlims=[min([xlimsd[k][0] for k in xlimsd.keys()]), max([xlimsd[k][1] for k in xlimsd.keys()])]\n", " ylims=[min([ylimsd[k][0] for k in ylimsd.keys()]), max([ylimsd[k][1] for k in ylimsd.keys()])]\n", " axes.set_xlim(xlims)\n", " axes.set_ylim(ylims)\n", " if setupfunc:\n", " axeslist=setupfunc(axes, figure)\n", " else:\n", " axeslist=[axes]\n", " if mfunc:\n", " for k in xs.keys():\n", " mfunc(axeslist,xs[k],ys[k],color=cold[k], mms=mms);\n", " axes.set_xlabel(scatterx);\n", " axes.set_ylabel(scattery);\n", " \n", " return axes\n", "\n", "def make_rug(axeslist, x, y, color='b', mms=8):\n", " axes=axeslist[0]\n", " zerosx1=np.zeros(len(x))\n", " zerosx2=np.zeros(len(x))\n", " xlims=axes.get_xlim()\n", " ylims=axes.get_ylim()\n", " zerosx1.fill(ylims[1])\n", " zerosx2.fill(xlims[1])\n", " axes.plot(x, zerosx1, marker='|', color=color, ms=mms)\n", " axes.plot(zerosx2, y, marker='_', color=color, ms=mms)\n", " axes.set_xlim(xlims)\n", " axes.set_ylim(ylims)\n", " return axes" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 2 }, { "cell_type": "markdown", "metadata": {}, "source": [ "In any learning problem, or goal is **to minimize the prediction error on the test set**. This prediction error could be a root mean square error, or a 1-0 loss function, or a log likelyhood, or something else." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##Polynomial regression\n", "\n", "This part of the lab is partly taken from\n", "\n", "http://raw.github.com/jakevdp/sklearn_pycon2013/master/notebooks/09_validation_and_testing.ipynb. Images are taken from Andrew Ng's Coursera course, on which the above notebook is based." ] }, { "cell_type": "code", "collapsed": false, "input": [ "np.random.seed(42)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 3 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Consider the model selection problem: what degree of polynomial you want to fit: d. It acts like a hyperparameter, in the sense that it is a second parameter that needs to be fit for. Once you set it, you still have to fit the parameters of your linear or polynomial or elsewise model." ] }, { "cell_type": "code", "collapsed": false, "input": [ "def rmse(p,x,y):\n", " yfit = np.polyval(p, x)\n", " return np.sqrt(np.mean((y - yfit) ** 2))\n", "\n", "def generate_curve(x, sigma):\n", " return np.random.normal(10 - 1. / (x + 0.1), sigma)\n", "x = 10 ** np.linspace(-2, 0, 8)\n", "intrinsic_error=1.\n", "y=generate_curve(x, intrinsic_error)\n", "plt.scatter(x,y)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 4, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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"text": [ "" ] } ], "prompt_number": 4 }, { "cell_type": "markdown", "metadata": {}, "source": [ "A high bias situation is one in which we underfit. Notice how for low d, the rmse on the training set remains high. A high variance situation is one in which we overfit. We want to be just right. As we get to the limit of being able to interpolate the points, the rmse training error goes to nil." ] }, { "cell_type": "code", "collapsed": false, "input": [ "x_new=np.linspace(-0.2, 1.2, 1000)\n", "plt.scatter(x,y, s=50)\n", "f1=np.polyfit(x,y,1)\n", "plt.plot(x_new,np.polyval(f1,x_new))\n", "print \"d=1, rmse=\",rmse(f1,x,y)\n", "f2=np.polyfit(x,y,2)\n", "plt.plot(x_new,np.polyval(f2,x_new))\n", "print \"d=2, rmse=\",rmse(f2,x,y)\n", "f4=np.polyfit(x,y,4)\n", "plt.plot(x_new,np.polyval(f4,x_new))\n", "print \"d=4, rmse=\",rmse(f4,x,y)\n", "f6=np.polyfit(x,y,6)\n", "plt.plot(x_new,np.polyval(f6,x_new))\n", "print \"d=6, rmse=\",rmse(f6,x,y)\n", "plt.xlim(-0.2, 1.2)\n", "plt.ylim(-1, 12)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "d=1, rmse= 1.70524942832\n", "d=2, rmse= 0.89214139212\n", "d=4, rmse= 0.496552676012\n", "d=6, rmse= 0.132980700607\n" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 5, "text": [ "(-1, 12)" ] }, { "metadata": {}, "output_type": "display_data", "png": 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fc/Ufn7A2+wghfnqm9BnBuhuf4e5LLm8ywdKZqIMiiLrxP7SddpTwsc8i6QKp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K08eL+glQq4Re0S13WpFa1gXYJiEZa6/qyX0j6y7S6trHVR0KLcIqJWEFQuJSrQAAm5EXJPJsnM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\nNp1n5VXzAAAAAABJRU5ErkJggg==\n", "text": [ "" ] } ], "prompt_number": 5 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The curves start taking on all kinds of wiggles so as to be able to fit themselves in." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Constructing a data set" ] }, { "cell_type": "code", "collapsed": false, "input": [ "N = 200\n", "x = np.random.random(N)\n", "y = generate_curve(x, intrinsic_error)\n", "plt.scatter(x,y)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 6, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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547SCZcuca15iYuT2+Hil2raV29q1U2rtWqkXqsg99zifb+1a18d0+rTzeT75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\ngg==\n", "text": [ "" ] } ], "prompt_number": 6 }, { "cell_type": "code", "collapsed": false, "input": [ "from sklearn.cross_validation import train_test_split\n", "xtrain, xtest, ytrain, ytest = train_test_split(x, y, train_size=0.6)\n", "plt.scatter(xtrain, ytrain, color='red')\n", "plt.scatter(xtest, ytest, color='blue')" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 7, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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GZWXJD3jlyvJx//3KrblY0oU5V0S+bvdupWrVsv2H3LatUikp6vBhpW65RXK1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\nU4jLpaYqNXmyUi+8IEvLnHn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3HwBcuKBZOXjsmPS3Ll4EqleXPlr58nbnWywy9fjpp8Ch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\nERG50f8A1StZe5KZMFYAAAAASUVORK5CYII=\n", "text": [ "" ] } ], "prompt_number": 7 }, { "cell_type": "code", "collapsed": false, "input": [ "ds = np.arange(21)\n", "train_err = np.zeros(len(ds))\n", "test_err = np.zeros(len(ds))\n", "\n", "for i, d in enumerate(ds):\n", " p = np.polyfit(xtrain, ytrain, d)\n", "\n", " train_err[i] = rmse(p, xtrain, ytrain)\n", " test_err[i] = rmse(p, xtest, ytest)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 8 }, { "cell_type": "code", "collapsed": false, "input": [ "fig, ax = plt.subplots()\n", "\n", "ax.plot(ds, test_err, lw=2, label = 'test error')\n", "ax.plot(ds, train_err, lw=2, label = 'training error')\n", "ax.legend(loc=0)\n", "ax.set_xlabel('degree of fit')\n", "ax.set_ylabel('rms error')" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 9, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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Vq1Cr1diyZQs6dOiAt956C1988QV8fHwwduxYjBo1CpMmTUK/fv3Qr18/3HfffQgJCcFf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\n6p80aVKN5ZCQEISHhzspGnlZ+8gOrK+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"text": [ "" ] } ], "prompt_number": 9 }, { "cell_type": "markdown", "metadata": {}, "source": [ "How to tell that a hypothesis is overfitting? Its not enough that the training error is low, though thats certainly an indication.\n", "\n", "The training error is low but test error is high!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If we plot training error against, say, d, the training error will decrease with increasing d. But for the cross-validation (or for that matter, test error), we'll have an error curve which has a minumum and goes up again.\n", "\n", "![polynomial regression](files/data/bias-variance-error.png)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We use the word test and cv interchangeably here, but they really are not, as will be clear soon." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "###Learning Curves\n", "\n", "Here we plot the train vs cv/test error as a function of the size of the training set.\n", "\n", "The training set error increases as size of the data set increases. The intuition is that with more samples, you get further away from the interpolation limit. The cross validation error on the otherhand will decrease as **training set** size increases, as , more\n", "data you have better the hypothesis you fit.\n", "\n", "**High Bias**\n", "\n", "Now consider the high bias situation. The training error will increase as before, to a point, and then flatten out. (There is only so much you can do to make a straight line fit a quadratic curve). The cv/test error, on the other hand will decrease, but then, it too will flatten out. These will be very close to each other, and after a point, getting more training data will not help!\n", "\n", "![Learning Curve under high bias situation](files/data/lc-hb.png)\n" ] }, { "cell_type": "code", "collapsed": false, "input": [ "#taken lock stock and barrel from Vanderplas.\n", "def plot_learning_curve(d):\n", " sizes = np.linspace(2, N, 50).astype(int)\n", " train_err = np.zeros(sizes.shape)\n", " crossval_err = np.zeros(sizes.shape)\n", "\n", " for i, size in enumerate(sizes):\n", " # Train on only the first size points\n", " p = np.polyfit(xtrain[:size], ytrain[:size], d)\n", " \n", " # Validation error is on the *entire* validation set\n", " crossval_err[i] = rmse(p, xtest, ytest)\n", " \n", " # Training error is on only the points used for training\n", " train_err[i] = rmse(p, xtrain[:size], ytrain[:size])\n", "\n", " fig, ax = plt.subplots()\n", " ax.plot(sizes, crossval_err, lw=2, label='validation error')\n", " ax.plot(sizes, train_err, lw=2, label='training error')\n", " ax.plot([0, N], [intrinsic_error, intrinsic_error], '--k', label='intrinsic error')\n", "\n", " ax.set_xlabel('training set size')\n", " ax.set_ylabel('rms error')\n", " \n", " ax.legend(loc=0)\n", " \n", " ax.set_xlim(0, 99)\n", "\n", " ax.set_title('d = %i' % d)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 10 }, { "cell_type": "code", "collapsed": false, "input": [ "plot_learning_curve(d=1)\n", "plt.ylim(0, 10)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 11, "text": [ "(0, 10)" ] }, { "metadata": {}, "output_type": "display_data", "png": 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hYSFeeukl7NixAxUVFUhMTERCQgIA14cHSktL8dprr+HQoUP49NNP8cILL+C6665DZmYm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\n39TU9NAuSCCitsMii4hapVKp/u2XeVlZGebNm4fo6Gi4uLj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"text": [ "" ] } ], "prompt_number": 11 }, { "cell_type": "markdown", "metadata": {}, "source": [ "At the point of balance the learning curves come together and carry on, close to the intrinsic error." ] }, { "cell_type": "code", "collapsed": false, "input": [ "plot_learning_curve(d=5)\n", "plt.ylim(0, 10)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 12, "text": [ "(0, 10)" ] }, { "metadata": {}, "output_type": "display_data", "png": 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3o0+fPna95rrUQ3h1z3o8edc9+LDHULueu65tOH0YL+9ehydatsf8nsOcPRwi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\nSb4F5qQUvgWEQfEnaOPjPjQ27r/IwHtAg3BXnIJz39/g3Pc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"text": [ "" ] } ], "prompt_number": 12 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next consider the high variance situation. The training error will start out very low as usual, and go up slowly as even though we add points, we have enough wiggle room to start with, until it runs out and the error keeps increasing. The cv error, will, on the other hand, start out quite high, and remain high. Thus we will have a gap. In this case it will make sense to take more data, as that would drive the cv error down, and the training error up, until they meet.\n", "\n", "![Learning Curve under high variance situation](files/data/lc-hv.png)" ] }, { "cell_type": "code", "collapsed": false, "input": [ "plot_learning_curve(d=20)\n", "plt.ylim(0, 10)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 13, "text": [ "(0, 10)" ] }, { "metadata": {}, "output_type": "display_data", "png": 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3MWLECDzyyCM4duwYAODChQuYN28eevTogcTERISFhVWoGCUiIqo22Yn++OMP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\nQZJlWXbGjiZMmIC//voLv/32m3ls+PDhyM3NxZY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crcS4AAAAAElFTkSuQmCC\n", "text": [ "" ] } ], "prompt_number": 13 }, { "cell_type": "markdown", "metadata": {}, "source": [ "### K-Nearest Neighbors" ] }, { "cell_type": "code", "collapsed": false, "input": [ "df=pd.read_csv(\"data/olive.csv\")\n", "df.head(5)" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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2 3.North-Apulia 1 1 911 54 246 8113 549 31 63 29
3 4.North-Apulia 1 1 966 57 240 7952 619 50 78 35
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4 North-Apulia 1 1 10.51 0.67 2.59 77.71 6.72 0.50 0.80 0.46
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" ], "metadata": {}, "output_type": "pyout", "prompt_number": 16, "text": [ " areastring region area palmitic palmitoleic stearic oleic linoleic linolenic arachidic eicosenoic\n", "0 North-Apulia 1 1 10.75 0.75 2.26 78.23 6.72 0.36 0.60 0.29\n", "1 North-Apulia 1 1 10.88 0.73 2.24 77.09 7.81 0.31 0.61 0.29\n", "2 North-Apulia 1 1 9.11 0.54 2.46 81.13 5.49 0.31 0.63 0.29\n", "3 North-Apulia 1 1 9.66 0.57 2.40 79.52 6.19 0.50 0.78 0.35\n", "4 North-Apulia 1 1 10.51 0.67 2.59 77.71 6.72 0.50 0.80 0.46" ] } ], "prompt_number": 16 }, { "cell_type": "code", "collapsed": false, "input": [ "akeys=[1,2,3]\n", "avals=['North-Apulia','Calabria','South-Apulia']\n", "amap={e[0]:e[1] for e in zip(akeys,avals)}\n", "ax=scatter_by(dfsouthns, 'palmitic', 'palmitoleic', by='area', labeler=amap, mfunc=make_rug, mms=20)\n", "ax.grid(False)\n", "ax.legend(loc='upper right');" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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RTqd58MEHe71GbW0tNpst02dFUbI+f77vRW997b72okWLmDRpEjC6M/gl4AshxDCzu/yU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Qm4Cw5fENH0lTThp9NpZLNZhELF+0NCVGuOFfGxU1mYxybgAbAHE8iOpKF2hKGGvE6hGlWBNG1n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\nssGET0Vh2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"text": [ "" ] } ], "prompt_number": 17 }, { "cell_type": "code", "collapsed": false, "input": [ "from matplotlib.colors import ListedColormap\n", "#cm_bright = ListedColormap(['#FF0000', '#000000','#0000FF'])\n", "#cm = plt.cm.RdBu\n", "cmap_light = ListedColormap(['#FFAAAA', '#AAFFAA', '#AAAAFF'])\n", "cmap_bold = ListedColormap(['#FF0000', '#00FF00', '#0000FF'])\n", "\n", "def points_plot(X, Xtr, Xte, ytr, yte, clf, colorscale=cmap_light, cdiscrete=cmap_bold):\n", " h = .02\n", " x_min, x_max = X[:, 0].min() - .5, X[:, 0].max() + .5\n", " y_min, y_max = X[:, 1].min() - .5, X[:, 1].max() + .5\n", " xx, yy = np.meshgrid(np.linspace(x_min, x_max, 50),\n", " np.linspace(y_min, y_max, 50))\n", "\n", " plt.figure()\n", " Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])\n", " Z = Z.reshape(xx.shape)\n", " plt.pcolormesh(xx, yy, Z, cmap=cmap_light, alpha=0.2)\n", " plt.scatter(Xtr[:, 0], Xtr[:, 1], c=ytr-1, cmap=cdiscrete, s=50, alpha=0.2,edgecolor=\"k\")\n", " # and testing points\n", " yact=clf.predict(Xte)\n", " print \"SCORE\", clf.score(Xte, yte)\n", " plt.scatter(Xte[:, 0], Xte[:, 1], c=yte-1, cmap=cdiscrete, alpha=0.5, marker=\"s\", s=35)\n", " plt.xlim(xx.min(), xx.max())\n", " plt.ylim(yy.min(), yy.max())\n", " return ax\n" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 18 }, { "cell_type": "code", "collapsed": false, "input": [ "from sklearn.neighbors import KNeighborsClassifier\n", "subdf=dfsouthns[['palmitic','palmitoleic']]\n", "subdfstd=(subdf - subdf.mean())/subdf.std()\n", "X=subdfstd.values\n", "y=dfsouthns['area'].values\n", "Xtrain, Xtest, ytrain, ytest = train_test_split(X, y, train_size=0.6)\n", "Xtr=np.concatenate((Xtrain, Xtest))" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 19 }, { "cell_type": "markdown", "metadata": {}, "source": [ "We do kNN with 20 neighbors. kNN " ] }, { "cell_type": "code", "collapsed": false, "input": [ "clf = KNeighborsClassifier(20, warn_on_equidistant=False).fit(Xtrain, ytrain)\n", "points_plot(Xtr, Xtrain, Xtest, ytrain, ytest, clf)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "SCORE 0.930434782609\n" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 20, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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P/HyS+fmnyxWqVht88EGTZHIW33e5dm0D1y0yNeWhKFk6HZ/V1TpTU7mhLTWl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"text": [ "" ] } ], "prompt_number": 20 }, { "cell_type": "markdown", "metadata": {}, "source": [ "What if we decide to get ultra local. We get high variance and Jagged islands." ] }, { "cell_type": "code", "collapsed": false, "input": [ "#your code here\n", "clf = KNeighborsClassifier(1, warn_on_equidistant=False).fit(Xtrain, ytrain)\n", "points_plot(Xtr, Xtrain, Xtest, ytrain, ytest, clf)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "SCORE 0.913043478261\n" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 21, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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qq6tVLGsngLLt6sMKsN6WhB7Xrtcb3L1boNVSCQIbx6miabMUCgaqqpBOx7aX\nm0zzydfRyzXqus/4uL7dT2k3jqNuayhKuDt9MhneS9Pk4bYXDqVSE9cFXQ9Ip6NEIsYT73WhUGJ5\nuYrrqpimz8JCinQ62bPvIAhf3yCgzbeqQiIR4cGDMtFoelvH8zyqVZV43CeTMdmZaLJoNlViMbfr\n/nzDeK+urGyytuZQKinEYgEnTow/tarvRfnbPWzag/Txuc+9yec+9+b271evfrvrOFm2EwTh0HPs\n2BSmmWdlpYTrqhiGz+JilMXFZ8sVKpWqXLtWIxqdx/ddrl/P4bpZZmY8FCVJs+mzvl5hZiY1sKWm\nWEzDdR1gJ4E7CAIKhRLF4hqxWMDkZITJySz//J8rBAHUamHQ8oMf1Lh1y8TzkihKGLiur9doNFyg\n+7rd0tImS0smkcg8igKOA9eu5Tl9eoupqd7WIN97D/76r9ur/gD+6T+FuTmV8XGFV15p8vGPh9Np\ntVqDe/dgbKyBpmXbAusgiNFsNkkkEgybDz5YolqdIAgiKArU6wFXr65y5UqWWOyA1jmFQ8XAgyf/\n4V9D0Eu9rCAIwoCYmRlvy6V6nhL327eLRKNh9d76ehFFmSAS0alWy3iei6Lo+H6CarVOMjmY3kyz\ns2PcuLFOEMxRKlUol1ssLeUxzSSnT5/AcbLcvdtgY2OJS5fCBpW+D6ZpU6sFqGp71ZxhxNncLHDq\nVGcwEPbEcolE2iuko9Fx7t1bZnIyw+7NgPfC88L7vLvqbzcnT06jaRusrxfwPBPPK+O6HlNTZzpm\nJKGFYSQ7RQZMpVKlVEoSiUS2lxMVRSEanePOnWUuXZofugfh8DPQ4Glzc5M/+IM/QFEUvvGNbzA/\nP8+FCxcG+RSCIBwSolH4lV/pPL4PEwvPhed5NJvmdo5RtRpsd+I2jDiNRhPT1NE0jUbDJzmg73td\n1zl3Lsn3v/8jms0FajWfYtEinS4SBGGClWlGaTQmWV8vMDMTJjPlcmU0rftMkeMYOI7T0Y6gUqkS\nBN032nXdBI1Gg362P9qNbdtsbTWJRHyy2TTHjk2xuBj2k9L1cVR1qeOcIAhIJJpY1tP7XD0vGxsV\nIpHO3CqASkUS1oXeGHifp9/5nd/hd37ndwYpKwjCISQSYeib3A6DcBmuY1oEgCDw+exnA0wzXKZS\nVZ/paRhUi7v19SoXL34C227y0UcbTE0dR1VVlpdXSaddNE3HMCLkcoXtWTZNU5iY8PnsZzsrDnXd\n7bqsqKpWQ0uFAAAgAElEQVR7XyP4z7QU6fs+m5sVbNuiVIpTrbZQ1WUuXhwjkYhtB3Dnz09z//4S\nrVYaXY/iunUsq8yFCwMswXwCiqIQBMEe92VfLAhHgP3PeepxLr2m53r+h8/oVIAdPh/D1B4VHwC5\nqgV+b1mFh7HiZJjaL54PFXCp1cLfLEsnn7fRNJNiscD582O0WuEMSyajo2lh+4JCIWzB8Hi1XDcf\nm5ts60O4/FUqBWxtJYhGVSCGooyj6yq1GnjeBEtLW0xMhFGapoUfpbkcZLMZGo1N0unO4MP3a6yt\nZSkUwud81HsyCJI4To1KJUyedd3dXmo4Tran+9dq7VT9NZthvy1FUbFtMIwYEONHP1ri4x+Pbgcr\n5bLJmTOLlMsV6vUSiUSERGKRRiOs0HycQb9HkskMt27licUmtjc0hnD2KxLZewPi0XyvHg4fw9Q+\nUhsDP4ms11fNUx8jR6AC7JD6GKb2qPggoUm1nfjoeeyrr07yk58soWkzHDuWwbbXKJd9Tp60SKcN\nbtyw+bu/azI52f4Ev/Eb3Z/z8WN/8zfw4x/v/J7JwPe/D6lUZHvLkmbT4nOf80ilNGxbxzA84nFw\nHJu5uZ0qulRK46WXDO7ezRGJjKMoCp7n4rrrvPzyONevw//5P7C0tDs4UfjsZy3u3q3xr/5VFM9T\n8TwP297g5Zczu7SffM/Gx+HSJWi1fAoFBU0Lp27icXi0UthqjeF5JcbGMm33I5VKAr2teQ72PRLh\n7NkSq6tFMpnM9j1VlHWuXJnhSQ3XR/G9elh8DFP7IDYGlmo7QRCEx7Asi1dfnWF5OU+16vPKKz6W\nFVCv28AKmUy2I3B6HjQNNjcVlpZ2Lx0ZnDrV4vLlgGq1SioV5/79B5TLG7juDPn8MtlsilQqyezs\nOKlUneXlVRxHIZNRWViYRtd1ikX4yU9gYyNs8vmIf/yPDaanFRKJHPW6RzKpsLg4jrm7bO4pnD0L\n585BPu9y+7a9PevmeTv9pnTdpNGotZ1n2za3bm1SqYRVg8lkwOnTE/u2AfCJE9OMjVW5cWMFXYeJ\nCZ3Z2TnZFkboGQmeBEE4FNi2zc2beSqVAEUJv/Dm5yfZ3NxidbWB76tEowHHjvVXbl6vN7hxYwtN\nU1BVn9nZKFNTY+i6zvHj013PKRQGdVXtmKZGs9nCdR/1xwpw3TtEo2XW1iASWeCllz6Gqmr4Pty4\nkSOVgnQ6STwe49y5/pK8NU3n2LEpnidmCALQNIMgaLYt/z3Ctquk0zu+XNflxz/ewDDmMU3l4Rh4\n550lPvGJ6efaa68fUqkE584lBjILIbx4SPAkCMLIY9s27767QSYzt92YcnW1xXvvXWVs7AKWNYai\nQKMR8JOfrHP5sg88vYVAuVzl/fereN4siUQ4C3LnTo1KZZXTp7tXZA0TRQmT0n1fezhzo5FIxBkf\n97HtWSKR9m/6SGSCu3eXuXIlXP5qNpssLW3RakEkorC4OAb0PpP07L4VZmcNlpfbG5V6nkc8XiGR\nWNw+trKSR9NmOhK2TXOO+/fXD+S+C0K/SG2BIAgjz507OUxzvm0D2SCAlZUpWq2d6Y6wX88Mt28X\nu8l0EPZzav8it6w4GxsGrVZrcBfQI7btYRhRYjGTeNwkFjOZn5/j9u1wU91uNBoaQRCQyxW5erVM\npTKD48xSKk3x93+fx3GcffG+sDDJwkIDx1mm2czTaq2RTK5z6dJc27hq1d9u/bAbVVWpVKQ/oHA4\nkJknQRBGnnKZjpmKQqFKLDbH1tY6qVR7z6J6XX/KhsHhrEijEfZzajbr1Go1LMsglUpjmhk2Ngp7\ndig/dgymu6zoddtapRsvvwynTu32Em7PsrQUsHt3kkfpR/H4OBsbeRYWOhs4qmrYcuDOnTqx2Nyu\n4yrR6CyNRpV/9I+Mtuo+gAsXYGICBrkX7/z8JHNzAY7joOt6W7C742vvAKnLziyCMJKMbKsCvN7r\nCYfV1qDf8Ye2jP+FuMbe98Eb1ibC/Y4fFe1R8NFoQKXSfqzZVGg0wvynxwODZjMgn1eemMvjeVCr\nedy6tcTGRpxMJovv28Ay8/MJEgllz48r1+0ePD3quL2bbteYSLQ3C1UU+PjHQVVtkkmLIPBwXQ/L\nUqjVDCwrzvr6GrVae/BUKHjMz8PSUoVKJd21y7eiwMsv27RaZttmxvPzYdVRtdr9Gp/9dVR40lKh\nrscoFCpYVnulnW3XOHYs0nH/HjwIN2R+nMVFSD/W53MU3qviY3+1X5hWBb1m52XLwAi0Neh3/KEs\n4x+i9qj46Hcj4WG1Neh3/KhoH7SPuTmFlRWPeHwnGrKsJJub9zl2bKotKADIZDymptSnaGu0Wqto\n2iuMj+sPO4qHgfPKyk/4zGcu8qTCs0Ff45UrKs1mmY2NJsWiShBEabVcGo08c3MuP//zEywtrWOa\nE2iaRqtVY2wsz5Ur81QqVWIxpaPHFICiuHzsYyquax746whw5kyGzc1VNjYcIpGwM3qzWWJ+vsbp\n050za64Lf/mXnTr/4l/01hbiaRzVv5lR8zFMbWlVIAjCC0O5DPl856xROk1HMHTy5BSrqyu47jS6\nHkY0rtvgwoU6imJvjwv7G61x8eIkT0tZCoKAZHKMra08njfOo4/DZrPI7Owk5XKNiYnhJ1vvxrJ8\nCoUSpnmCSERH16HVUmk0Cuj6NIuLLpVKFcuqk8lE0fVjaBokkwkUZZNuM6amWSMWyzzXXn+D5vTp\nWWZm6qytrQFw9myKREL2lBMODxI8CYIwNIIg4O7ddfJ5H89TiEZ9jh9PkU4nuX0b/u//7dxQ9stf\n7gyeNE3j5ZfnqdfzFAoOmgbHj8fJZi9TrdZYXl7BdRWyWZX5+Rl0XX9q8OR5HoYR5+LFLHfvllAU\nH02DhYUEkUiKWm2TieFvtdZGtWrw8suzFItlVBXefTdCrWbh+7P84AdNYrEoc3NpvvrVNEGws0So\naRoLCxoPHhSJRHaaUTabeU6ffrY96oZNPB4bWW+C8DQkeBIEYWhcu7ZMszmNrhvoeti76IMP8pw/\nX6a/xdEwAXpubpK59uItEok458/3mKm9C13XMQwbTdOZmRlvS/ZuNstks/v7xe55Hp4X5X/9Lx0Y\nQ9Pgo4/CnKQ33ghotVodQeVu5ucnicfLLC0t4zgqpulz6lSaVGp0d2IO9sgdH2QSuyAMAwmeBEEY\nCtVqjXI5QTTa3vQwEhnn7t1lFOXguxPOzVk8eFAF2nsTRSIlUqnFvU8cApqmoWketv3o97AjeLMJ\ntu1jWU/vZJnJpMhkDv6+Po7ruiwt5anVfFqtgPPnM1SrMf74jzvHvv46fOxj++9REPpBgidBEIbC\n5maFSKR7h+5WS8eyfA661dzc3ASQ48aNEs1mBHBIpz3OnZt72qlDIZXS8H0XVW3/aFYUh2i0Szb4\nIaDRaPLuu3l0fRpN06nXA959N8/YmEep1Lm33eNdymdm4Ktf7dRN9rYtniAMhdFtVdBPPeGQ2hrA\ni1LGL9fYPnY4bQ1gdEpw98OHbWuUyy663rndRqvlAwr1euf5jUb3j4lh3Y9EYoLFxYB02nk4+6N1\nJLE/j5dcDprNBsViDcvSyWTS+H6YGO77AWNjqe0tSQwjjaZVqddB00wcR8XzXCIRA9ve2cqkWg3b\nIjzv61gslmg2HVKpGLFYjLU1uHcvfKzRgEjEp9Focfasy/R0ZM+tU57k46c/zREEC9tBUamkkMlM\nsLxcpNHwO3pBtVrtr3+tRtfcM9/vrS3Ekxi1v5mj6mOY2tKq4DnGDrOtQTj6iJfxD1F7VHz0NX6I\nbQ1gdEpwh+0jFstSKGwSjbZvt+H7PhMTAcmkwhe/2JkwPj4eVtxdu9a+kW2rBfV62GByr1yZJ/l2\nHIdms4lpml02oFVIpfqrrOvlngRBwIcfLrOxEcPzTGy7Qb3+E6LRFInEHIqiksttMTsbcOLENOUy\nTE8n8H0f13UwDIUgiHD+PBw/HmpGImGPqEf34Flex3q9wbVrOTwvi6bFKBSqxON5bHueq1fDYKZQ\naFCvuyhKlIkJnWJxi5kZn1OnZnq+H67roihmR65WPA6qGsfzmkSj7Q9aVqfWi/I3c9BjD6u2tCoQ\nBOHIoOs6p09HuHlzDcuaRNM0bLuOruc5fXoWXQ+DgL0+yK5ehaWlnd9bLZidDYOnfgiCgI8+WiWf\nfzRLWCGZ3OTChbAqb5jcvr1GqZQmny9i2wlaLVhejpLNOnzqUyaqqmIYU6yvV0gmixhGhtdeg3A5\ncyfAO3asvSP548Gj53n4vt/TprpBEHDtWg5dX9zu6K3rWWw7RT5fAdI4jkOx6BOLhWtjmgaRyBSb\nm1USiQJTU2M9XX8QBIRNMztRFOXh44Jw+JDgSRCEoTE1lSWTsVldzeE4PplMhPHxhY6tVobJrVtr\nVCqTaNqjwCJBrebzzjtbnDs33tGlelAEQcDmpse9e0VSqUUiESgUVojFzlEul7l1a4mzZ48BYcPP\nlZVlxsYyXLzYqTU+3v05bNvm/fc3qVR0QMM0Wxw/nmB8fO+LKhbLeN5Yx1YomqbRaKgEQUCl0kTX\nO6v0LCvB6uoyU913renAMAwsq3vPiCCocelSvKMLfK9b3AjCQSLBkyAIQ8U0TY4f7544Pmw8zyOX\nU9B1g//5P3c/ouK6Mb70JZs33hhOI0zf99nYKJHLxcjlVggCKBY3SKWyWFaK1dV1zp7dPV7l6tVw\nuXI30Sh87Wud+775vs9Pf7pOOr1AJLITjH70UR5dr5BOd8+objQcNG2vPD0V3/fxPNhrxsjz+kvy\nP306zfvvbxCL7URcrVaVmZkGP/dznUGeTEYJhwEJngRBOLLYtk0QdK9SUxQD27Z50j5s/bJWWGXT\nXsdTPDJKmvX1DeLx/49IJJxeMYwIDx7kyWZjZDLRtnNN0+/rudbXCyjKFIqioCg7mwhb1jjr62tk\nMmHw9CgY0bSwf1ImE2N9vYFlGZgmOM7u/KlwW5tmU8FxfAyjM1AKqyR7J51OcuWKxr17y7RaKqrq\nc/JklKmpGQmUhEOLBE+CIAyVWq3O8nIR11VIJjXm5sbRnrRj7wAxTRNF6V7h6/suhjG4j8AbKx9Q\nHN/CnLQwFZ0/+0aEv/7RAm6lQiRiYRgmmUya8XGfSmWFRGJnJqZe3+Ds2Sw3b/b+fJWKg66HeVG6\nDn/2Zzub/HpegpkZOHECPv/5MGj69rdhdRUgRi5XJpHwKRRULCusXPM8h1jMZG5O4d/+2wg//nGB\nVCosc1PVcEyjscnp05mufp5EPB7jpZfC2a5yeTAJu4JwkByNVgVDamsA/bU2GJ1S+9HQHhUfw9Tu\np60B9Nfa4CiUAq+sbLK0pBKJzKIoCpubDjdvrvDyy9OYprmntqLAG2+EX9iPqFTCL91yubelnVBb\nwzQ9qlUX2979cRegKC2CIE25/Pz3ut6ocV/JEw2iODUo3U/w3t/GWF4ap1H20BWdIHC5fDlgYcHD\ntitomkkup2JZTY4fT+F5MRoNOraVUVWoVgPW1oqUSk2iUZ2pqTFaLYVCwXt4jbC5CcXiw6sLfBQF\nstnwvj3yvL4e/uz7Cba26jx4oOP7DTzPZmIigqKkqdVA03TGx+OUSks0GhagYppNjh1LEgTx52oR\nMCrv62Fqi4/905ZWBfs0tv+2BtBPMfpIlNqPkPao+Biadp9tDULtPsYOqQS3UoGf/KTz+LFjOyXx\nz+vDtm0KhYCJid3ZzgZBsMD6+gqXLs0/UfvxJoi7ZywqlSqVSpNkMkIyuff2I6kUfOxjM7z3XhFF\nsQADRfEwDIfp6QSOE94H24bl5fAcXYdPfCJcBguCgK2tErbtkc0mtlscNJsN6vX6w75NKTbrK4zP\nR7a3Fbmz6VEsauTz4LYUND8gCDR832Fx0eTEiThf+MJJgiDANHeaGEWjna0bdN1jeTlHq5XEsrJU\nKg5bW+ucPm2xsZEjHp/GMMAwQs+e55JIaFhW+HsyGQajsRgoik2r5WKaGqoaoGka6XQK31dwnCaN\nRhXTTJBIwOJilEuXFnAc56HPPbLWd93rXhmVEvdhaouP/dOWVgWCIOwLrRb84AedxxOJ7sHT7vOu\nX2+fEQLIZMIlot2srxexrM6SdkVRqFTUJ5ax74XjOLz33hq2nUbX07huHct6wOXLM3uW6auqyqlT\nY3zlKy6u66LrOpoWRVXDvePu3g2vy7IeldbXOH3aw7JUbtwo4/tZVFXnzp0y2ewmnhewthYnlUri\n+w6atkxkbGe6qFFr4HsTaEbYLVxRNKJRE9/3iUY1xscjuO5J3n9/x6+mweXLcPp02I5hN/l8Fd/P\n4nkujuNgGAa6PsedO0ucPBlnY2MFmMD3dVy3STTqdSSLu65LLldnY8NEUSzK5S1iMR9FiaGq2sP7\nFKNabXTkgfXS/kAQXjQkeBIEoWc8D77znc6lpU98ojN48jwfRdmrMuvZgqf3319DUXaqy0wzTbGY\n4u23i8zNZbfHxWLtJe/JJLz2ms7jH3lrazs/r67mWVtzSCYTfOc7dW7ceJ+f/dlXmJwMl1kNY4IP\nPriLYUTIZscIYwoTiFNcaaFmC8Qm4uGaYqCgKAq64eLaYT8jVVVR1YBbt5qsrWXaNr9Np8PgaWGh\n/V/Ftm3zx3+8xPr6LGHfpyqJhMOJE+MEwRiaZvPJT06Ty5WJxy0sy+zau+rGjXV8f5Yg8CgWaxQK\nGhMTCWy7ia6rWFaYvK7rUWq1KoNMoheEo4gET4IgDIXp6TRra0Uikc7Zp1jM7diW42k0mw0ajTjR\naHvA9ed/rlAqWczMuNuBw5Ur8HM/17v21laJ1VUdyxp/uFwHpvlpfvCDa3z+8wkikRhBEFCrhY0t\ns9n2801zDmWlRNOo4/g+xUKJ8UyWM8cVTFVF11soisLp0x6Tk2nW13sLGj/8cIlmc5Jo9NE9jNNq\nedy9m2NxMYttN9A0jfHxLBcutHdkh3BbE8exqVYtpqYgn28yNZWiVGqQyUQAjyBoEY02iESiD8/p\n9FaphNu1PE4qFXY8F4QXDQmeBEEYCtFolPHxLba26pjmTpJ8o7HG5cv9V2zZtsPurtvt6Hie13PH\n8Ed71zlOmO9ULLokk+M4zqPjHppmYJrnuX79JleuXMb3PYLAeNgD6bFn1y3GE/PoZZe/fGeZiJ/B\nczzOnEjheQqqWiOZ1HjzTZ8PPugtaHQch2o1gWm275SraRrVqkmjkePEifGHzw//7J9116lWHVzX\nJJ0u8LGPpdE0WF9v0WpFME2HZNInHq9w+nQUx7GZmWkQBO2dKm/ehD//807tr3wF5g5mD2VBOFAk\neBKEF5Ru3QIG3fj77Nk51tbyrK8X8TyFaNTn3LkxYrHo009+jGg0ChSBbi2obQyjtypGRYE/+qMw\ngCqV4L33YG0twvg4TE6GideWpeO6LXQ9QqUSRkuapqNp9q5O5Ts4To1MJsrSUoUL8/8ATYMzC1Xu\n3HlAPg+G0eTiRZsLF17igw86Pfm+z/JygXv3bBIJGBvTSacjKEqUyUmb1dUSlpXeNV4hFithWTuR\nS7cKxI2NAqurNW7eLJHPK0xOpjEMiEZjbG6GpXmJRIJKpYJtB3jeOpOTEg0JwtN48VoV9Fun2Edr\ng2G1Neh3/Khoj4qPYWr37aNqgd9bqUc/b9VCociNG3WyWZiaipHNPnlmJwjg136t87iuP3mn+lYr\nnKl5POep1do573Hfsdg4J0/u/O66e499EqWSgWU5lMvOdgBjGNBqeWhagOPszOjYNuTz3XU0LeyH\nVCyGwdJnPgO3b7c4dizOiRPhufV6DMfJ02pBMqltz1TpegvDULZbAkAY+KhqEUVZJJ+voWlh4vnt\n21UcZ44gMLAsuHfvAZq2RqMxS6ultp1fqVRZXk5TLIbXVSw6BMF9bDuBZY3hOPd48OABiqIyNhYj\nmWxw7NiJJ96/W7dWKJfTWNYYiYTB0pLDrVtFjh1LoWkWY2MO5fJ9arUJgmANzws4eXKGWk3reG1a\nrc7XHMJlwn5bPYxKifswtcXH/mlLq4IRHdt/a4NDVmo/ZO1R8TFM7b58JLSBtioIN3ldplrNEo/P\nYRiwtlajVlvipZcWnku721jX7R50WVa73rD+dE+enOXWrTXyeQXfN1FVn2TSwjQTbbNmphnuB9dN\nW1HYLuMvlcJjzabC6mqFxcUkjgOGoXDmTJqPPnqb8+cX0bQCut7gU59K43k+N2+uoGkRwCGbdTl3\nLtzoOJkM+yvl8yV0PUskYqDrEIkExGI60egUH/94mV/4hZ3gNp+vUK3GicV0MplHie4GjrNIrfYO\nq6sB0ehJzpzR8H2fZjPH8eNNpqaiRCLdr7HRaFCtqtRqPlevVrCsLKraolZrcuNGg9dea5HJtPgH\n/+A8jlPn+PFjzMx0tiJ4pG1ZnS0UgLbnH5XS8lHRFh/7py2tCgRB6Iu1tTz1+gSWFcF9mBpjWXGq\nVZX19TzT00/uzdMvug7z8wOV7AtFUThzZpZTp3wcx0FRDFIpFd8Pg6LNzXDGyffhhz8Mv/Af9W16\nVHGvKGGV3aOGkQCum2V2to7r3qBUGkNRbCxrld/4jdPMzU3heR6WNcaHH8Lqqk257GLbEImkKZe1\n7SWzTCbg+vVVNjZaRCI7AZJt5zh5MouiaDhOnfn58LFwhmoN255G12O0twgwKZc1EgmXWm0Lz4vh\n+w0SCRtNizyxWvG99+5w69YYQRDjnXc0XLeFogSk02ny+Rxf+EIaw4jhOBvMzKjMzPS4068gCIAE\nT4JwqMnlbAyjs9zJNKNsbm4xfTD78Q4F3/ep1cLqskgkst2w8ty5nTEffQQffhj+/Kh3UzwOH/94\nu9bmJty/v/O758HsbIwvfvEEa2sbuK7N1NRFYrFwHV7Xw4T0H/6wxttva7RaKpYVoOtVTpyIc+WK\nxs2bK5RKUer1CvfulVHVJWZnk7hug9OnTUwzfJ0ezZCVSlVu3Chy/76OosRZWaliGCXOn59AURSa\nzQael+D06QVsu0Wz2SQSiWOa4zSbFSqVKhD2c2o0Gvi+TywWo9VqPezqPrW9PKjrFratY9sNpqZS\nLCxoTEw4xOOTPW2VMzUFv/ALncdjPaYpDBLP82g2m+i6vv0eEIT9RoInQTjEPN6sstfHDhv3729w\n65ZHJBJHUVpEIjkuXJgkEnm2L8/Ll2FmZud3z4MzZ6BWa7K2puA446ys2FjWFmfOpEink9y4scrW\nVoqtrQDHUdB1F9NU2NyssrLiUa9PEYkYnDo1Tjy+wfXrDer1e7z88kXS6XD5rlDwiMXi3Lzpce+e\ng64vMDlZoVQK0PUs1arN6mqBublxbLv5sJ0AmKaFae6+VhXwaDQa3LyZx7YzVKsaqlrC9+uk06dY\nX28Qi+0k1yuKRrMZkE4HRKNRUqnek/bn53dmHGu1nVm7QiH8r9EI7+f4YCc6O7h9e43NTfC8GIrS\nIB7f5OLFaWnkKew7EjwJwiEmndbI5100rf1P2XUdpqePxp/3ykqOtbU4phkn+vD7XlHG+MlPcpw8\naaI8nMpRlDDZG8JZp2YzzNFSlDA5XFXDZpSWFf68+/v20ca4N2866Po8Ox0PMly7ts4rr6hcv17E\n96eBgCAA34/QavkUiw1yORfL2hGcnp6iVlunXE5RqVRIp8cIghZ/9VctVDVFtdqgXE6habCwEOfc\nuVXK5XE0LUKx6DEx0SCTqRCJdA8KFKVMNDrBj360wdjYArlcuPEvRCkUAqJRD9dV+Oxnd7qFB4GP\n69YYG5voqtkr5TJ885vtx1ot+Cf/ZLjB09276xQKGSxrZ6bV8wLee2+JV19dHN4TC0IXjsanqyC8\noCwuTpDPr+B5c0C4/OJ5HoqyxtwRacCzutrCNCe2ezBBGCR9/esZMpkm8XgYURlGGBxBuCx361ZY\nWZfJwJ/8CWxtwW/8RoDv51lbs9jcBF0PSKeth1uWNIlExtueB8CyJrl9+w6FgoFte1y7ZuH7Co96\nfCYSHnfvNjl/vv28kyenyOeL1GpL6HqT6ekIk5MZCgXlYR+p8PVSFJVTp+ZYXc2zulpAUXIsLqrM\nzCyytlbg3r0tIpGdrpzNZonFRZ319S00rTNXKRqNUqnUmZoaI5VyGBurb+dkZbNRMpnhfOwHgcfN\nmxsUi2FwGY8HnDo18cyzg+3aAZubXscStaIo2HaGUqlMOj2ALGBB6BFpVTDI8UNqawAvSBn/IdTu\n30fvmwjnajpPf5NonDw5y4MHGxQKAZ4HmYzK4uLcdsl5V+0R+ZPpZezWlko0Slt7gCAAz9OpVBrb\ns0ThbBDbifOB4qHoAYoGDj4tAu6u5UCJEegWmOAC61t1ook6KQLqVLEfN6BCuVklV62jaKfQDB/F\nU1Afbj1jGDqNhrPdzmAHBVXVOX78xMP2AGHQ12wG1Go2m5sFVDVMeK9WI0SjE4yNQSoVEI9PsLXl\nkss5lEplbt68SyplsbCQ5dixOOn0JHfvruP7YdNO296ZddM0C9fdotUKSKcNfu3XwtmrfD7PK69E\nH24Q/PSP4r1em2azs21BrRZw/36Fen1qOyi0bfjrv17mlVcm2nKTnuX95Dgu5bLZtZu558VYWcmj\nKKkDf68+y9gXwccwtaVVwaiO7WP8MNsahKOPeBn/IdXuy0e2TKqPAKo3ZZ2xsVlOnQr3cOtZ++D/\nZHoam8n42wHSo/3qHAc0zSUe17ZL6BUlrKo7eTJMHH/nfRfj4Xnlmo+qu3ieSTyr8Uu/snt6ycBR\nVkmYJoGaIbKr2aTvgx8ERCIa8WSFmTGXX/hFA98NUFEBnyBoYhgahlHDNOO7zvWJxYqcOrVIKhX6\nM82AUqmMqqYxjCaKEsf3fVZX11hcnCEarXPuXJRYzOXHP15FUWaZnp5hehp8v8V3v2uTfPgiVyoJ\nKhWPj39cwzTD1gsP7wQzM1Esqwq4eF6TWMzn8uU0c3P9ZXh3e21qtc62BdVqA01LkEq1B+yx2ByF\nwko+B+EAACAASURBVCrnz7fPgvb7fkomdZJJZ9c17tBqNZmZsZ6pZUK/4w/L38wo+himtrQqEASh\nLxQl3Ki3Wg3/pf/oyyWdhk9/unvX6WHieR5ra1tsbjpkMlHGxtLbOUnPyvS0wdpaA2hPcA6COolE\nctfvYbCTzYY/r2/6bV/y9ZqNpkfDppZmewC7tZLkfsFiqxCgaTsnvfpJn6a7yvmXxjj/0hard0t8\n8EEU19HRFRvDCIjHfRKJOHNzdVZXS3helCBwSKUczp+fpV7f5aHexHVjaJrO+HiUYrGG52nYdoyl\npZ9y8eI809MT3Ly5iqrOt+3/p2kWq6sKpVKTWCyC70dZWalx/nySRGLnOVzXJpMxSSRinDwJs7Ph\n8XI57Gv1/e933uOzZ+HChd5fk8dpNr2OvDsIl9Wq1WfX3a0zPq6wtWWj6+0RlK4XyGYl50nYXyR4\nEoRDzp07YY7Po9J8CL8wP/3pnTHNJvz4xzsVeI/GTk6GX5yDoFSq8sEHJZrNSTIZk1yuhq4v8cor\nM89UDeW6LsVihXjcZGxsi3v3ymhakiBwUFWXqalUX4GZqioEQXgDKtUinm8T1GbZKmoU8grv/H0E\n23ZxHZ9UNiDwYXbaw4yO8+O/sdC5gqnbTIybVGsOhqJjGC6pVJR43GFhYZL5+YBWq4WuJ7vus/fq\nqzaXLj0KAjUggWF4JBIqqjrBzEyYzF0uB103TtZ1k1qtQiwWQVVVJiYsfL/M2JjB5/5/9t78ya00\nq/P+3P1erSmlcs90ene5XHZ1bVB00293M00PTA/dzcAbvBDMBBMBDMMfwI8TwAQR8D/wAxFDEBPM\nMMAAQzDR0AR0Q9NLLV3lsl3enXtKmdqlu9/3B+ViWUpbt5xyKu3nk+Fw6uq5R0c3r548+TznfM+X\nFMAmk4F8vvOn9cNBFXSqCq9d6w2q4yR6p1Lwla90H1taCnuaJe8Ss//zgZw+PcXNm2tsbWlIUpIo\ncjGMOq+8IjSqBM8eETwJBC8Avg/f/vZ+rspu8PTmm4cTPEVRxI0bFWS5IygZhiGGkSSKEnz88SqX\nLsVT1nzwYJPV1QhZztKpbmsxOysxO+vx/vsJqlWtS9/JsuD06f2E8ZkZ+MKPdW8vRaGO77S4vlQh\ntCI0XWblBzY/+L7CudPqju6TiqbBiVM2YSCxUTTZLO2uUmkkLYkf/dEAwwpIaAaSBJblcP58J1iR\nJAmzX2IOnYAln2/iedlHnlF2/g0WCD4cLxqGzvS0zuXLDYLAJZ1ODaTb9DSk03DxYvexTEbhwYMK\nmtbdFsj33UOr+pQkifPnZ3Fdl1arja7rJBJixUlwNIjgSSAQPDUbG0Vu3vQIgia2rZFIbDE+rjAz\nk6dWU/F9v+9KTD+2t6usrhqYZifIqNcBLO7eraMoBu+8o7GyQleD3dOn4ad/urOyAnDiBIydsrty\nG6Io4o/+uMjf/KOMoloYuoTekrn5wOHsmW7fdEMj8KWecKbZVnnlSsjsiQpW4DExkcE0B0+gmJgw\nuXu3hWF05x4FgU+hsB/0ZLMylUrQEwj5vksy2buKl06neo49S9LpFFNT62xuljGMMSRJwnEaJJNl\n5ucf3yYoLrquo/dLfhIIniGi2u6obMeozIPj2XR4VPwYpu2h+jFAE+HdCi7HoSu3xnU7eVC7wcRu\nhdTuytPuWNf95FVXu0RRxD/90xq2fRFV1XFdMIwUKyttXLdMKqVRLgcYRu9008/2jRsNwnCOZrOz\nzfjf//vue0iRz7d4/32dl17af2/Q+b7Z3K84Ayg9kpe/Vd5CSetkczKtZosoklDUFKal44cBftBZ\n+5Fl8NyOTd/vrSzzPBlVHyerZ7qq3A6iVOqISLouRFEO2KZWU1FVHVkG23bRtA2y2bm965HPT7C6\nukoYTqOq2s51tjlxwiOZ3M/zsn0XMxNRo0/X3kf9aKoYYQLH6ayCaRoUCp3vfR+WljrjJKmzghd3\n6isUpkkkWqytrROGETMzScbGFnaC3+6xcTiO07vw49nZFtV2ozp2SLbjV+bBcWw6PCp+DNP20PwY\noInw7i+6IOjkouxuU2Uynce7uS2y3Fshtdscd5BbNpOBarXOgwc1bFtGUUKmpnTm5ibY2qoyMTFP\ns1nHMDrJM5bV0RtqNuvMzXkUCjn6pSetr5e4dcshCGQMI2RhIY1l7SfJPJwEDxKK0nnPktQJHHdR\nlE4lXteOWS1H5qEAqmxXsBQdU5IwUxaaCmFVRwEsXaaQVZEkCU2DXFJDUWCmAI8KcecsyKtWrGnh\n4493RSwloihPs9mm1XL4hV/wWFgImJnpJIfL8u7PQ+Ezn5ljdbVEuewjSTA5afLZz+a77NaVFuk0\nRAxWGeBvd/Kboqiz/fbuu502NR9+uK8gPjUF//E/dsbEnfoymQTT00/+K28EpuCh2xZ+PDvbx7ba\nbmVlhd/5nd/hypUr/PM//zO/8Ru/waVLlw7DtEAgeAxRBD/7s53/m839Un5J6k0KluX95N3d7wfN\nty6VKty6FWCac3vK3KurbVqtVRRFIpWaJp1epdXaV7QGaLVazM4m+yZ23769xspKllyugCx3Vplu\n3NjG98ukUjN93mvI06TzjJk5Aq/Gw9OeIu+s3vken/tcx0fThK99rbMi91//a0f2YN+HiM99LuBf\n/as6Y2MtFhYyZDIx9CHo5O6kUglSKZif58D+g7IsMz8/ycO7Xo/+TMNo0LCpQy4Hv/zLu/Y7K04T\nE4PfB0+L7/vcv1/qVDzKMDFhMD095J4uAsEQeOrgKYoivvKVr/B7v/d7fPGLX+Rzn/scX/7yl7l5\n8+bQExcFAsF+mxHbpq8ODnRWgv79v99/3G53jg2YhsT9+01MszvpW9MsSqUmCwsenmezuDjL2toG\na2shjiOjaQELC01mZ0/22HNdl81NFV3vXqUwzTy12hbtdhHLmuh6LgiapFKfvBNtNjOG0m4SRRGS\nJOEHML/o8hNzET/+ts7iQ0FKItEJLHR9//oGQYDjhLiuTKkUsbkp8eBBkStXbObmJvq/6IjR0Zra\n/16WeaqANA6e5/Huu+vY9iyZjEIQwIMHbcrlZS5ePNy8KIFg2Dx18PT1r3+da9eu8fnPfx6Aixcv\nomkaf/Znf8bP/MzPPK15gUBwCCgKXaXkijL40rXruriusddX7mE0LYssV4ASkrTA7Ow02SwkEhG+\n7zIx0X+K2d6uo6rZvvlCuj7O4qLP6uoKnpft5BipPhMTJrKscOVKR4Zh4aFCK0XpzoE6iE+/OsX0\n1BotpUXTaRM0Ycqa5oP3Elz9QYNEwtiTVZib6wSXuwFmu+3j+xLtdojv53fyrNp84xvX+bmfG3su\nmtOGYUizaXP/fh1ZTsReVXscd+8W0bR5PG9/mUvXLarVjGivIjh2PHXw9K1vfYvTp093VdKcP3+e\nv/u7vxPBk0DwHNDRGwr7PhdFAaqq8MorBa5dW8J1MziOjiTVmZjwOXmyf389VZUJQ5+Ht/h2cd02\nUaRy9myaIND41V+VURSLatVG01qYpsHEhML0dPd5W1tw48bDdjqrLIuLnUAoiiI0rclUWmJpSWFM\nOkmr5bG0FvA3f+OTTGp4XgPDbDM5mUPXTXblA8IwJAgiPE9GlveDJF23sO3z/OAHt3njjadQmRwB\n2m2bUslDlhM0GgnW1+tsby/xyitzfTWn4lKtgqb17g+aZoaNjVURPAmOFU8dPK2vr5N55E/YbDbL\n8vLy05oWCAQjgKqqpFIuvh/15C4FwTaFwjSyLPPGGwvU6w22tx1mZ3OPXYnJ57Pcvr3GoyWk9++v\nUqtVMM0zRJGPohSZmdFYXfWw7TFUVaVe38KyAqA7L6rZhH/8x/3Hu1pW6TRYVpVbtxoEQZaPPw6Q\npBSmuUa9niaXK1Cv+6wXa2hpCBs+Jf8WF+1p/GAM6LwP1w2Q5U5GehSFOI6LoijIskK1+vjMo6kp\n2Fmc7+IASSigs6127Rp9GhXDhQuHox7/2mud7d4wDFhZcdG0DJbVsW0YaTwvwe3b65w79/RNpp9V\nXpVA8Cx46uBJVdWeSTIM+/+VCvCbv/3be99//u23+fzbb/cfeBzrGofoR8MoPalqfd/0i1DGf4S2\noygiDEMURTlyqYKu8UO8VaenJ/jww2VkeRJVNQiCAM8rcfp0gkbj4VWJFEHQyalqtzvXKor6qWXL\nTE+n+N731pmYmEBRFJaXl6hUIs6fP4fndVakHMfkT//0A65cuUK7vdvHzmR5uU0QFJmZ2c81erhh\nbRiG2HbnNVstn+9+t0EqNUej0aBUUmg0QjY3QddtCoU1mu1xWkpIVtNRJJ16zacd+lx+s8X5cykk\nSaFc7kQrc3M+a2s2xaIEuMjyOpOT5oGSD50y/n0Bz0d5+LxSqwGZzvypIPGNb+kUH/lZzc3C3AWX\ngGjnfhpM86inKXUEp17tfLu2WsLVcqhqp5dKxYNKW2EMi1rt4KT2h9/jk5BlqNdDarXue8FxahQK\n6cdev0E5ptP7c+/HMG0fth/f/vbf8+1v//3e43/7bz/bd9xTB0+zs7N885vf7DpWqVQ4efJk3/G/\n+V/+y+DGj2Nd45DGphQQUgVHazsMQ+5s3GEr2iJUQwzPIGNlyOSPTqqgx/bQblWDz31ujvX1ber1\nbTRNYn4+f6BYoWm63LxZpNFQiCIJy/I5dSpLJpN6yGaWZNKiUilj2wq2HXHmzByy3MlgVhTY2KiR\nzZ7HccqMjRX2qgnBotHY7noPlQq4bot63ScIFHw/oFptc/euj20b6PomjrNJszlJIjFJMmlRrZYx\njAVa7gZqRkGWo51KRI22Y/P2Ly6T28hzcuoM9+6V+Yu/eECxeArXTZFOg+dVyecL1Ot3yWRO0Wj0\n6kLpemeFaSBdx5y3954kJHQzwjC7l5h0QyI1FuzIE+iD30+PaUpd3HLI5hUe3Z5NAoqikEqFT9y6\ne9L9dPnyBO+/v0IUzZBMdn71OE6TQqHO/PzjFeif8+n9hfBjmLYP048vfenzfOlLn997/M47f9t3\n3FMHT1/4whf43d/93a5jN27c4Jd+6Zee1rRAMFJcXbmKO+NiqPuCSfer90ltp5jOTz/mzOcDWZaZ\nnS08cVwQBLz33gaaNo9hdPZqogiuXt3g1VcVEon9zHNd19G0Av/zf0YsL6vYtoPjREQRfPnLIY6z\nTqmUZWtrm1zOYX7eZHynEZvvd/8y396uUauZKEoCWYZKpUkY5qhWi+RyHb/v3Nmm2fSwLDBNhY0N\njyDwSaY0grCBLiXRjAAzAbqqICkyNjYAi4vzFArfw3EaOI69syVooih1pqdPUy5XuX07u6PntI/j\nwK/9GkyOcAu2iYkkxfUaptX7W0XX/UPJedI0jddem+X69RJBECDLMD9vUSjEa90jEIwCTx08vf32\n2ywuLvKNb3yDL3zhC1y/fp1Wq8VP/dRPHYZ/AsFI0Gg2aKQbWGp3yZmZNVlZWWGa5z94ehK+77O0\nVOL99zdxnAITEzXy+f29Ksua4t69FV5+ufeXpSRJ1Gp1wnAKWVaQJGg2m1y/HmJZOouLi0CG9fUm\njrPB7OwUur6/ShKGIdVqiKp2lneCIMD3ZUxTJwxVfL9FJpNgfDwHuGhaA8MIkOU1vv/9BKdOaaSm\nG0xMpfCdTaYXG0ydjPA9maSc2rO5uHieP/5jhWYzQlVB03xSqTyf+YxMrVYEDtibG3Ey2TSJ5Aqe\nm0B5qPjHtsucPZt8zJnxUBSFhYWpQxEpFAiOkqcOniRJ4s///M/57d/+ba5du8Z3vvMd/vIv/xKr\nX12zQHBMKTfL6OP9911c3Y3Vu+15ZFfDR1FmabUiVHWGtbU29fomi4v7Sy67eUiPYtsOmpbAtn1A\nIYoiWi2fiYmLrK5+h3T6bWwbNC3J1laDsbFtzp3bTzZ3HAfLkvnFX+w8bjRsNjd1LAscJ43rbvOt\nbyWo1RLYdoogCAlDhZdfvsB3v7vB6j2VXLSElnTIjifY3AqYfbVOsJlmZmdlRFEUFCVAkrLo+v42\nXLsNjuOSTOoUi/vvKQgC6vU2rVZEsRiSyyVGWs7glVdnuHNzg+0tiTBUiKKQs2enKBTGnnyyQPCC\ncSiz/enTp/mDP/gDAH7913/9MEwKBCOFoRqEXthX+FXypUPZ1jjO7Gr4SJKELEc7sgAWtVpAs9kk\nuZOsJMv7q0W1WoP79xuEYZJGIyKTGUNRWjSbdXwfPM9HUUq88soMkrS5I4GgEoYOmUyDiYkze7ZU\nVSUIGnsBjSxHlMseYajhOAHz82mWl2s0my7r6y75fBrL0lCUDD/1U5O8//42ujGO1pBp2S6JZIbE\n5iaXL17cC4o7yuAyYRgA3feBJLUZHx/j3r3OY8dxKRYdZDmJ78s0GgHf//4mFy+myWYHa+IbEfGv\nfzIgfKSqTlEGb8cSB1mWOXuhs4IahiGNqhY7r1AgeFF4cf9UFghiUBgrcHftLjyy4xQEAYWo8EIH\nT021woeF7yNPdoKCcMqjXnuXWfk0vHuRra0iyWQSz2szN2cQhiFXr67QbGbw/Sl8P6BY3MI0dZLJ\nBJcvR2xu+liWhq6bRFETXU9y8aKPrvuEYZ6Fhe7EZk3TSKWcPTmFVCqFJK0DCbJZB9suoKpgWS6T\nky00zSCZlAnDOhsbAUtLGRTFJZUKUdVkZ6vwyxkSVreUwuRkFsNoYNsysqwDIbJsMzmZ6JJx2Nqy\nUdX9wEOWFTRthps3l3nzzcGCJ4D5M4/vOhyGIZV6hTAKyaazh9bV4UW+nwWCQXj2wdOTWrjvclzq\nGp+VH8Hg45tq6VH5nMe7IqQKnjxWhtnMLDdXbqIUFBRdwa272FWby7OXqTHYfV1qtAaWHygNXoW+\nP34H13UJAh/TtPr2lTusW9W227RTDf7W+weQO6tLtg+h2eL1ZkCycQ7fD3cSvm1SqVk++GCNanUG\nWVYoFm0KBZWf+Ik8m5sVpqY0XFfhu9/VWFryse0QTetUx3z5yyrZrIrnrQCzPVPJ7OwUH320jOfl\n0PUkqZTO9vb3OXHiAh98EHHrVkgQeMhyCllWOHnSJ5PxCYIszWYT3/cJgk6yea22TRD0ls/btkQq\nld4RB+3oPOl6ljDsTG3ZLLz5psvGhrbX1qXd7rR6cV2w7Qxraw2SyU4A5TgOURRiGCaSJFEaQCV9\nl61Kiff975CZMkGGqBgxp8wxO9Ffkyn2ZyaGVMZxnIKHaVv48exsD9OPx/Hsg6dRqFU8hvWVuRoQ\nxPF7NCQCniepgkw6w1xyjs3yJm2vzXhyHBZi+uHlBh+vx79VTdPl+vVNWi2TMFRR1Qqzsxrz8729\n157mVi2VKty718TzEshTLrbcwEzq6DsRg64lmElbaOP3OHtW4vTpWSwrD4DrRrTbZUolj0YjQaPR\nxDRtFhc9JKlCJnOW8XEJxwHXXSeXm0RRwDQDZLnIq6+myWb7KS5qfPazC5TLVSqVDWZmdE6e/BTX\nr7e5fdsmldJQlAT1uossqxiGxvR0jrt3N4miHKapYFk6QWAzPj7G9naDU6fMrtWcMIQf+iFwXQVd\n38/rnJ7uXKNMBmZmXD74INprZ9Nssve9osgkkyGq1uJG+SPsRBsUCbWlsqAvUlBmyAwQQNm2zZq7\nzsT07L58gwWVaoXJ6iT5bL7/zzHOvRpTKuM4TsHDtC38eHa2h+nHQYhtO4EgBrIsMz2+X1k36IrT\nsyCKIj74YANZnsc0d4OLMVZWGijKFjMzh9O9vlZrcPOmj2XNoaoQ6R6ZxBRrG2tMTE6wO61EUcBL\nL1lcuLC/1xlFEZubFcrlE+j6BKbZUcwOw4hmc5nLl0M2N+uoqkQ6rbKwME293sbz2iSTIa+/Pv7E\npOtcLksul6VW6+QHpdMdTaYzOylSrivhOB7z8xqplIppWuh6k0xGQdchmTQwzY5y+MbGNrOz+4Hn\n2Bj8xE90VpkOmoATiQSKsgH09oWTpDqWVeCd0ncwFkys3SXiMbhXuc1MVSeTefLPablyH2vWokW9\n6/hu9edBwZNAIDgcRPAkEDwnbG9X8P3xPW2lXQwjxepqlZmZA06MydJSFcvqTv6SZZnJyUn8YAtZ\ntpBlyKZ9Lox3j+tIEjiEocLy8ib1uoRlRaTTKoZhYpohhUKGwkNyUtlskiDoBC5B0N0AWNc7ytVP\nYnsbXn557yxc1+Wtt2rkci2Wl2UuXMhjmvvTYachsEar5ce8Op1rMT+v8eBBFdPcly5wnBpzcyrX\n7lznTqtOtOag6gETsyq5iQzmmMXqxgMWeXLw5Ehu3+1YAF+O77NAIIiHCJ4EgueEWs3GMHJ9n/O8\nTvn/Qb9w4+C6ck+fMolOKb+mJ8hmUhgGpLDY0ZfcI4oiEgmVd9/dJJlcRFE6Pc/K5TameRdZ7u//\nxgZ861vwf/9v9/Gf/3m6Aq2D8LxHe8TpZDI6L7+cwfc3uHRJ5VF1Fde1SadjJJ09xOxsAcOosLy8\ngu/LSFLI6dMJPE/ixp0AZW6xMzCEldt1XLvC1MIYruI83vAOJhZ20IY+gaMefjKfBQLB4IjgSSB4\nTkgkdCoVB00zep5T1eBQAqeOrbBr9UeuZ/l56VchirCsKhl3jIQKWtT7S1ySJNptnxMnCpRK23ie\njKJEpFKQSo0TRTZnz8Kv/Er3eTdvwj//c2/rk0GYnOy1B+z0yYOpKY2rV+vo+v42W6d/YZHJyfn4\nL7jD+PgY4+Nje1t8YRjyve+tkzQmqIZllJ02NLqRprjSZGIuRAkHm5IXcifY3FiDR9xrl9qcGTvT\n/ySBQHBoiOBJIHhOmJjIsb29yqO/UT3PYXLy8D7qc3Mpbt6sYRidpJ/IMVCK07Ram1x6/SRu2yRz\nQFpSFEVYlkoQKJw8mafZDEkkJCRJwnWXiSKVZJKHetjtU6vtBzz92NiA997bf+w4nfEXLsABrTYB\nmJrKU62WqFbreF4CSfJJJGyuXJncCzglCf7F/HvKUbljWwZDB0My+ILzk0ThkwPTVqtFEKSZzJiU\ntjdRCvuJ6FGUprJRYUG99EQ70Glr80rqU7y3/C+0J12QQWtqnEueI53szbUSCASHi5AqeB79iCFr\nAPGkDUZaTuAIbMeRHoB48gM3tA9oSVtdxxRkLrXeQvF6Ffy3t2VOnMjz8cfL+H4WWdYIwzq5nEcu\n113a/zS3qqpmyWaLrKysI0lZIESSqpw8mcB1zSfYlkinx2m3t6lUNJrNNJ7noShV5uYyuG677xTh\nONBq9R5vt/enlGoV/uVf9p9rtSCRgPFxyD8hf1pVC5w/H2HbbRQlga4XcJz9lS5ZhuvSXe5F9/dt\nR5CTsrzZ+AlC/+Dgafd6tNsyzaaLZWlM+KdZfXCfIN1ZEXS32py3JlGSMwNPkZBmbuwC6USbKIow\nx0zg4CKG+J+ZwXUTSk2VQSeRUZmCh2lb+PHsbAupglEdewz9iC9rAHGkDUZZTuCZ244jPQB95Qds\nu5MYZJpm1/F1+Q4f6e92HbMweUN5DeuAnOBMJsHMTIJarY7rtslksuh6/2jtaW7VTGaCc+cCqtU6\nsiyRyUx3CSs+zvbcHIyNTRMEPsVik2xWJZmcp9Xa5Ny5HP3cNYxOIPToypNl7b9WpdL7vGF0/g3y\nXjMZiWy2fwAgSTsrTY/Y1iVIAYR9T3vIdudns7y8jaKMkUxmmY4u02w18EMfc6bKD18++dgqvr4o\nKTLm4KKbse7VXI1MjABqWLIGccePim3hx7OzLaQKBIIXiHK5xt27dRzHQpJA00qcPTs2cPuOx5HJ\nDH/rRlEU8vn4fc/OnJnk/fdXgEmy2RyJRES7XeLkSfnAQC+XgytX6AmshtFOcHW1I2rZ8zpn4Gm7\nopw/n+Pq1VU0bRJFUbHMBJ63ycWLA2S9CwSCkUEETwLBEdBqtbl2zSaRmHuoyivPRx+t8/rrGsbj\nknuOOaqq8tprc2xsbLOysk06DS+9NPbYZuLnz8PMDKSHHBNKEvzDP8D9+93HZ2bAOIQ87HQ6yZtv\nGqysbNFuh5imzNxcYaQbBgsEgl5E8CQQHAEPHpSxrF7hJcOYZGlpg7NnD0mUaUSRZZmZmQLJ5OBL\n6NETVn0kiS65AUUZXAdqEHR0LDovoEid1DWD+EGuqqosLk4djlMCgeBIEMGTQHAEOI7UVzpAlmXa\n7SNw6DlgdrZbkqDZ7FTtHcbWnm3Dz7lfI9zZt2u2ILn74wtFE12B4EVDBE8CwRGgquEjoo37aFrn\nF/Rbzmf4tPJDPc/rwcHbWy8SYRiyvr5Nve6haRJzczksa38lyPPoEb78pEQRmGFyb/XLc8EyH3+O\nQCB4fhFSBS+6HxBL2mBYsgZxxw/Vdgz5gTjSA3vjgUwmw40bZSyrW1G73d7i0qVOX7ZWqbCnnh2G\nIVtbFWzbo51t900IL7UakHlC2dfu2GGWlsfxAwcG3Pp62GfXdfnwww3CcJyGU8EN23x0rcXFl3JM\nTOTi+7FjW5bBdXvFOF0XGo391jCxPo5Duh6d8YPfgMP9zBjxPjNx/DiG06rw49nZFlIFozr2BfAj\nvrTBMZMTiDs+jvxAH+mBJ/qR6VTDKUqJpaV1IIskQRRVuHRJZ2Ym2TW2Vmtw40YFWS6gKDrLyw0s\na4lXXplFUfaFFsl58W6RmD4PTBw/ci0yA0xDruuiGA6yPE4qleTq1SKRarAivYMyoyIrCtt1h+/e\nvMfPLv4/qKr6ia/Hj/wIfOpT3c8pSq9w5+Dv8fCvxz76aHxmUoqQKhB+HJltIVUgELxAzM4WmJoK\nqFRqSJLE2NhUl1YSdBS5r1+vYBj7quGmmcH3k9y8uc7Fi3PcuNEprXdkA2NnK0nX4NwrLtFOjo7r\nuoRh2KMl9TBldZM1ZaXneNqaIsPsIbzj+ERRxM3rG2yVdNrNDKuhj6Lco9EIWbHuYEzsr56ZWQtb\ni3j3xvu8demNT/ya584dhucCgeB5RgRPAsERoigK4+P9m+ECbG1VgPG+51UqClEU8s1vymxuX3E+\nWQAAIABJREFURriytCcSOTMjce4VaDRa3LxewbETRJGMbpQ5dSaJ2qcBb1ne5i+kP+85/iX1qywc\nQfAURRF3bm9Sq01gJXRCX8YiRRAkee/G15n9sV7ZcM3U2bQ3nrmvAoHgxUIETwLBCOM4PorSXwMo\nDBXurd9hvZVgreUT4jMeZUianf0l3/P58L06prWAuZc4nePjayVOnGiSSR/C2vUQqDaq3Kvcoyk3\nuXG7Rl46w3z2LLu5PYqiEsgSLdsmtbOXZlkhsuHj+U3GpkzK6iZtpYGGuScvIBAIBIeFCJ4EghFm\nbCzJ0lIdReldKVquXiMznUZJpVBbKq4UUI7KRO0ISLOyUkbTe/WETKvA8oM1Zi+NnpZUvVnno9ZH\nWPMWuqejTiZo600+XnmPBfUt2JEHODd3ilvFd0glO3tsrXSRv5L/FN1wyEpJ/kn9Jo5s8//x05zl\n7BG+I4FA8DwiBEoEghEmmUyQSjUIgu5+IbVakeTpBoqqdB1XDZWa36lotdt0J5Q/RBRpSBJd/1QU\n5COeEh5UHmBN7ghRqgqK4iPLMuFEQLm+vx03XZjm5VwKpHV8v0QY1TGTDpaukdYyhDtf0dP2UxEI\nBII+CKmCF92PuOOHJGsAQ5YqGJL8wFB/jDsl7vMvp7l35w7lbYkw0FA1B6WwTfq8SYsmHh4uATY2\noOCrPu2gjae1aESNHjFOVZG4tvBNrkp/13U8lG0sL8N2WOk63mhALUYMUjLilOZ3X5CSXELdnZYk\nMMfblLcqqKbJWrREnmmiKAJ9hbevfJo7xZtUlQqtJGiBTEpOIxsyDg4t18MOoXaAnlbX68aVnIgl\nPzAicgJDtT14A+E4MhkwOlOf8GM0bQupglEd+yL4EWP8MGUNOqOHVHY9RPmBof0YHypx/9T4BFEU\nEQQBqpqlVJa5Y95Bt1R+7Mst/BAcPAxkvFrI2azK1Nwk7661sBITXWYDu06UbVLUuxOrDVnlp9Wf\nJXgkUDLNcTIaXLsGK48U4ykKvP32I2KUSipe2fpDo9NRumv16/RckpVwm61inYScRlY3SaXbvHRp\nAk2TyE+cJ4oiboQ3+EiZ3jlr5w20dcwwQSY4OCF/j7iSE7FkEEZETmCYtnM1MjECqLjZdiPxeRR+\njKxtIVUgEAgORJKkjn4RkM/mubN2h2AuIHF+FYAmTazQwlwzWZzzAZMz523u3lpFknKARBhWmT8h\nYZm9Qox6aDHvnUYJu1dJam1Ag9VV+P73u88xDHjrrcN7j+PKOEW3iKrvT01zC3myWoOFxSlm0kl0\nvRMMOY5D225j6AayJTIQBALBs0METwLBMUSWZS5kLnBt5RrKhIKma7hNF2vL4vzs+b1xk1NjFCZC\nKuU6QRCSy4+hqRqMaP+8E5MnaK40qaVrmFmTIAhwSg6n1dOkxlPo6IRhyPXV61TNKlJCAhvklsyn\nxz6NrOwHUQ5S7JUWgUAgGAQRPAkEx5RsOstbibfY2N6g7bfJWTkWTyz2jJNlmfx49gg8jI8kSbw8\n/zL1Rp3NtU1UWWUmN4Ou69To5EveXL9Je7qNpe7sFSY6mlD6ss6nFvalwWu2IoIngUAwFETwJBAc\nYxRFYXaiI2C5G1wMQkpKkac7FygRJ7v/EKg1anxY+RBZkZEiiRw5Tk+eRlVV0qk06VRv/z7f9ykr\nZUy1WyldkiTa6TaNZoNUMkWlXOPqe23kdhNFicjl4PTpqQOrDwUCgSAOotruRfdjmLZjVOZBzKbD\nMarnIGYF3VAbucZohBujSmt//GC8uv15vhBO9hxv9sn53b0eoWogPeK6ZEALn/ChZOFB/G62mnzU\n/Ah73maMMQA2wg3Wl9d5deHVngrBXbtJN0nDaBD0SU52TZdiu0jZq/Hx1Qi7Nc1YVCAMYW0toFhc\n5ZVXFvr6E/sj8xQVhQdRqVW4Wr9KUk6ihRqzqVly2ccnu49Otd1wKvNgyE2sn/PpfVT8GKZtUW03\nqmNfBD+GZDt+ZR4MXIcTp3oO4lVTDbORa6zx8aq0IEZ1lKWQfPKoDjvX47M/7vCZH+sNaqxUgCQ/\nXKL3ZL+XykuMz43TpEly1xMZ3AkXp+wwme8N7Gr1GsVKkc3qJlk/y1R2ClXbv5ZKW2HanObjaxXG\nrQWanvzQe1RwnBxBUCWX67+FGesj8xQVhf1Y21pjVV4lM5fZux5r1TW0ksZs4fGtcUai2i7O2JiV\neR3bMcYe/dQn/HjGto+i2k6UqAgEgoEwkwGJjN/zrztwGoyW3Op7XLd0yk655/iDzQdcD67jL/ik\nx9OUk2Wul6/jOA4AYRiSbCaxLIt2q//WnGGk2Nrq/7pHSRRFLDvLmLnurUgza7LsLROGg61wCQSC\nZ4cIngQCwTNHDvtPPWEY7otk7uC6LsssY411EsTnp+dJl9NEUcTtldu0i22MVYOXZ17u2Jb7BxtB\nEKBpozflNZtN/JTf97kwHdJoNJ6xRwKB4EmIhHGBQPDMKagFim6xJzXK3rJ5Ofdy17GNygZG3thR\nUO8khy/OLhL4AbVGjdfSr2FO7K/ajE9AZdvnUeOuW2R2dnwo7+dpkGWZyD9g9S7qPC8QCEYL8akU\nCATPnBOTJ7A2LexqJyAKgoDWZouT0klMs3v7qmpW2Za2qVFja+drm200VcNKWeh6d5B06swkmr6K\n49R3bPu02+ucOWOgadqzeHuxSCQSGA0DCYmAYO89brFFLaixklzBY4AeMwKB4JkhVp4EAsEzR5Ik\nLs1fYqwxhr1md+k5PcpGYoM/d/6cKBGh76wm6ej8PD9Pwk/0rMzIssyV1+ZYutfELa2haTIzM+Mj\nGTjtcnbsLNfWrvHx1Mdcla8SRRF+06dgFbguXedX+BU0Rtd/geBFQ0gVvOh+DNN2TD8aRmlg9YHY\n5c5DkggYlfLv+LZjNHIdomSCk3KYSHV679k7X48SqAFaW6PslvEln0a7gYLC1dJVToQnKLmlvkGX\nlw2YyBYAaO98HexzXMmJw71HpJTEWf0sH7Y+JIgCVEll3BpHVjpNjps7DaA/ie1PMnaYtuP7cfya\nDh/TKfhY2hZSBaM69kXwY5i2Y4xNKTBwUXLccuchSgSMRPl33PGxrt+Tr0fbbnNv6x5tuU07bGMa\nZleJfbFcZLW1SiAHGKHBibETpJPpgXzW0ZlOT6M2VNYaayhphSRJLixcQFEV7izf4Y3ZN3oFMOO8\nx7iSE8O4R3SY0qeYY67rsIFBkiQWVt/TRuJ+GqYfx7Tp8DGcgo+tbdEYWCAQHDsarQYfVD/AnDWR\npc4W2nJ7mfpKnQtzF7i3cY+N5AbGnIGMjIfHh8UPueBfQM0OPgV5kUdhqoAkSejoe1V58rTM6tYq\nC5P9BTB3kejVqIqIL7OwS71RZ6W2gi/5JKQEC+MLI701KBAIDg8RPAkEgqfibvku1lz3qohu6ZQT\nZSrVCmvSGlaq+3lrwuLeyj3OZs8O/DoeHrrUu1WmairVoMoCBwdPW2zxdb7ec/wyl3mZl/uc8XhW\ni6uUlTLWbOd9lYMym+ubXMlfIWE92zY3AoHg2SOCJ4FA8IlwXZfNyiYPKg+YnppGUbu3zYwxgxsf\n3UA521+00jGdjsjlE1KNXuIl5pnnbnB3L2laQkJGJqSj6aREj+9ZFxBwj3s9x09x6vEv3gfP81gJ\nVxif2Jc9UBQFZU7h9sptXpl9ha3KFrZnszW2xZq+tpfoDqCi8sP8MEafN36JS1zkYtcxCalH+0og\nEBwt4hMpEAhic2f9DhvKBlpOo+gV2S5tM6PNUBgv7I2Joghd0fGiA8rsw14NI8/zaLfbaJqGZXVW\ndaaZ7tgLIsqtMnpC3zm9Ezi1K21Op09/sjcSdbbf6tRJp9J9e+o9SrFSRM33nzo33U2+/eDbyBMy\nWkbjPe893qm+w3xmfs+2hcVbvNX3/AKF2HlJAoHg2SOCJ4FAEIvN7U2KqeLeVlxGy+BNeKxurZJs\nJfeKnZwth1dPvMoH5Q9gpteO5Vh7OUJRFHFr7RYltQRJkGwJo2RwceIikiShaRpT41OEKyFlp4wx\n1lm1sbdtpr1pMtPxA46W3WLFWSGQA1pSi5W1FU6YJ5jOTz/2vIiob5AVRRF363d57eXXUFSls2Kk\nqIR6yHZjm/H06Al0CgSCT4aQKnjR/Rim7bh+BIOPb6qlOBXJI1R2ffxsPzr2VvsWUT7Cp9NSJJ/L\nc2vjFuThfuk+6USa9nabOWmO9cQ6eqhTqpVQ0yqSJKH6KvaGzSvjr+zZvr9xn+3xbVSjMyVFiYj7\n3n2+89F3OHvyLJIjIUsyr82+RqaVYXN9E1mSOTt2FsM0qNE7rzzsd5s2Ds7eY9/z2Qg2CLIBISE2\nNmbK5Or2VYJGQDqVPvB6GFmDYrmIMtG9VVitVCELttqRW9hNjndkh5CQZJREkiQUlEORHog7flRs\nj4oEB8STNngRpuDjaPu5kSpYX19nevoxf7mNQq3ii1BfOSq2Y4zN1YAgXq/6OIxE2fUxtf3wWEu2\nuivXNHh94nVK1RJ20WaaaS5kL+AlPX6f3ydMhXieR71RJyDgC9IX+NLkl9A0jRo10lGadtQma2T3\nTD4oPSDIBSQSCbRQI5PPUHWqFNeLnJ05y0yyz1LWY/y2sZliau942Skzn5wnRYokSQCSJEnmk1RW\nKsyl5gjDkDsbdyhHZUIpxAotFjOLFNIFzgfnadVbGOnOClgURZRWSpxfPL9nT0JCQ8PERFZktFBD\nURR09EOTHog7flRsj4YEx67tGGOf7yn42No+1lIFxWKR3/qt3+Kv//qvuX379mGZFQgEI4YRGri4\nXcdkRWY8M05hukBuKkeKFGXKe89rmkZeywMwxliXWrbv+wTa/i883/OpKBVMzUSWZdpbbTKZDKqh\nUpJLnPRPoqrxpq5JJvlP/CcAPNfjW0vfopFv4EYuG/IGyYkku/GgJ3dWhD5Y+QB/xkdTO76GhHxU\n/IiXeZnF6UXcssvayhqBHJCIEnx6+tPcDrvnPhUVAwPVV7ESnWBJKIULBMefQwue2u02J0+exHXd\nJw8WCATHlsXcIj/Y/AHWZPfKib/hMzc1R4tWLHuqqqK4+1tgjuOwuyjjt3wS5v62SpSIsG2bVCoV\n22/P87i3fo/vbX2PslEmmUliWRYNt8Hm8iaXFy4DoIUa5WoZO2djqN0VcdaExb3le5xKn6KQK1DI\nFbqeX1taw0t5KIpCRMRlLnOidYKFcIFx9nOeTLr79wkEguPFoQVPJ06coFAoPHmgQCAYmCiK2Kps\nUbEraLJ2YP+3Z0kykeTl4GVuL9/GMRyIIOkmuVK4EntFCDp97iaVSYpOEc3QUFUVyZWIzAilopBe\n2M8/klwJLRV/5aZtt3m/9D6rrCK/KpN1s9xcv8l0bpp8Jk8z36RaqWIEBqezp9msb2LM9NdQaCsH\nt3m5NHuJ2xu3KctlIjVCdVQmjUkWC4uxfRYIBKOLqLYTCEYU3/d5Z/Ud/IKPkTMIgoCV4grnjHNM\n5CaO1LdsOsvr6dfxfb+TBP1oa5SYnJw6SbAWUJSLRMmIcDns9Hub3hfRjKKIZDuJMT54D7pdbpZu\nYs6bOKsOiqSgGRon8idYWV9BD3QiLWLz7iafO/k5MqkM5WaZIAj6vi85lPu8QgdFUTg/e54wDAmC\nYC+vSyAQPF888+DpN3/v9/a+//xnPsPnf/RHn7ULAsGx4O7mXaR5CUPuBAuKopCYTnBr7RY5P/eJ\nVnkOm8f5YGDwRb7Yc/zh7auHOTNzhkV/kXa7zaX5S9yq3sK1XSRJwmt5SDWJl6Zfiu1jEAS0tFbP\nVlkqneKMeYZ0MY1lWCxMLjCZmwRgJjfDamkVa6p7azLwA/JyvuvYNtvc5e7e4yiIcD2XWWmWk5yM\n7a9AIDg6vvnNv+db3/r7vcc//uOf7Tvu2QdP//k/dx84SLrgONY1Hkc/hml7mH7EkDWAeNIGo1B2\nHUURD6QHTMqTPc/5BZ/b5dvMTHRXnI1iafkZzvQds7sa02NbBXZ26c5mzlKr12hVWyTNJM6CQ3vn\nK44ffuTTlJoEBCiSQjNoIiud1aNACkiYCWpejWQmub9KpENBK/Bg4wFaoVMl5zQcjG2DM/Nnuvze\nYou/4q8AqDaqNGkS6RFfCr7Eg6UHjI+Ps5B4fN+9R30elFG4V4+rH53xg1fmDUvWIO74UZmCR8X2\nYftx5crnuXLl83uPb936277jnhg8LS0t8frrrx/4/Fe/+lV+//d//0lm9hmFWsUXob5yVGwPyY/4\nsgYQpyj5qMuugzAgI2f2yt4fJlIj9EDva+fhY02afbeMUqRiK1k/qxL3MmVs7L3HSlohnU6TJ4+D\n88n8UCHv5pGQODN5hpsrNwmmAjRDw67b5MM8aTvN/Ox897n5DIvuImulNbzQYzwxTu5EDuhoOO36\nUqOGgUG9VcfTPSy9s1qVIEFmIcPG8gYvGS8NvLU5KnICw7Q9Kn7ElTYYlqxB3PEjMAWPlO2RlCpY\nWFigWCw+/SsJBIKBURQFw++f22NXbSbST8552mCD/8H/6Dn+Fb7CHHNP7ePTEhHRotWlGXWTm3zA\nB2yzvdd+BeCX+eWnKvE/M3aGq+tXMadMzs+fZ2t7i60HW0w3p7l86jJKoX9go+s6i1ODJXs3/AZK\noteOMqmwUd5gtjD7if0XCASjxaFu24Vh+ORBAoFgIBZSC6xtrWGO7+fq+K5PppEhNR+/VB86n9FS\nvUSpWSJNmnF1nLnCXE+PuX40W03ul+/jyA5KqDCTmHmqxPWIiP/F/+paaVphBROTKaYG3p4bhEwq\nw6vKqzxYe4At2UyFU7w6/iqT5zrbooeR1B1IQd8Gvqqu0vLiyTcIBILR5tCCp3feeYc/+qM/YnNz\nkz/8wz/kq1/9Kun0wS0OBALB48llc2RrWe4v38dWbJRQYVwZ5+TcyU9kLwgC1hvr2GmbRLaTu7Hu\nrlNeKXN5/vJjm+JW61Wutq6SmEsgIREScqd+h8Z6g1PTpz6RPwA+flebEhcXmScHcp+EhJXgJWuw\nhHPP81jaWqIdtdHRmR+b32tUfBBK1H/1ynd8ElqMXkICgWDkObTg6fXXX+frX//6YZkTCATAWGaM\nsczYodiqtqrIGbkrSNJ0DbtgUywXmcz3Jqfvcqt6i8R8dwBgpA3W2mvMe/N7DX6fB+rNOh9WP0Sf\n0lEUBTdyea/0HmfsM3vVeA+TJ89/4D9QkSqU7TKK2QmidrcZg2LA1MxUz3kCgeD4Mpw/8QQCwcjh\n4PRdXdItnZJ9cAmK53l4Zm8TWwBtTKNYfb5yIm+Wb2LNWnsJ3pIkYU1Y3G3f7ZuakCDBDDNcTF9k\nvjYPaxA2QpyKQ7AUcGn80lPrYAkEgtHi2QvFHCRN8CjHpa7xuPsxTNuj4gfEkjYYlqxB3PFPa1tH\n57Psa5Ssh+tISJiYVKh0jfXwDsz72ZK2aEadUv9H8SKPltTqOjeO323aODh7jy0s5pjjR/iRru08\nH58q1YHtxvVjd6zjOJStct/2Kc6Yw1JtidxY7kDbY5NjpIM07VYbRVewFixKlAbOqRrl++l58yO2\n7YYB4WBlWqMy9Y2KH8O0PUw/HsezD55GoVbxRaivHBXbI+JHfGmDY1h2/cj4DBnm2S+/v9u+y3Zy\nG0VVkJD2ZBDsus3Z5NmDX0uFttMmIto7FBBQo4Zne/hjPhtsAJ0GvIPKIEREvM3bXXah0zj4U3yq\nZ3yN2tCvtR3ZJKQEFr35TZqskYySezYPtK1ALp17Kj/icBxtj4ofscanFCFVMKK2R1KqQCAQPB8s\nTi5SXi7jTXmwo4LgNBxytRy5udxjzz03fo4frPwAbbojGLkdbfO/2/+brJZFVdS9Val/x79jjDFa\ntChQ6Ft95uKyzTYAJzixF6gYGOR4vB/DxjRN9K3+vQPDasjY+OHknwkEguONCJ4EghcEWZb51Pyn\n2NjeYGlrCR2dE4kT5OfyTzw3YSV4Y/INlovLtKIWRsJgMjGJrunc5S4rrAAwyyzrwTpBK+BrztcI\n3ZB0lObMxJm9hsZNmvw3/hshIQ4Oxk4k9xk+w49y9O2aTqVOcaN4A2tif/XJqTnMSrMj0RJHIBAc\nPWImEAheIGRZZqYwQ5Jk7O0NTdP2ZAmucQ2d3hWaKIzYaGwwlhlDS2tERNiRzbsr7/L61OvHoiov\nn83zSvMVHqw8wJVd1FDlbPIs45P9e/IJBIIXDxE8CQSCQ6PttpHT3XIIkiShzqg8KD7gzHT/XneP\n8rDq+OOODYt0Ms2l5KVn9noCgeB4IYIngUBwaARRgCT3BjmKotAIGwPZiIj4P/yfLuVxgCxZvsgX\nexLMBQKB4FkjpApedD+GaXtU/Ig7/pBkDVQ3JPXN98HfL7nXaSHnF6i+efaJQcAolHQ7jsOd+h0m\nlUly2dxeG5c0aX6SnwTgLne5xz0AWmELGxvFUdhobyCpEolU5wIpKNSo7ckThIS02G9b4uBQo4aE\nxC1u9cgpzDBDnXpXz7vDeI8HjV1iiTXWuo7JyFzmMnXqT2X7MMYeV9uj4kd824M3EC41VQbWO0FM\nwaPqx+MQUgXCj+HaHhU/Yow/LFkDOXDRv/8BNJt7xyIcjEsy6TdfG9Dy0ZV031y9yZa+hZ2xKQZF\nNtc2OZc6Rz6b75JBSJPeazRcj+qMFccw0yZ20qbaqqIv6SxkFjhtniZDBhWVn+QniYi6EsYnmCBD\nhogIHX3v+C4WFmnSsVaenuZ6bLPN9/l+1zEVlTd4Y2A5hsPw43m0PSp+xBqfq5GJEUDFrYYXU/Bo\n+nEQYttOIBD0sFJcoZKrYFomAUEnOXwObqzf4M3Em12J36d2vgDeLb9Lzsjhui7tdBsja9Cixfat\nbSbf6LQ2SZDgDd4APpl200HUqLHJ5t7j3cAsv/MlEAgEh4UIngQCQQ8b7gaa1VsZp0/orJRWODl1\nsue5VquFnbJZyC0gtSW2SlsAzKfmkRYlXNfdkysYBhUq/Al/svd4N3j6N/wbETwJBIJDRQRPI0YQ\nBGzevUtULkMUESWT5E+d6qN3LBAMD1/2+0oRKIqCG7p9z3E9F8noJIsnrAQJaz/no+23YwVPSZI9\n23P9VL8FAoHgKBDB0wgRRREr77/PXBSh7G6LeB5r778Pp09jHcZGreCZIikqUZewYgDy6PfjNkKj\nb26R53iktFTfcxJWgqga9c2TlVoS5nhvv7h+SEj8Ar/Qc7xJ85lW2klIPQrp/RTTBQLBi4eothsh\nP8rFIhPVKsojf53PQCeoevvtw/cj7vjjeK2HafsxlXlhGOH9v1/rOlZVqjiJHPYAjWKPsippLDXG\nrfItzNx+E+EoivA2PRJzif6NbnXQXI1VbxUe2vHzHZ9smKWltnpOOUyfbeyuJsO7lXy7VXxxbb/E\nS5zlbM/xkJAy5UFcPtD2YYw9rrZHxY9h2o5TmQfxqvOO4zQ5TNui2m5Uxz5DP+zVVfK5/r29JM97\nLt7j82b7iZV5qWzXQ19JQCbTZ0PsADeOqCopk81glS2WVpYwTAMpkMi4Gc5PnseQjQPPe2P2DdR1\nFUdyiPQI2ZGZkWY4NX3qQJHLw/K5QqWnQs/Y+RrkNeL4oaCISrTnwI+h2Y5ZmdexHWPs8Zomh25b\nVNu94EiqShRFXerMexyDrR7B88VkbpLJ3CRFp0hOyQ3U102SJE7PnCYVpvA8D21M29OGGjZZsnyN\n/ZU+GxsTk3FEWxWBQHC4iOBphMjOzLBdLDJudSfGer6PfMCKlEAwbAzDiJ3rI8syhnHwCtUwyO58\n7XKYMggCgUDwMGI5Y4RIJJMEc3OU2m2iqJMY23Ac1g2DyYWFI/ZOIBAIBAIBiJWnkWPyxAnsyUnW\nV1aIgoDk4iILudzgifYCgUAgEAiGigieRhDTNJk5M1j3eYHguNCm3dOX7uHqOIFAIDguCKmCF92P\nYdoeFT+GaTuuH4fUdLivKyNcWq6g8Cf8Ceusdx3Pukl+zfklomiAyiSnBHHSqGKMf56u9ajbHhU/\nhmk7vh/DaTo8KtPkMG0LqYJRHfsi+DFM26PixzBtxxh7WE2HDx49mqXl0s7XoyKXeigzFqQgerL4\nZa4FqDGudczxz8u1Pg62R8WPYdqO5ccQmw6PyjQ5TNtHIVUgEsYFAoFAIBAIYiCCJ4FAIBAIBIIY\niOBJIBAIBAKBIAai2k4gEDwTznOeWWa7jiVQjsgbgUAg+OSI4EkgEAydiIgf5od7jivtGvDkZHGB\nQCAYJYRUwYvuxzBtj4ofw7Q9RD8aRokwRlXI6JRdDz7eaJTIhE8e1zE8xJ95DAkJiCdtMCrXelRs\nj4ofw7Q9XD+GI2sAIzP1jYwfj0NIFQg/hmt7VPwYpu0h+ZFS4Hkvn1dSndGDGx7OtY4vIQFx/B6F\naz1KtkfFj2HaHpofQ5Q1gJGY+kbKj4MQCeMCgUAgEAgEMRA5T8cEx3Go3L9PFIZkp6awEjHkkAUC\ngUAgEBwaIng6Bmw+eID08cdM5PNIkkR5fZ1yocDsuXNH7ZpAIBAIBC8cYttuxGnUamirq0xYFrIs\nI0kSectirFxma339yQaeUxzHodVqEQ3Q1kMgEAgEgsNErDyNOLXVVWZNE5rNruMJXae8sQHT00fk\n2dFgt9uUbtzAKpVQEwkqqoo+P09hdvbJJwsEAoFAcAgIqYIR90Oq1cDzoFLpeU6Oov7X85i9x0HH\nh2FI6b33mNc0cBywLLKeR/36dbZbLfKTk4fjy4jcT0Kq4FHDI3JfQzxpA6cExmBD40ggwOj8HI+j\nH8O0PTp+DF6VB/GkDUbl4yikCkZ17BH7oUxP4xeLqGNjkEzuHY+iiCiRONjGMXqPg47fXltjIpkE\nTesc2Lke6WSSlVoNTpyAoM9koevxfRmB+0lIFfQzPBr3dRxpg1wLUOP4PRo/82HaHhU/hml7JPyI\nKWvQsR1j7Gh8HI9EqkBs2404+dlZ1jc2mIsipIeOr9s2+ZdeOjK/jgKv2cTYDZweQfYCNqLPAAAb\nvklEQVQ8+MEP4J/+qffJX/iF/QBKEJswDFnZWmHL2wIgr+aZLcwiyyJlUiAQvJiI4GnEUVWVyVdf\nZfX995EdB8KQMJUid/kypmUdtXvPFNWy8CoVNLX3tg01rbO92W4fgWfPL2EY8tHKR2hTGpreCVzX\n3DVKKyWuzF0RAZRAIHghEcHTMUDXdeYuXCBKpwGQpM4alG3bVNbXkSSJselpDGPAxIpjSn56mvWl\nJbLtNu31ddRcjkw+j+P76HNzsLx81C4+d6xtreFOuST0/TwITdfwpjzWttaYm5g7Qu8EAoHgaBDB\n0zFiN2gCWLt9G71YZHJnO2p7dZXy9DTTp04dlXtDJ4oiGr5P8/ZtZlyXqNnk2v37mG+9xVkRPA2F\nbW97b8XpYTRdY8vbYo54wVMYhtTLneKH1FgW5VC8FAgEgmeLCJ6OIZWtLVKlEmnT3DtWsCyq6+vU\ncjkyz+lWysbNm/z/7d1rbBTnvcfx787evF7vru31/U5MuOQ4TpOooSf0NFQtaqSKIrWVWilpmqBy\nSUGV2lcoERIkRWpFm6hqolQKrRIp4Q1vUqjcSiE0SJBUySlJcKjxgSSAbfD9smt77zvnxYLjy67x\nrHc8s97/R0Ji14///nkY8MPMPP/n7uJilK98heDgIEmnkw0lJQyEwySTSWlatsIsc57Cu7PRGzeJ\nf3EdH2ABRlQVR1k53rocPL0phBArSFoV5GGOqcuXqU8kIB6fM8QH3Lh8Ga/fn3VtI8aqqoqqqiij\noxnHJJNJrDduoNyaMBaHwyjFxVjCYcqjUca/+IJytxs2blz4ybHY0s87Dbk1j9U43gytChx2B8Np\nltrHojFq7bUEWHhcp9O0H5ianEK5cJHaWc/puYCJC50Ek8V4lrL8xSx/d/WsraUFAtpaG5hn+bw5\ncuhZO39zLH1lnpa2BmD4j5msx2eSk8nTgQMHOHr0KKqqsnPnTp5//vnMg82wVjHP11cqLhdk6Kxt\nsVqhoiIvvsdoNMrQ5csowSAKEE8m8VVUUJLmcxKxGDa3m4npaSKDg9gCARLBIHi9lNbUEHc4oLUV\n2trSf7FAwHR/jndihlYFngoPI70j2Kvs2J2p23exSIySwRLurr8bJc31vrLYwtqhazdY46yAeZMq\nr6eGvokJPA0NSwxtkvNap9paWiDMKq5hpAmWz5soh5618zKHxtYGms/U/PoneFHLnjwdPXqU+vp6\nTp8+zcmTJ9m/fz8bNmzgscceW366VWIqGGT8+nWUUIikouCorqby1sPfWXG7SQYCC1Y6JRIJLMup\nu4ISiQQDn3xCg82G5fbtx6kpBi5exHrffQs2Prbb7QwGAjQNDqae83I6wW4nPjnJZ5cv03jPPQZ8\nF6ufxWLhvxr+i6mRKUZGUq0KqhxV1NTXaFppZ4nFMn5MmXcFVQghzG7Zk6dEIsGePXsA2LhxIx0d\nHZw9e1YmT7cEJyYI/+c/1LtccGuJffjGDfoUhfoHH8yqpr+pif7z51PbtszSH49T1dSUF8v1R/v7\nqWbuQ/AA1S4XfVevUp9mMpRUVRLzrripQNyi7dkboY3FYqGuoo46st8CR3U6UaemFvx5q6qKOu88\nFkIIs1v2M7a7d++e87qmpobm5ublll01Al98QeW8fkxFdjuu8XFCWU5yHA4HZe3t9Nls9IfD3AyH\n6bPb8be3Y8/QRNJs4oEAjkwNL8PhBe/FYjFqfD6S9fX0JZMMRKPciMUY9nhYt3Ytk4s8LyWMV97U\nxECaP9ehcJiyxkYDEgkhRPZy/sB4d3c3L7zwQq7L5qVEIoE9FII0zSxLHQ6GBgdxZTnRdBUXU9/W\nhnrrSsz8/9Gbns2GGg6nza2muR1ktVqJWyxUlJdTVl5OMhhEuXWLMhSNYi+whqH5pqioCPc999B7\n5QrF0SgWi4VphwPP3XcvuEUrhBBml9PJ04kTJ9i1axd1i+xwf/C3v535/ZbNm9ny9a/nMoKpWCwW\nkhkmNYlkEiUHV4nybtJ0i6+ujtELF/DPm/SEYrFUw8t5FEUhWVpKYnISq9U653mbUaC2vFzvyGKZ\nPD4fngcfJHzrClRZUZG2VZBCCKGzs2ff5dy5d2deb936P2nHLTp56unp4YEHHsj48e3bt3P06FEA\n+vr66Ozs5Nlnn1002MGnn577RqZ/PPNxXeO8sQqQUBTUyckFk5yR4WEq7r3X+NYNetZeZGwxMO33\nM9DTg99uR7FYGB8aItzSQl1JSdrjUl1VxY2REUrDYUqmp4nG4wwnEvjWrUOZnLxjFlVVCUciKBbL\n4t3YTXKszdCqQOtYAGeaVgWzzTzhFI2a5libprbWHBpaG2hpawDmOZ/ysXZh5NC24bCW1gZG/tVt\nb99Ce/uWmddXrryTdtyik6fGxkaGhobuGCYYDPL666/PmTjFYrH0z9+YYa3iCi5JrvzKV+i9cIEq\nVcVpt5NMJhmJRHC0t2PTerXEpN9jtmMrvF5ia9YwOjBAMh7Ht3495VVVGcdbgcaHHyYwMcHA9evY\nKyuprapCUZQ73r4cHRwkdPky7liMBDBUVIR//frMt4xMcKzN0Kogm7HWktRnLL248cfaVLU1jNXe\n2iD/zqd8rb3qc2hsa5CqrWGsSf7qZrLs23bRaJT9+/eza9cuLl26hKqqnD59mkcffZTW1tblJ8xz\nDoeD+gceYLS/n9FgEGw2yurrKYpGjY5mCna7narbPX6WeBXO6/PhbW4Gr5dIOMzwZ5+hBINYgITb\nTXlr65xJUWBsDMu1a9T7/TMrHgH6OjupfvBBbGk2GhZCCCEyWfZPjR07dnDs2DFeeeWVmfcefvhh\n9u7du9zSq4aiKFTMfw6sACZP0WiU4f/7v9SkSFFQfD4qW1qwWnOzo1ksFmPo449pKCqC28vdEwlu\nXLiAcv/9M7fmgj091KdZDl9ltTJ68yZVstpLCCGEBstuVfDGG2+QTCbn/Dp79mwusok8FovFGLxw\ngdqpKepsNuoUhcrxcfo++YRkcpEHYjQY6emhNs2t4RqHg9GenpnXSoaJqt1mIzE1lZMsQgghCofc\nr1gFkskkowMDxAKB1G1Brxej2w4OX7tGnd0+5xkkq9VKdSzGaH//witxWVCnp9NexVIUBWZNipIZ\nrnQlEgksDseycwghhCgssjFwnueIxWL0f/oplapK0e0H0j/+mKl778VfU5P7LEvd7PfmTZRbt+tm\ncwIjvb1QUrLsHGoolPH2p2q1zpxrRSUlTF29invew+hD4TDlzc0Lz0mznE8m2SQ216vt5hY3ybE2\nS205n1ZFbcmRbrw+mw7n9cbAmphghUo+rqrJNH7wP/+hweuducKjAJWKQv/ICLE1a5becTzXuT2e\n1MTJ7SYciRCLRHAUFeG8vS9dphoacpT4/Ux0deGb9zzTZCSCq7V1ppbf62UgEmFychKfopBIJhlX\nFDz33IOjrGzZOfQ6n8y0SaystlvB2nI+rYrakmMeHTcdzsvVdmKuZDJJJBLBZrPpvlWKqqoogcCX\nG+vO4rfbGR8cpDJNw8mVYPP7mR4dJdDXR3EkgsNiIayq9NpslG3dmpOv4fX5GKipIXrzJuUOBxaL\nhbFIhGhVFbUVFXPGVjc1ES8uJjg+jmKzUefz5W2DUSGEEMaSyVMODfb2Ep+cpDiRIKiqRL1eqtev\n120Spapqxif+rYpCwsAVfZUNDfzvmTNsUFU8t1a9RcJhHC4XocFBmDe5yVZ1SwuR2lqG+/tRVZXS\nmhr8GTaatdlslOXo6wohhChcMnnKkaG+PtwDA7hn3QZKRqP0dXbSuEiX9uVQFIV4honCRDSKd5GG\nk3oLh8PcVV1NwuHgxtgYWCx46upoLClhaGKCaDSK4/bD2skkTEzA9DQkZl3WtVqXdH3V6XRSLZtR\nCyGEWCEFPXlKJBIMXr2KOjEBqgpeL5UtLVldKYrevEnlvJVbiqJQGokQGB/HW1qaq9hzeNesYfDi\nRapmNYWMxONMlZdT5nbr8jWXIhqJ4LJaKfb5KPX55nysCOZOniIReOMNGB9PPQ912/33Q45u8Qkh\nhBC5suw+T/kqmUxy4+OPqRofp05RqLNaqQkG6f/4Y+LxuKZa8XgcRyyW9mNuu53QxEQuIqfl8flw\n33svfTYbN2Mx+pJJJqqqqN+wQbevuRRFLhfTGfo5hYCi+VfMVDX9LyGEEMJkCrZVwfCNG1QHg1hn\nXWVSgLpEgqGuLmpu3wZaQm2rqhILh1O3neaJRKOpFV3LWQ5/h/FuwN3UNHdsMJiT2tmOdQLDySTx\nQADbrD5LsUSCeEkJttnHKhpNXX2af/wikdxsHK11vFmWlmusrWUjYWlVYNLaZskBum06bK7l86u7\nRYBZcmivrU9bA5BWBcseG79+HUeaW2lWIJlIzK13h9oWQGlqItrbSxwIBQJYnU68paUM2+00tLRA\nupVdGjLHYjHGg0HUZBJfVdXM1iMZmWDZde1DD3Gzvx/72BhFQMhiIVFZSe3dd889HqFQ6nZdcfHc\n23aLtTTQmlnreBMsLdc6VutGwtKqwKS1TZJDz02HTbN8XsfakmMZ43VsawDSqmB5Flumrmi/m1nZ\n0sJHH35IxeQk1U4nU/E4H12/TuOjjy57SfxQby/J7m7KfT4Ui4Wx3l5Gq6qoNfnGy4qiUL9hA/F4\nnEgkgt/plE14hRBC5L2C/Unmqq5m6rPPcM+7ghOJxXBk0Rtp4PPPub+ujnhREVOTkzgdDh4sKaHv\n2jWSVVWpLUOyMDU5ibW3l8qiIrg18ahwuZgaHmbU46HcwBV1S2Wz2RafNFmtsGlT6rbd7D8Pv1//\ncEIIIYRGBTt5KquooG9khOT4+EwfoqlIhFG3m4baWk21VFXFMjqK1WrF6nDgLC+f+ZhfURgbGsJf\nX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"text": [ "" ] } ], "prompt_number": 21 }, { "cell_type": "markdown", "metadata": {}, "source": [ "You do it for 35 now..see what happens?" ] }, { "cell_type": "code", "collapsed": false, "input": [ "#your code here\n", "clf = KNeighborsClassifier(35, warn_on_equidistant=False).fit(Xtrain, ytrain)\n", "points_plot(Xtr, Xtrain, Xtest, ytrain, ytest, clf)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "SCORE 0.939130434783\n" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 22, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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DZ2EhycLC0+UKVasNPvigSTI5h++7XLu2geuOMD3toShZOh2fYrHO9HRuaEtN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\nzEcfwYcfhj8/7N2UTsPHP96rtb4O9+5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KBIIdLSPbpqcODrRXVv7dv9t53Gq1x/aZhsSD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"text": [ "" ] } ], "prompt_number": 22 }, { "cell_type": "markdown", "metadata": {}, "source": [ "We now start splitting data even more in a strange way. Why do we need to do this?" ] }, { "cell_type": "code", "collapsed": false, "input": [ "Xcv,Xte,ycv,yte=train_test_split(Xtest, ytest, train_size=0.5)\n", "print ytrain.shape, ycv.shape, yte.shape\n", "trscores=[]\n", "cvscores=[]\n", "ns=np.arange(1,80,1)\n", "ones=np.ones(len(ns))\n", "for n in ns:\n", " clf = KNeighborsClassifier(n, warn_on_equidistant=False).fit(Xtrain, ytrain)\n", " trscores.append(clf.score(Xtrain, ytrain))\n", " cvscores.append(clf.score(Xcv, ycv))\n", "plt.plot(ns, ones-trscores, label=\"training\")\n", "plt.plot(ns, ones-cvscores, label=\"cv\")\n", "plt.legend(loc='upper left');\n", "print clf.score(Xte, yte)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "(172,) (57,) (58,)\n", "0.775862068966" ] }, { "output_type": "stream", "stream": "stdout", "text": [ "\n" ] }, { "metadata": {}, "output_type": "display_data", "png": 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htmlOa8fN27xtlZKS4jL1uMptK1epxxVujx8/3qXqcaXbVq5SjzNvf7V7J9DL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\nc8TLurA+tmnEy7bGy02nGjm3LsZc5JiJmDWXgqq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"text": [ "" ] } ], "prompt_number": 23 }, { "cell_type": "markdown", "metadata": {}, "source": [ "This is the same graph we saw earlier, but rversed..k=1 is high variance!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### train/validate/test\n", "\n", "If you fit hyperparameter by finding the lowest test set error, you can ask\n", "how well this model generalize. But this is not likely to be a fair estimate of how well this model generalizes. It is likely to be an optimistic estimate as d is fit to the test set.\n", "\n", "So do a 3 way split to train/cv/test and pick hypothesis with lowest cross-validation error. But this might be hard if we didnt have that large a data set.\n", "\n", "Practically what we do is to nest our cross-validation inside a grid search. Remember, our hyperparameter fit is also a fit!, and thus the X_cv serves as its \"data\". Thus we need this nesting and 3 way split. Or you would be testing the hyperparameter fit on its own \"training\" set." ] }, { "cell_type": "code", "collapsed": false, "input": [ "Xtrain, Xtest, ytrain, ytest = train_test_split(X, y, train_size=0.8)\n", "Xtr=np.concatenate((Xtrain, Xtest))" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 24 }, { "cell_type": "code", "collapsed": false, "input": [ "from sklearn.grid_search import GridSearchCV\n", "from sklearn.metrics import classification_report\n", "parameters = {\"n_neighbors\": np.arange(1,80,1)}\n", "clf = KNeighborsClassifier(warn_on_equidistant=False)\n", "gs = GridSearchCV(clf, param_grid=parameters, cv=10)\n", "gs.fit(Xtrain, ytrain)\n", "#print gs.grid_scores_\n", "print gs.best_params_, gs.best_score_\n", "y_true, y_pred = ytest, gs.predict(Xtest)\n", "print(classification_report(y_true, y_pred))" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "{'n_neighbors': 31} 0.94039408867\n", " precision recall f1-score support\n", "\n", " 1 1.00 1.00 1.00 3\n", " 2 1.00 0.70 0.82 10\n", " 3 0.94 1.00 0.97 45\n", "\n", "avg / total 0.95 0.95 0.94 58\n", "\n" ] } ], "prompt_number": 25 }, { "cell_type": "code", "collapsed": false, "input": [ "points_plot(Xtr, Xtrain, Xtest, ytrain, ytest, gs)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "SCORE 0.948275862069\n" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 26, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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NDv5WajZb3Lu3wd2761Srg6eQTNPk7bdzKMoq7XaBdnsLRVnjxo001mEjJ0E4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\nNZ8QQoidS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"text": [ "" ] } ], "prompt_number": 26 }, { "cell_type": "markdown", "metadata": {}, "source": [ "We've seen the interplay of bias and variance, and we've seen how hyperparameter, here d and k must be fit by cross-validation, using a nested scheme. \n", "\n", "See Chris's notebook for bad consequences that might arise otherwise! \n", "\n", "(http://nbviewer.ipython.org/urls/raw.github.com/cs109/content/master/lec_10_cross_val.ipynb)\n", "\n", "We'd touched on regularization last time, and will revisit regularization next time in the bayesian scheme, and see how regularization parameters control bias and variance.\n", "\n", "Finally, we'll put all this together to come up with a strategy for evaluating classifiers and improving our predictions, using this notion of the bias-variance tradeoff, and hyperparameter estimation." ] } ], "metadata": {} } ] }