{ "metadata": { "name": "", "signature": "sha256:86214db6abbbbf960bb48dae9c8803d01cbca5bdce57903fb933fe8e77e7affb" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "code", "collapsed": false, "input": [ "from sklearn import datasets, svm, metrics, cross_validation\n", "from matplotlib import pyplot as pl\n", "import numpy as np\n", "import pickle\n", "%matplotlib inline\n", "%run util.py" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 1 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Carregando os dados" ] }, { "cell_type": "code", "collapsed": false, "input": [ "digitos = datasets.load_digits()" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 2 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Imagem como matriz de 64 pixels(8x8)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "> Data in scikit-learn, with very few exceptions, is assumed to be stored as a two-dimensional array, of size [**n_samples, n_features**]." ] }, { "cell_type": "code", "collapsed": false, "input": [ "digitos.data.shape" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 3, "text": [ "(1797, 64)" ] } ], "prompt_number": 3 }, { "cell_type": "code", "collapsed": false, "input": [ "digitos.data[5]" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 4, "text": [ "array([ 0., 0., 12., 10., 0., 0., 0., 0., 0., 0., 14.,\n", " 16., 16., 14., 0., 0., 0., 0., 13., 16., 15., 10.,\n", " 1., 0., 0., 0., 11., 16., 16., 7., 0., 0., 0.,\n", " 0., 0., 4., 7., 16., 7., 0., 0., 0., 0., 0.,\n", " 4., 16., 9., 0., 0., 0., 5., 4., 12., 16., 4.,\n", " 0., 0., 0., 9., 16., 16., 10., 0., 0.])" ] } ], "prompt_number": 4 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Imagem" ] }, { "cell_type": "code", "collapsed": false, "input": [ "show_digits_plots(digitos, 0, 9)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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HgK1b9e+T2RobDeCmm+w+kypnLlsjFAXbmAUIOfNRzmo10ln195NJlW0bMRQE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BxrbUOVnA8OknfNRkGQ6mq3lDOVd89V5cyVmLWlnJnEWpxyppJz1tg40tnglTNzRJKzCy64AFOm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\ny++60GCeObP0M9WCIKoIT9Br165VbyQCsjFLsW1bcrbGPChnc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"text": [ "" ] } ], "prompt_number": 5 }, { "cell_type": "code", "collapsed": false, "input": [ "show_digits(digitos, 0, 9)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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"text": [ "" ] } ], "prompt_number": 6 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Parti\u00e7\u00e3o dos dados" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Realiza-se um split randomico dos dados, com 60% dos dados para treino e 40% para teste." ] }, { "cell_type": "code", "collapsed": false, "input": [ "X_train, X_test, y_train, y_test = cross_validation.train_test_split(digitos.data,\n", " digitos.target,\n", " test_size=.4)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 8 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Treinamento do modelo" ] }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "O Scikit-learn fornece um conjunto de modelos, com uma interface com os seguintes m\u00e9todos:" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "- **Presentes em todos estimators:**\n", " - **fit():** \u00e9 o m\u00e9todo para o qual \u00e9 passado o dataset. No caso dos supervised estimatores, possui dois par\u00e2metros, o primeiro sendo os features, o segundo sendo os labels/target.\n", "- **Presentes nos supervised estimators:**\n", " - **predict():** ap\u00f3s treinado, retorna os labels para o conjunto de features passado.\n", " - **predict_proba():** retorna a probabilidade para cada label, em modelos probabil\u00edsticos.\n", " - **score():** retorna um valor de 0 a 1 representando qu\u00e3o boa \u00e9 a predi\u00e7\u00e3o.\n", "- **Presentes nos unsupervised estimators:**\n", " - **transform():** lembrar do PCA. Apenas transforma, usando os par\u00e2metros do modelo.\n", " - **fit_transform():** lembrar do PCA. Ajusta os par\u00e3metros do modelo aos dados e os transforma." ] }, { "cell_type": "code", "collapsed": false, "input": [ "model = svm.SVC(gamma=0.001, C=100.0)\n", "model.fit(X_train, y_train)\n", "\n", "pickle.dump(model, open('model', 'w'))" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 9 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Testando o modelo" ] }, { "cell_type": "code", "collapsed": false, "input": [ "y_predito = model.predict(X_test)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 10 }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "M\u00e9tricas de classifica\u00e7\u00e3o" ] }, { "cell_type": "code", "collapsed": false, "input": [ "print metrics.classification_report(y_test, y_predito)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ " precision recall f1-score support\n", "\n", " 0 1.00 0.99 0.99 73\n", " 1 0.97 1.00 0.99 68\n", " 2 1.00 1.00 1.00 73\n", " 3 1.00 1.00 1.00 74\n", " 4 0.99 1.00 0.99 78\n", " 5 1.00 0.97 0.99 69\n", " 6 1.00 0.99 0.99 68\n", " 7 1.00 1.00 1.00 74\n", " 8 0.96 0.96 0.96 70\n", " 9 0.96 0.97 0.97 72\n", "\n", "avg / total 0.99 0.99 0.99 719\n", "\n" ] } ], "prompt_number": 11 }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "Matriz de confus\u00e3o" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Matriz cujas colunas representam as classes preditas, e as linhas as classes reais" ] }, { "cell_type": "code", "collapsed": false, "input": [ "cm = metrics.confusion_matrix(y_test, y_predito)\n", "\n", "cms = np.zeros((11, 11))\n", "cms[0, :] = np.arange(-1, 10, 1)\n", "cms[:, 0] = np.arange(-1, 10, 1).reshape((11,))\n", "cms[1:, 1:] = cm\n", "print cms" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "[[ -1. 0. 1. 2. 3. 4. 5. 6. 7. 8. 9.]\n", " [ 0. 72. 0. 0. 0. 1. 0. 0. 0. 0. 0.]\n", " [ 1. 0. 68. 0. 0. 0. 0. 0. 0. 0. 0.]\n", " [ 2. 0. 0. 73. 0. 0. 0. 0. 0. 0. 0.]\n", " [ 3. 0. 0. 0. 74. 0. 0. 0. 0. 0. 0.]\n", " [ 4. 0. 0. 0. 0. 78. 0. 0. 0. 0. 0.]\n", " [ 5. 0. 0. 0. 0. 0. 67. 0. 0. 0. 2.]\n", " [ 6. 0. 0. 0. 0. 0. 0. 67. 0. 1. 0.]\n", " [ 7. 0. 0. 0. 0. 0. 0. 0. 74. 0. 0.]\n", " [ 8. 0. 2. 0. 0. 0. 0. 0. 0. 67. 1.]\n", " [ 9. 0. 0. 0. 0. 0. 0. 0. 0. 2. 70.]]\n" ] } ], "prompt_number": 12 }, { "cell_type": "code", "collapsed": false, "input": [ "show_confusion_matrix(cm)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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GpKWliWySiFyhrZx2NGzYMFRVVYlsgohag4LmxPjYERGpmoJGtkSkGgqqHApKhYhUQ0GV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\nViEkJARhYWFYuHB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"text": [ "" ] } ], "prompt_number": 13 }, { "cell_type": "code", "collapsed": false, "input": [], "language": "python", "metadata": {}, "outputs": [] } ], "metadata": {} } ] }