{ "cells": [ { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "# Random Forest classifiers\n", "\n", "In this section of the tutorial, we will investigate the use of Random Forest classifiers in `sklearn`. As for all models in the `sklearn` framework, Random Forests mainly rely on `fit(X, y)` and `predict(X)` methods. Once fitted, relative importance of the features can be accessed _via_ the `feature_importances_` property.\n", "\n", "More information about the use of Random Forests for Classification in `sklearn` can be found at: .\n", "\n", "To begin with, let us import libraries we need and define a function to plot a fitted classifier (this function will not be specific to Random Forests) in 2D." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "%matplotlib inline\n", "\n", "from sklearn.ensemble import RandomForestClassifier\n", "from sklearn.datasets import make_circles\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", "def plot_decision(clf, X, y):\n", " # Build a 2D grid and perform classification using clf on this grid\n", " xx, yy = np.meshgrid(np.arange(X[:,0].min() - .5, X[:,0].max() + .5, .01),\n", " np.arange(X[:,1].min() - .5, X[:,1].max() + .5, .01))\n", " zz = clf.predict(np.c_[xx.ravel(), yy.ravel()]).reshape(xx.shape)\n", " plt.contourf(xx, yy, zz, alpha=.2)\n", " # Plot data\n", " plt.scatter(X[:, 0], X[:, 1], c=y, s=40)\n", " # Set figure coordinate limits\n", " plt.xlim(X[:,0].min() - .5, X[:,0].max() + .5)\n", " plt.ylim(X[:,1].min() - .5, X[:,1].max() + .5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Then, we load some data and train a forest made of a single tree (`n_estimators=1`):" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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JrK4SGBDAzoULCT17ltsxMVQrV86lSwS0qFuX46tWcSoiAp1WS6mAgP/8tNOq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\nIXiMtMV7+VJ7pC3eqarbUuuSuzvLS9UW0hbv5UvtkbZ4p6p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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "X, y = make_circles(n_samples=100, random_state=0, noise=.1, factor=.6)\n", "clf = RandomForestClassifier(n_estimators=1)\n", "clf.fit(X, y)\n", "plot_decision(clf, X, y)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, if we vary the number of trees in the model, things can change a little bit:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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HHyYyduwIVqz4Cbv9unq0XtGsWQeU2p5maywOxzEaN25NdPRZ3nlnEBERpYiI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ymUkiWrMHr0bNzc4q9PWtaMGRnz66/xJu97wkGlIpmTEyFaLR9bIgvw0mT6qrXTnYcPmb1iBVdv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\n2LAHmTt3kyYLK128eI6BA9uQmFgZh6MBEM+hQ+PYtWsrr7zy6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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(15, 5))\n", "for i, n_trees in enumerate([1, 10, 100]):\n", " plt.subplot(1, 3, i + 1)\n", " clf = RandomForestClassifier(n_estimators=n_trees)\n", " clf.fit(X, y)\n", " plot_decision(clf, X, y)\n", " plt.title(\"%d tree(s)\" % n_trees)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Once a model fitted, we can have a look at relative importance of the different features:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([ 0.52747471, 0.47252529])" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "clf.feature_importances_" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To get an idea, we can add random components and see what happens:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 0.01904568 0.09171014 0.11415525 0.12332016 0. 0.11732331\n", " 0.07057143 0.07285714 0.10031884 0.10500781 0.18569024 0. ]\n" ] } ], "source": [ "X, y = make_circles(n_samples=100, random_state=0, noise=.1, factor=.8)\n", "X = np.hstack((X, np.random.randn(100, 10)))\n", "clf = RandomForestClassifier(n_estimators=1)\n", "clf.fit(X, y)\n", "print(clf.feature_importances_)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Surprisingly enough, first 2 dimensions do not seem to be the most informative. This is because we do not have sufficient amount of data to assess feature importance. If we add some:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "100 [ 0. 0.06123426 0.03619321 0.16778742 0.0317675 0.19332414\n", " 0. 0.32911261 0. 0.03648969 0.0790939 0.06499726]\n", "1000 [ 0.25272982 0.22444649 0.06011106 0.04157876 0.05531609 0.04779058\n", " 0.05020186 0.06180678 0.02339828 0.03804851 0.08905098 0.05552079]\n", "10000 [ 0.28151625 0.24462119 0.04144543 0.04638612 0.05330028 0.05210088\n", " 0.04936459 0.04543707 0.05635139 0.04343161 0.04420838 0.04183681]\n" ] } ], "source": [ "for n in [100, 1000, 10000]:\n", " X, y = make_circles(n_samples=n, random_state=0, noise=.1, factor=.8)\n", " X = np.hstack((X, np.random.randn(n, 10)))\n", " clf = RandomForestClassifier(n_estimators=1)\n", " clf.fit(X, y)\n", " print(n, clf.feature_importances_)" ] } ], "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": "3.4.3" } }, "nbformat": 4, "nbformat_minor": 0 }