{ "cells": [ { "cell_type": "code", "execution_count": 40, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# imports and setup\n", "%matplotlib inline\n", "\n", "import numpy as np\n", "import pandas as pd\n", "\n", "import seaborn as sns\n", "import matplotlib.pyplot as plt\n", "\n", "pd.set_option('precision', 4) # number precision for pandas\n", "pd.set_option('display.max_rows', 12)\n", "pd.set_option('display.max_columns', 12)\n", "pd.set_option('display.float_format', '{:20,.5f}'.format) # get rid of scientific notation\n", "\n", "plt.style.use('seaborn') # pretty matplotlib plots" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 8.3.1 Fitting Classification Trees" ] }, { "cell_type": "code", "execution_count": 41, "metadata": { "collapsed": true }, "outputs": [], "source": [ "carseats = pd.read_csv('../datasets/Carseats.csv', index_col=0)\n", "carseats['High'] = (carseats['Sales'] > 8).map({True: 'Yes', False: 'No'})\n", "carseats.loc[:, ['ShelveLoc', 'Urban', 'US', 'High']] = \\\n", "carseats.loc[:, ['ShelveLoc', 'Urban', 'US', 'High']].apply(pd.Categorical)" ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from sklearn.preprocessing import OneHotEncoder, LabelEncoder\n", "\n", "le = LabelEncoder()\n", "carseats['ShelveLoc'] = le.fit_transform(carseats['ShelveLoc'])\n", "carseats['Urban'] = le.fit_transform(carseats['Urban'])\n", "carseats['US'] = le.fit_transform(carseats['US'])\n", "\n", "X = carseats.loc[:, 'CompPrice':'US']\n", "y = carseats.loc[:, 'High']" ] }, { "cell_type": "code", "execution_count": 43, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/plain": [ "0.87749999999999995" ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.tree import DecisionTreeClassifier, export_graphviz\n", "\n", "tree_carseats = DecisionTreeClassifier(min_samples_leaf=5, max_depth=6)\n", "tree_carseats.fit(X, y)\n", "y_pred = tree_carseats.predict(X)\n", "\n", "tree_carseats.score(X, y)" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAecAAAF5CAYAAAClYeJnAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Feature Importance\n", "\n", "# (pd\n", "# .DataFrame({'Importance': tree_carseats.feature_importances_ * 100}, index=X.columns)\n", "# .sort_values('Importance', ascending=True, axis=0)\n", "# .plot(kind='barh', title='Feature Importance'));\n", "\n", "from scikitplot.estimators import plot_feature_importances\n", "\n", "plot_feature_importances(tree_carseats, \n", " feature_names=X.columns,\n", " x_tick_rotation=45);" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [ { "data": { "image/svg+xml": [ "\n", "\n", "\n", "\n", "\n", "\n", "Tree\n", "\n", "\n", "0\n", "\n", "Price ≤ 92.5\n", "gini = 0.484\n", "samples = 400\n", "value = [236, 164]\n", "class = No\n", "\n", "\n", "1\n", "\n", "ShelveLoc ≤ 0.5\n", "gini = 0.35\n", "samples = 62\n", "value = [14, 48]\n", "class = Yes\n", "\n", "\n", "0->1\n", "\n", "\n", "True\n", "\n", "\n", "12\n", "\n", "Advertising ≤ 6.5\n", "gini = 0.451\n", "samples = 338\n", "value = [222, 116]\n", "class = No\n", "\n", "\n", "0->12\n", "\n", "\n", "False\n", "\n", "\n", "2\n", "\n", "Income ≤ 58.0\n", "gini = 0.499\n", "samples = 19\n", "value = [10, 9]\n", "class = No\n", "\n", "\n", "1->2\n", "\n", "\n", "\n", "\n", "7\n", "\n", "Population ≤ 198.5\n", "gini = 0.169\n", "samples = 43\n", "value = [4, 39]\n", "class = Yes\n", "\n", "\n", "1->7\n", "\n", "\n", "\n", "\n", "3\n", "\n", "gini = 0.0\n", "samples = 7\n", "value = [7, 0]\n", "class = No\n", "\n", "\n", "2->3\n", "\n", "\n", "\n", "\n", "4\n", "\n", "Advertising ≤ 9.5\n", "gini = 0.375\n", "samples = 12\n", "value = [3, 9]\n", "class = Yes\n", "\n", "\n", "2->4\n", "\n", "\n", "\n", "\n", "5\n", "\n", "gini = 0.5\n", "samples = 6\n", "value = [3, 3]\n", "class = No\n", "\n", "\n", "4->5\n", "\n", "\n", "\n", "\n", "6\n", "\n", "gini = 0.0\n", "samples = 6\n", "value = [0, 6]\n", "class = Yes\n", "\n", "\n", "4->6\n", "\n", "\n", "\n", "\n", "8\n", "\n", "Age ≤ 56.5\n", "gini = 0.36\n", "samples = 17\n", "value = [4, 13]\n", "class = Yes\n", "\n", "\n", "7->8\n", "\n", "\n", "\n", "\n", "11\n", "\n", "gini = 0.0\n", "samples = 26\n", "value = [0, 26]\n", "class = Yes\n", "\n", "\n", "7->11\n", "\n", "\n", "\n", "\n", "9\n", "\n", "gini = 0.0\n", "samples = 10\n", "value = [0, 10]\n", "class = Yes\n", "\n", "\n", "8->9\n", "\n", "\n", "\n", "\n", "10\n", "\n", "gini = 0.49\n", "samples = 7\n", "value = [4, 3]\n", "class = No\n", "\n", "\n", "8->10\n", "\n", "\n", "\n", "\n", "13\n", "\n", "CompPrice ≤ 144.5\n", "gini = 0.312\n", "samples = 181\n", "value = [146, 35]\n", "class = No\n", "\n", "\n", "12->13\n", "\n", "\n", "\n", "\n", "34\n", "\n", "ShelveLoc ≤ 0.5\n", "gini = 0.499\n", "samples = 157\n", "value = [76, 81]\n", "class = Yes\n", "\n", "\n", "12->34\n", "\n", "\n", "\n", "\n", "14\n", "\n", "Age ≤ 50.5\n", "gini = 0.242\n", "samples = 156\n", "value = [134, 22]\n", "class = No\n", "\n", "\n", "13->14\n", "\n", "\n", "\n", "\n", "27\n", "\n", "Price ≤ 151.5\n", "gini = 0.499\n", "samples = 25\n", "value = [12, 13]\n", "class = Yes\n", "\n", "\n", "13->27\n", "\n", "\n", "\n", "\n", "15\n", "\n", "Price ≤ 100.5\n", "gini = 0.387\n", "samples = 61\n", "value = [45, 16]\n", "class = No\n", "\n", "\n", "14->15\n", "\n", "\n", "\n", "\n", "20\n", "\n", "Income ≤ 102.5\n", "gini = 0.118\n", "samples = 95\n", "value = [89, 6]\n", "class = No\n", "\n", "\n", "14->20\n", "\n", "\n", "\n", "\n", "16\n", "\n", "gini = 0.278\n", "samples = 6\n", "value = [1, 5]\n", "class = Yes\n", "\n", "\n", "15->16\n", "\n", "\n", "\n", "\n", "17\n", "\n", "CompPrice ≤ 131.5\n", "gini = 0.32\n", "samples = 55\n", "value = [44, 11]\n", "class = No\n", "\n", "\n", "15->17\n", "\n", "\n", "\n", "\n", "18\n", "\n", "gini = 0.157\n", "samples = 35\n", "value = [32, 3]\n", "class = No\n", "\n", "\n", "17->18\n", "\n", "\n", "\n", "\n", "19\n", "\n", "gini = 0.48\n", "samples = 20\n", "value = [12, 8]\n", "class = No\n", "\n", "\n", "17->19\n", "\n", "\n", "\n", "\n", "21\n", "\n", "CompPrice ≤ 121.5\n", "gini = 0.072\n", "samples = 80\n", "value = [77, 3]\n", "class = No\n", "\n", "\n", "20->21\n", "\n", "\n", "\n", "\n", "24\n", "\n", "Age ≤ 63.5\n", "gini = 0.32\n", "samples = 15\n", "value = [12, 3]\n", "class = No\n", "\n", "\n", "20->24\n", "\n", "\n", "\n", "\n", "22\n", "\n", "gini = 0.0\n", "samples = 39\n", "value = [39, 0]\n", "class = No\n", "\n", "\n", "21->22\n", "\n", "\n", "\n", "\n", "23\n", "\n", "gini = 0.136\n", "samples = 41\n", "value = [38, 3]\n", "class = No\n", "\n", "\n", "21->23\n", "\n", "\n", "\n", "\n", "25\n", "\n", "gini = 0.5\n", "samples = 6\n", "value = [3, 3]\n", "class = No\n", "\n", "\n", "24->25\n", "\n", "\n", "\n", "\n", "26\n", "\n", "gini = 0.0\n", "samples = 9\n", "value = [9, 0]\n", "class = No\n", "\n", "\n", "24->26\n", "\n", "\n", "\n", "\n", "28\n", "\n", "Income ≤ 63.5\n", "gini = 0.432\n", "samples = 19\n", "value = [6, 13]\n", "class = Yes\n", "\n", "\n", "27->28\n", "\n", "\n", "\n", "\n", "33\n", "\n", "gini = 0.0\n", "samples = 6\n", "value = [6, 0]\n", "class = No\n", "\n", "\n", "27->33\n", "\n", "\n", "\n", "\n", "29\n", "\n", "gini = 0.49\n", "samples = 7\n", "value = [4, 3]\n", "class = No\n", "\n", "\n", "28->29\n", "\n", "\n", "\n", "\n", "30\n", "\n", "Advertising ≤ 3.5\n", "gini = 0.278\n", "samples = 12\n", "value = [2, 10]\n", "class = Yes\n", "\n", "\n", "28->30\n", "\n", "\n", "\n", "\n", "31\n", "\n", "gini = 0.0\n", "samples = 7\n", "value = [0, 7]\n", "class = Yes\n", "\n", "\n", "30->31\n", "\n", "\n", "\n", "\n", "32\n", "\n", "gini = 0.48\n", "samples = 5\n", "value = [2, 3]\n", "class = Yes\n", "\n", "\n", "30->32\n", "\n", "\n", "\n", "\n", "35\n", "\n", "Age ≤ 46.0\n", "gini = 0.219\n", "samples = 32\n", "value = [28, 4]\n", "class = No\n", "\n", "\n", "34->35\n", "\n", "\n", "\n", "\n", "40\n", "\n", "ShelveLoc ≤ 1.5\n", "gini = 0.473\n", "samples = 125\n", "value = [48, 77]\n", "class = Yes\n", "\n", "\n", "34->40\n", "\n", "\n", "\n", "\n", "36\n", "\n", "Price ≤ 125.0\n", "gini = 0.391\n", "samples = 15\n", "value = [11, 4]\n", "class = No\n", "\n", "\n", "35->36\n", "\n", "\n", "\n", "\n", "39\n", "\n", "gini = 0.0\n", "samples = 17\n", "value = [17, 0]\n", "class = No\n", "\n", "\n", "35->39\n", "\n", "\n", "\n", "\n", "37\n", "\n", "gini = 0.49\n", "samples = 7\n", "value = [3, 4]\n", "class = Yes\n", "\n", "\n", "36->37\n", "\n", "\n", "\n", "\n", "38\n", "\n", "gini = 0.0\n", "samples = 8\n", "value = [8, 0]\n", "class = No\n", "\n", "\n", "36->38\n", "\n", "\n", "\n", "\n", "41\n", "\n", "Price ≤ 136.5\n", "gini = 0.184\n", "samples = 39\n", "value = [4, 35]\n", "class = Yes\n", "\n", "\n", "40->41\n", "\n", "\n", "\n", "\n", "46\n", "\n", "Price ≤ 124.5\n", "gini = 0.5\n", "samples = 86\n", "value = [44, 42]\n", "class = No\n", "\n", "\n", "40->46\n", "\n", "\n", "\n", "\n", "42\n", "\n", "Income ≤ 40.0\n", "gini = 0.057\n", "samples = 34\n", "value = [1, 33]\n", "class = Yes\n", "\n", "\n", "41->42\n", "\n", "\n", "\n", "\n", "45\n", "\n", "gini = 0.48\n", "samples = 5\n", "value = [3, 2]\n", "class = No\n", "\n", "\n", "41->45\n", "\n", "\n", "\n", "\n", "43\n", "\n", "gini = 0.32\n", "samples = 5\n", "value = [1, 4]\n", "class = Yes\n", "\n", "\n", "42->43\n", "\n", "\n", "\n", "\n", "44\n", "\n", "gini = 0.0\n", "samples = 29\n", "value = [0, 29]\n", "class = Yes\n", "\n", "\n", "42->44\n", "\n", "\n", "\n", "\n", "47\n", "\n", "CompPrice ≤ 121.5\n", "gini = 0.444\n", "samples = 51\n", "value = [17, 34]\n", "class = Yes\n", "\n", "\n", "46->47\n", "\n", "\n", "\n", "\n", "50\n", "\n", "Advertising ≤ 18.5\n", "gini = 0.353\n", "samples = 35\n", "value = [27, 8]\n", "class = No\n", "\n", "\n", "46->50\n", "\n", "\n", "\n", "\n", "48\n", "\n", "gini = 0.42\n", "samples = 20\n", "value = [14, 6]\n", "class = No\n", "\n", "\n", "47->48\n", "\n", "\n", "\n", "\n", "49\n", "\n", "gini = 0.175\n", "samples = 31\n", "value = [3, 28]\n", "class = Yes\n", "\n", "\n", "47->49\n", "\n", "\n", "\n", "\n", "51\n", "\n", "gini = 0.231\n", "samples = 30\n", "value = [26, 4]\n", "class = No\n", "\n", "\n", "50->51\n", "\n", "\n", "\n", "\n", "52\n", "\n", "gini = 0.32\n", "samples = 5\n", "value = [1, 4]\n", "class = Yes\n", "\n", "\n", "50->52\n", "\n", "\n", "\n", "\n", "\n" ], "text/plain": [ "" ] }, "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from graphviz import Source\n", "\n", "tree_carseats_graph = export_graphviz(tree_carseats, \n", " out_file=None, \n", " feature_names=X.columns,\n", " class_names=tree_carseats.classes_,\n", " filled=True, \n", " rounded=True, \n", " special_characters=True)\n", "\n", "Source(tree_carseats_graph)" ] }, { "cell_type": "code", "execution_count": 46, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from sklearn.model_selection import train_test_split\n", "\n", "X_train, X_test, y_train, y_test = train_test_split(X, y, train_size=0.5, test_size=0.5, random_state=42)" ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(0.90000000000000002, 0.72999999999999998)" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tree_carseats_tt = DecisionTreeClassifier(min_samples_leaf=5, max_depth=6)\n", "tree_carseats_tt.fit(X_train, y_train)\n", "y_pred = tree_carseats_tt.predict(X_test)\n", "\n", "tree_carseats_tt.score(X_train, y_train), tree_carseats_tt.score(X_test, y_test)" ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " precision recall f1-score support\n", "\n", " No 0.81 0.71 0.75 117\n", " Yes 0.65 0.76 0.70 83\n", "\n", "avg / total 0.74 0.73 0.73 200\n", "\n" ] } ], "source": [ "from sklearn.metrics import classification_report\n", "\n", "print(classification_report(y_test, y_pred))" ] }, { "cell_type": "code", "execution_count": 49, "metadata": { "scrolled": false }, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZcAAAFnCAYAAABq9AQUAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3XtcVWXe9/HvBkQE84Sg0q3m4S5N1Kx0SsPEQ4qHxBqV\nEC1Pk2MeaxRT8XE6oTk6hmmWeURMC9F01MC8dXJmiEZLzdLHwKbCAxKJJmyO7ueP7tlPjMJG3Ju9\nln7evvZr2AvWtX7pvPz6u65rrW2x2Ww2AQDgRB7uLgAAcOshXAAATke4AACcjnABADgd4QIAcDrC\nBQDgdIQLXMZms2nt2rUaOHCg+vbtq969e2v+/Pn6+eefb2rcP/zhD3r00Ud18ODBGz732LFjGjt2\n7E1d/9dmzZql4OBg5ebmljl+6NAh3XPPPUpKSnI4xu7du3XlypXrfm/x4sV67733nFIrUJ0IF7jM\nn/70J+3evVurV69WcnKyduzYoeLiYj377LO6mdurdu3apfj4eIWEhNzwuR06dNDq1aurfO3radiw\noZKTk8sc27Vrl5o0aVKp8+Pi4soNlxdeeEFPPfXUTdcIVDfCBS6Rm5ur+Ph4LViwQI0aNZIk+fr6\nat68eRo3bpxsNpsKCws1b9489e3bV2FhYVqwYIFKS0slST179tTmzZv129/+Vo888ogWLFggSRo5\ncqSuXr2qsWPH6q9//at69uypQ4cO2a/77/clJSWaM2eO+vbtqz59+mjSpEm6cuWK0tLS1KdPH0mq\n0vWvp3v37vrLX/5if19aWqqDBw/q/vvvtx87ffq0nnrqKYWFhalPnz72n3/xxRf17bffauTIkTp0\n6JBmzZql2NhYDRo0SHv27NGsWbO0YsUKHTt2TD169FBeXp4kaeXKlZoyZcpN/zkBrkK4wCWOHj2q\nxo0bq1WrVmWO16xZUz179pSHh4fWr1+v8+fPa9euXdq2bZsOHTpU5i/pf/7zn9qyZYu2bt2qjRs3\n6vz584qPj5ckxcfH69FHHy33+n/729+UmZmpjz76SCkpKWrdurW++OKLMj9TletfT8eOHXXmzBll\nZWVJklJTU9WhQwd5e3vbf+b1119XaGio9uzZo9dee01z5sxRcXGxYmNj7f89Dz74oP38xMREhYWF\n2c/v0KGDevfurbfffltZWVnatGmT5s6dW/4fAOBmhAtcIjc3V/7+/hX+zIEDBzRs2DB5eXnJx8dH\ngwYN0t///nf79wcNGiRPT081atRI/v7+OnfuXKWv36BBA2VkZGjv3r2yWq2aNm3aNdNozrq+xWJR\n3759tWvXLkm/TIn179+/zM+sWLHCvtbzwAMPqLCwUNnZ2dcd7+GHH1bNmjWvOT59+nR99NFHevHF\nFzVx4kQFBgZW+vcDqG6EC1yifv369n/Jl+enn35S3bp17e/r1q2rnJwc+/vatWvbv/b09LRPWVVG\nhw4dNHfuXMXHx6tbt2564YUXdPnyZZddf+DAgfrLX/6ioqIipaWlqXv37mW+f/DgQY0YMUJ9+/ZV\n//79ZbPZdPXq1euO9euafs3Pz09hYWE6fPiwBg0aVP5/PGAAhAtc4r777lNOTo6++uqrMseLi4v1\n5z//WVarVQ0bNiyzyyo3N1cNGza8oet4eHiU+Uv60qVL9q/79eun+Ph47d+/X1ar9ZqFfGdc/9/a\ntWunvLw8vf/+++rcuXOZKbHi4mJNmzZNv//97+0bGywWyw1fIysrSzt37tSAAQP05ptvVqlOoLoQ\nLnCJOnXqaNy4cYqOjtZ3330nSbJarZo3b56+/vpr1apVSz169FBiYqJKS0uVn5+vDz/8sMJ1lOsJ\nCAjQyZMnJf2ypbewsFCStHXrVi1fvlySVK9ePbVs2fKac51x/V8bMGCA3nrrrWumxKxWq/Lz8xUc\nHCzpl7WeGjVqKD8/X5Lk5eV1TVd1Pa+++qrGjRun2bNna8+ePTpx4kSVawVcjXCBy0yePFnDhg3T\n73//e/Xt21dPPPGE/P397f/qHjlypBo3bqwBAwboySefVI8ePcosYlfGxIkTtW7dOg0cOFAZGRlq\n3bq1JKlXr1766quv9NhjjyksLEzp6ekaPXp0mXOdcf1fGzBggEpKStS1a9cyx/8dtOHh4QoPD1ez\nZs3Uu3dvTZgwQfn5+erXr58iIiK0e/fucsc+cOCAMjMzFRERodq1a2v69OmaO3fuDU0VAtXJwue5\nAACcjc4FAOB0hAsAwOkIFwCA0xEuAACnI1wAAE7n5e4CqqJWp0nuLgG3mINJr7q7BNyCHmxx/act\nOMPN/D1o/cL1N+GaMlwA4LZnMfbEk7GrAwCYEp0LAJhRFZ5PV50IFwAwI4NPixEuAGBGdC4AAKej\ncwEAOB2dCwDA6QzeuRi7OgCAKdG5AIAZuWhaLC8vT9HR0bp06ZKKi4v13HPPqXXr1po5c6ZKS0sV\nEBCgRYsWlfko7+shXADAjFw0LbZt2za1aNFCL7zwgrKysvT000+rU6dOioyMVFhYmJYsWaLExERF\nRkZWOA7TYgBgRhZL1V8VqF+/vnJzcyVJly9fVv369ZWWlqZevXpJkkJDQ5WamuqwPMIFAMzI4lH1\nVwUGDBigs2fPqk+fPoqKilJ0dLSsVqt9Gszf31/Z2dkOy2NaDADMyEVrLh9++KGCgoK0evVqnTx5\nUrNnzy7zfZvNVqlx6FwAAHaff/65HnnkEUlSmzZtdOHCBdWqVUsFBQWSpKysLAUGBjoch3ABADNy\n0bRY8+bNdfToUUnSmTNn5Ofnp27duik5OVmSlJKSopCQEIflMS0GAGbkot1iw4cP1+zZsxUVFaWS\nkhLNnz9frVq1UnR0tLZs2aKgoCCFh4c7HIdwAQAz8nDNmoufn5/eeOONa46vXbv2hsYhXADAjAz+\n+BfCBQDMiAdXAgCczuCdi7GrAwCYEp0LAJgR02IAAKcz+LQY4QIAZkTnAgBwOjoXAIDT0bkAAJzO\n4J2LsasDAJgSnQsAmBHTYgAApzP4tBjhAgBmRLgAAJyOaTEAgNPRuQAAnM7gnYuxow8AYEp0LgBg\nRkyLAQCczuDTYoQLAJiQhXABADgb4QIAcD5jZwvhAgBmZPTOxdjbDQAApkTnAgAmZPTOhXABABMi\nXAAATke4AACcz9jZQrgAgBnRuQAAnM7o4cJWZACA09G5AIAJGb1zIVwAwIQIFwCA8xk7WwgXADAj\nOhcAgNMRLgAApzN6uLAVGQDgdHQuAGBGLmpcPvjgA+3YscP+/vjx49q9e7dmzpyp0tJSBQQEaNGi\nRfL29q64PJvNZnNNia5Tq9Mkd5eAW8zBpFfdXQJuQQ+2qOuysRuN+6DK52a9O7RSP/fZZ59pz549\nKigoUPfu3RUWFqYlS5aocePGioyMrPBcpsUAwIQsFkuVX5W1fPlyTZw4UWlpaerVq5ckKTQ0VKmp\nqQ7PZVoMAEzI1Qv6x44dU5MmTRQQECCr1WqfBvP391d2drbD8wkXADAhV4dLYmKihgwZcs3xyq6k\nMC0GAGZkuYlXJaSlpalTp06SJF9fXxUUFEiSsrKyFBgY6PB8wgUAUEZWVpb8/PzsU2Fdu3ZVcnKy\nJCklJUUhISEOxyBcAMCEXLmgn52drQYNGtjfT548Wdu3b1dkZKRyc3MVHh7ucAzWXADAhFy55hIc\nHKx3333X/j4wMFBr1669oTEIFwAwIaM//oVwAQAzMna2EC4AYEZ0Lqg2frW8tfrlUapXx1c1vb30\n6tt79HNegV6bFq7iklIVFpVobMwG/XjxirtLhUkUWPP1xxkTlfPjBRUVFmrspBkK6dVPkpT6yT5N\neeZJ/fN0rpurvD0ZPVyqdbdYZmam2rZtq5MnT9qPJSUlKSkpqTrLuGWNfPwhnfrugvr9Lk6RM1br\nTzOe1JSoUI2N2aB+v4tT2rFvNXpIV3eXCRP5ZN9Hatu+k97ZvFuxb67V0lfnSJIKCwu07q0lahjY\n2M0VwqiqfSty69attXjx4uq+7G0hJzdPDer6SZLq3VFLObl5GjFzjf51JkeSFBRYT2cu8K9MVN5j\nA5/QqGenSpKyzp5RYJMgSdLaFYs1dOR41ahRw53l3daq49liN6Paw6Vdu3by9fW95sFn69ev1/Dh\nwzV8+HC988471V3WLeGD5MNq2ri+jn/4f7R39XS9+OdtkqQ+Xdvq2PZ5CvS/Q+/t+qebq4QZjfnt\nY5o7bbyenxur706n65sTx9W7v+N7HeA6hMt1TJ8+XUuXLrU/o8Zms2nbtm1KSEhQQkKC9uzZo++/\n/94dpZlaRP/O+uH8RQUP/qPCno3TklnDJEl7/3FCHcJf0qlvs/SH0X3cXCXMaE1iihav2qR5z/9O\nf35ltqbPec3dJcHFj3+5WW4Jl7vuukv33nuvdu/eLUm6fPmyOnbsKC8vL3l5een+++8vsy6Dynn4\nvpb6OPWEJOnLU2cUFFBX4b3us39/+74j6tqplbvKgwmd+PKIzp/NlCTdc28H5edd0bfpJxUzfbxG\nP9FbP2Zn6XcR/d1c5e2JzqUczz33nN555x2VlJTIYrGUedJmcXGxPDx4Ms2NOv1DtjoHN5ckNWtS\nX1fyC/Xi7/qpw913SpI6t79L3/wry50lwmS++OzvSnj3TUlSTvYFlZZe1bYDR7Q26WOtTfpYDQMa\n6Z3Nu91c5e3J6OHitq3IDRs2VO/evbV582ZFRUXpyJEjKikpkSQdPXpUzz77rLtKM613E/+mt+dH\nKeXdqfLy9NDkVzfr57wCvTF7uEpKr8paUKyxc9e7u0yYyBMjxuiV6MkaPyxMhQVWzXxpEf/wMwiD\n70R2730uY8aM0XvvvSdJGj58uKKiomSz2TR06FDdeeed7izNlPKsRYqKXnPN8dBnlrihGtwKfHxq\n6ZU33i33+zsOflmN1cBMqjVc/uu//ksLFiywv/fz89M//vEP+/sRI0ZUZzkAYFpGv4mSO/QBwIQM\nni2ECwCYEZ0LAMDpDJ4thAsAmJGHh7HThXABABMyeufChnUAgNPRuQCACbGgDwBwOoNnC+ECAGZE\n5wIAcDrCBQDgdAbPFsIFAMzI6J0LW5EBAE5H5wIAJmTwxoVwAQAzMvq0GOECACZk8GwhXADAjOhc\nAABOZ/BsIVwAwIyM3rmwFRkA4HR0LgBgQgZvXAgXADAjo0+LES4AYEIGzxbCBQDMiM4FAOB0Bs8W\nwgUAzMiVncuOHTv07rvvysvLS1OmTNE999yjmTNnqrS0VAEBAVq0aJG8vb0rHIOtyAAAu4sXL2r5\n8uXatGmTVq5cqX379ikuLk6RkZHatGmTmjdvrsTERIfjEC4AYEIWi6XKr4qkpqbq4YcfVu3atRUY\nGKiXX35ZaWlp6tWrlyQpNDRUqampDutjWgwATMhVs2KZmZkqKCjQhAkTdPnyZU2ePFlWq9U+Debv\n76/s7GyH4xAuAGBCrlxzyc3N1ZtvvqmzZ89q1KhRstls9u/9+uuKEC4AYEKuyhZ/f3916tRJXl5e\natasmfz8/OTp6amCggL5+PgoKytLgYGBDsdhzQUATMhVay6PPPKIPv30U129elUXL15Ufn6+unbt\nquTkZElSSkqKQkJCHNZH5wIAJuSqzqVRo0bq27evhg0bJkmaO3eu2rdvr+joaG3ZskVBQUEKDw93\nOA7hAgAoIyIiQhEREWWOrV279obGIFwAwIQ8DH6LPuECACZk8GwhXADAjHhwJQDA6TyMnS2ECwCY\nEZ0LAMDpDJ4t3EQJAHA+OhcAMCGLjN26EC4AYEIs6AMAnI4FfQCA0xk8WwgXADAjHv8CAHA6g2cL\nW5EBAM5H5wIAJmTaBf0pU6ZUWPwbb7zhkoIAAI4ZPFvKD5eoqKjqrAMAcANMu6DfpUsXSVJJSYn2\n7NmjCxcuaOzYsTp16pRatGhRbQUCAK5l7GipxIJ+TEyMTp48qY8++kiS9Nlnnyk6OtrlhQEAymex\nWKr8qg4Ow+XcuXOaMWOGfHx8JP0yXXbhwgWXFwYAKJ+HpeqvaqnP0Q8UFxfr8uXL9rTLyMhQUVGR\nywsDAJiXw63I06dP19NPP61//etf6tevnywWi1555ZXqqA0AUA7TbkX+twcffFDbtm1TTk6OPD09\nVa9eveqoCwBQAYNni+Nw2bp1q5YtW6batWtLkvLz8/X8889r4MCBLi8OAHB9pu9c1q9fr+3bt9s7\nlp9++kmjR48mXADAjUz/eS6NGzdWnTp17O/r16+vZs2aubQoAEDFTNu5LFy4UBaLRT4+PgoPD9cD\nDzwgi8WiI0eOcBMlALiZsaOlgnC5++67JUn//d//XeZ4+/btVVJS4tqqAACmVm64DBkyxP71N998\no9zcXEm/3PcSGxuroUOHur46AMB1mfbZYv82b948nT59WqdPn1aHDh10/PhxjRs3rjpqAwCUw+DZ\n4vgO/fT0dG3cuFGtWrXSypUr9cEHHygjI6M6agMAlMPozxZz2LmUlpbqypUrkn7ZhtykSROdPHnS\n5YUBAMpn9M7FYbhERUVpz549ioqK0qBBg+Tl5aWuXbtWR20AgHKYfs1l0KBB9q979uypvLw8HgED\nAG5m8GwpP1yefPLJCufmEhMTXVIQAMD8yg2XuLi46qzjhlz855vuLgG3mG6x+91dAm5Bh2NCXTa2\nae/Qv/POO6uzDgDADXC41dfNHK65AACMx7SdCwDAuEz/VORTp05pwYIFysvL05YtW7Ru3Tp17txZ\n7dq1q476AADX4apwSUtL09SpU+3Plbz77rs1btw4zZw5U6WlpQoICNCiRYvk7e1dcX2OLvTyyy9r\nzpw59oEeeeQRPuYYANzMlXfod+nSRfHx8YqPj1dMTIzi4uIUGRmpTZs2qXnz5pXaLewwXLy8vNSq\nVSv7+9atW8vDw+hLSQAAZ0lLS1OvXr0kSaGhoUpNTXV4jsNpsTvuuEOJiYmyWq06evSo9u7dK39/\n/5uvFgBQZa5cc0lPT9eECRN06dIlTZo0SVar1T575e/vr+zsbIdjOAyX2NhYrV+/XvXr19c777yj\njh07KjY29uarBwBUmas2i911112aNGmSwsLC9MMPP2jUqFEqLS21f99ms1VqHIfh8vXXX6tz587q\n3LnzNccAAO7hqmeLNWrUSP3795ckNWvWTA0bNtSXX36pgoIC+fj4KCsrS4GBgQ7HcRgu8fHx9q9L\nSkp04sQJBQcHEy4A4EauWvnesWOHsrOzNXbsWGVnZysnJ0dPPPGEkpOTNXjwYKWkpCgkJMThOA7D\n5T8fA2O1WjVnzpyqVw4AuGmumhbr2bOn/vCHP2jfvn0qLi7W/Pnz1bZtW0VHR2vLli0KCgpSeHi4\nw3Fu+CZKDw8PpaenV6loAIBzuGparHbt2lq5cuU1x9euXXtD4zgMl4ceesi+L9pms8nDw0NPPfXU\nDV0EAHB7cRguq1ev5m58ADAYgz9azPGa0MKFC1VSUlIdtQAAKsnDUvVXdXDYufj6+uqxxx5TmzZt\nVKNGDfvxN954w6WFAQDKZ/qPOR4zZkx11AEAuAEGz5byw2XKlCmKi4tTly5dqrMeAEAlmPaR+7m5\nudVZBwDgBlhk7HQpN1y+//57vf766+WeOHPmTJcUBAAwv3LDpVatWvYPiwEAGItpp8UaNmyoIUOG\nVGctAIBKMm24BAcHV2cdAIAbUJlPlHSncsMlOjq6OusAANwA03YuAADjMnjj4rKPBAAA3MboXADA\nhEz/+BcAgPGw5gIAcDqDNy6ECwCYkYdZH/8CADAuOhcAgNMZfc2FrcgAAKejcwEAE2IrMgDA6Qye\nLYQLAJgRnQsAwOkMni2ECwCYkdF3YxEuAGBCRv88F6OHHwDAhOhcAMCEjN23EC4AYErsFgMAOJ2x\no4VwAQBTMnjjQrgAgBkZfbcY4QIAJmT0rb5Grw8AYEJ0LgBgQkyLAQCcztjRQrgAgCkZvXNhzQUA\nTMjjJl6VUVBQoN69eyspKUnnzp3TyJEjFRkZqalTp6qoqKhS9QEATMZisVT5VRlvvfWW6tatK0mK\ni4tTZGSkNm3apObNmysxMdHh+YQLAJiQ5SZejmRkZCg9PV09evSQJKWlpalXr16SpNDQUKWmpjoc\ng3ABAJSxcOFCzZo1y/7earXK29tbkuTv76/s7GyHY7CgDwAm5Kr1/O3bt+u+++5T06ZNr/t9m81W\nqXEIFwAwIQ8XbUY+cOCAfvjhBx04cEDnz5+Xt7e3fH19VVBQIB8fH2VlZSkwMNDhOIQLAJiQqzqX\npUuX2r9etmyZ7rzzTn3xxRdKTk7W4MGDlZKSopCQEIfjsOYCACZkuYlfN2ry5Mnavn27IiMjlZub\nq/DwcIfn0LkAgAlVxz2UkydPtn+9du3aGzqXcAEAE3LVmouzMC0GAHA6OhcAMCGDP1qMcAEAMyJc\nAABOV5VdX9WJcAEAE/IwdrYQLgBgRnQuAACnM/qaC1uRAQBOR+cCACbEtBiq1exZM/X3vx1USUmJ\nZkS/qAce7Kyxz4xUaWmpGjdpojXr4lWzZk13lwmTCQtupFFdm6n0qk0rD3yrS9ZiTevdSiVXbSoq\nuaqYD08oN7/Y3WXeVoy+oO+SabEVK1ZoyZIl9vdXr17V4MGDdfLkSVdcDv/rrwf26+uvjuuvf0vV\njl0facYL0/Ty/Hl69vfPad+Bg2rVqrXWr13j7jJhMnVreWl897s0dt3nmrb5mB69p6GiHmqqeR+e\n0LPxR3TszGUN6RTk7jJvO9X54MqqcEm4jBkzRsnJycrKypIkbd26VR07dlSbNm1ccTn8r0dCuith\n8weSpHr16ik/L0+ffHJAAwc9LknqP2CQ/ud/PnZniTChLi0a6LNvLyq/qFQ/XinSq7v+r6K3fqUz\nuQWSpMA7aurCzwVurvL2Y7FU/VUdXBIuPj4+mjhxopYuXSqr1ao1a9Zo6tSpSk9P16hRo/T0009r\n4sSJunz5soqLizVt2jSNGDFCQ4cO1SeffOKKkm4Lnp6e8vPzkyStW7Naffv1V35enn0aLDAwUOfP\nnXNniTChoHo+8qnhoSXD2+vdpzup8131JUkPt2qgpIm/UQO/Gtp9LMvNVd5+LDfxqg4u2y32+OOP\nKyMjQ3PnztWQIUPk7++vl19+WS+99JLWr1+vbt26KSEhQadOndLFixeVkJCg1atX69KlS64q6bax\nc8eHWrd2tf4c92aZ45X9eFLg1yyS6taqoRnvH9f8HSc0//FfZiBSM37SEyvS9K+cfD3Trbl7i7wN\neVgsVX5VS32uGthisWj69OlKS0vTM888I0k6duyYYmJiNHLkSO3YsUM5OTlq2bKl8vLyNGPGDH36\n6acaMGCAq0q6LexNSdbC2Ff14V/2qG7duvKrXVtWq1WSdPbsGTUJYm4cNyYnr0jHMi+p1GZT5sUC\n5RWVqs+9//9jbv/nRLbua1rXjRXCiFy6W6xp06YKDAyUt7e3JKlWrVrasGGDLP+RnO+//74+//xz\nbdu2Tfv371dsbKwry7plXbp0SbOjZ2hX8sdq0KCBJKlnz97anrRVT42I0rakrXrssX5urhJm8+np\nnzT/8bZa9/fvVaeWl3xreGpcSHN9l5OvU1lXFHxnHX2Xk+/uMm87Bt8sVr1bkdu0aaNPPvlEjz76\nqHbt2qUGDRqoTp06Sk9P1+DBg9WxY0eNGDGiOku6pSS+v0U/5vyoqKeG2Y+tWrNeE58dp3dXva1m\nzZoratTTbqwQZpT9c5H2ncjWujEPSJJeTz6l7J+LNCvsbpVetamw5Kpitn/t5ipvQwZPF4vNhRPx\nmZmZmjJlipKSkiRJGRkZiomJkYeHh2rWrKnFixfLYrHo+eefl9Vqlaenp6KiotS3b98Kxy0ocVXF\nuF11i93v7hJwCzocE+qysdMyqr4+/ZtWrp/GdGm4uArhAmcjXOAKrgyXz05XPVy6tHR9uHCHPgCY\nkMFnxQgXADAlg6cLT0UGADgdnQsAmBBPRQYAOJ3RPyyMcAEAEzJ4thAuAGBKBk8XwgUATIg1FwCA\n0xl9zYWtyAAAp6NzAQATMnjjQrgAgCkZPF0IFwAwIRb0AQBOZ/QFfcIFAEzI4NlCuACAKRk8XdiK\nDABwOjoXADAhFvQBAE7Hgj4AwOlclS1Wq1WzZs1STk6OCgsLNXHiRLVp00YzZ85UaWmpAgICtGjR\nInl7e1c4DuECAGbkonTZv3+/goODNX78eJ05c0ZjxozR/fffr8jISIWFhWnJkiVKTExUZGRkheOw\noA8AJmS5iV8V6d+/v8aPHy9JOnfunBo1aqS0tDT16tVLkhQaGqrU1FSH9dG5AIAJuXrNJSIiQufP\nn9fKlSs1evRo+zSYv7+/srOzHZ5PuAAArrF582adOHFCM2bMkM1msx//9dcVYVoMAEzIchOvihw/\nflznzp2TJLVt21alpaXy8/NTQUGBJCkrK0uBgYEO6yNcAMCMXJQuhw4d0po1ayRJP/74o/Lz89W1\na1clJydLklJSUhQSEuKwPKbFAMCEXHUTZUREhObMmaPIyEgVFBRo3rx5Cg4OVnR0tLZs2aKgoCCF\nh4c7rs9W2Qk0AykocXcFuNV0i93v7hJwCzocE+qysdMvWKt8buvAWk6s5ProXADAhAx+gz7hAgCm\nZPB0YUEfAOB0dC4AYEI8FRkA4HQ8FRkA4HQGzxbCBQBMyeDpQrgAgAmx5gIAcDqjr7mwFRkA4HR0\nLgBgQgZvXAgXADAjo0+LES4AYErGThfCBQBMiM4FAOB0Bs8WwgUAzMjonQtbkQEATkfnAgAmxB36\nAADnM3a2EC4AYEYGzxbCBQDMyOgL+oQLAJgQay4AAOczdrawFRkA4Hx0LgBgQgZvXAgXADAjFvQB\nAE7Hgj4AwOmM3rmwoA8AcDo6FwAwIToXAMBth84FAEyIBX0AgNMZfVqMcAEAEzJ4thAuAGBKBk8X\nwgUATIg1FwCA0xl9zYWtyAAAp6NzAQATcmXj8vrrr+vw4cMqKSnRs88+q/bt22vmzJkqLS1VQECA\nFi1aJG9v7wrHIFwAwIxclC6ffvqpvvnmG23ZskUXL17UkCFD9PDDDysyMlJhYWFasmSJEhMTFRkZ\nWeE4TIsY4ODKAAAIMElEQVQBgAlZbuJXRTp37qw33nhDklSnTh1ZrValpaWpV69ekqTQ0FClpqY6\nrI9wAQATsliq/qqIp6enfH19JUmJiYnq3r27rFarfRrM399f2dnZDusz5bSYjymrhpEdjgl1dwnA\nDXH134Mff/yxEhMTtWbNGj322GP24zabrVLn07kAAMo4ePCgVq5cqVWrVumOO+6Qr6+vCgoKJElZ\nWVkKDAx0OAbhAgCw+/nnn/X666/r7bffVr169SRJXbt2VXJysiQpJSVFISEhDsex2Crb4wAAbnlb\ntmzRsmXL1KJFC/uxBQsWaO7cuSosLFRQUJBiY2NVo0aNCschXAAATse0GADA6QgXAIDTES63kMzM\nTLVt21YnT560H0tKSlJSUpIbq4LZrFixQkuWLLG/v3r1qgYPHlzm/1eAI4TLLaZ169ZavHixu8uA\niY0ZM0bJycnKysqSJG3dulUdO3ZUmzZt3FwZzIRwucW0a9dOvr6+1zyeYf369Ro+fLiGDx+ud955\nx03VwQx8fHw0ceJELV26VFarVWvWrNHUqVOVnp6uUaNG6emnn9bEiRN1+fJlFRcXa9q0aRoxYoSG\nDh2qTz75xN3lwyAIl1vQ9OnTtXTpUvudtDabTdu2bVNCQoISEhK0Z88eff/9926uEkb2+OOPKyMj\nQ3PnztWQIUPk7++vl19+WS+99JLWr1+vbt26KSEhQadOndLFixeVkJCg1atX69KlS+4uHQbBg1Ru\nQXfddZfuvfde7d69W5J0+fJldezYUV5ev/xx33///Tp58qSaNWvmzjJhYBaLRdOnT9eMGTMUGxsr\nSTp27JhiYmIkSUVFRWrfvr1atmypvLw8zZgxQ3369NGAAQPcWTYMhHC5RT333HMaO3asRowYIYvF\nUuZ5QMXFxfLwoGlFxZo2barAwED7Awtr1aqlDRs2yPIfTz58//339fnnn2vbtm3av3+/PYxwe+Nv\nmFtUw4YN1bt3b23evFl16tTRkSNHVFJSopKSEh09elRt27Z1d4kwmTZt2tjXVHbt2qXU1FR99dVX\n2rlzpx588EHNnz9fGRkZbq4SRkHncgsbM2aM3nvvPUnS8OHDFRUVJZvNpqFDh+rOO+90c3Uwmzlz\n5igmJkarVq1SzZo1tXjxYlksFi1ZskRbtmyRp6enxo4d6+4yYRA8/gUA4HRMiwEAnI5wAQA4HeEC\nAHA6wgUA4HSECwDA6QgXGEJmZqY6deqkkSNHKioqSsOGDdPevXurNNbGjRu1bNkynThxQnFxceX+\n3L59+1RUVFSpMU+dOqWRI0eWOZaWlqYpU6aUe86yZcu0cePGSo2flJSkhQsXVupnATPgPhcYRosW\nLRQfHy9Jys3N1ZAhQxQSEiIfH58qjde2bdsKbxZdt26dHnroIfsd6ACch3CBIdWrV08BAQHKzs7W\n8uXLVaNGDeXm5mrp0qWKiYnRDz/8oJKSEk2ZMkUPP/ywUlNT9dprr6lhw4YKCAhQ06ZNlZaWpoSE\nBMXFxWn79u2Kj4+Xh4eHRo8eraKiIh05ckTjx4/XunXr9MEHH2jnzp3y8PBQ7969NWbMGJ0/f15T\np06Vt7e37rnnngrrXbNmjZKTk3X16lU9+uijmjRpkiTpyy+/1JgxY3ThwgXNnDlT3bt3V0pKitas\nWSMvLy8FBwdr1qxZ1fFbClQrpsVgSJmZmcrNzVWTJk0kSXXr1tWyZcu0c+dOBQQEKD4+XsuXL9dr\nr70mSVq8eLEWLVqktWvX6uLFi2XGunLlilasWGF/cu/OnTsVHh6ugIAArVq1SllZWfroo4/03nvv\nKSEhQSkpKTp79qw2bNig/v37Kz4+XoGBgQ5r3rRpk95//30lJSXpypUrkqScnBytWbNGS5Ys0dKl\nS5WXl6e33npLGzZs0MaNG3Xu3DkdPnzYyb97gPvRucAwvv32W40cOVI2m001a9bUwoUL7U9y7tCh\ngyTpiy++0OHDh/X5559LkgoLC1VUVKQzZ87YP8yqc+fOKiwstI97+vRptWzZUj4+PvLx8dFbb71V\n5rpffvmlvvvuO40aNUqSlJeXpzNnzigjI0P9+vWTJP3mN7/RwYMHy63dx8dHUVFR8vLy0sWLF5Wb\nmytJ6tKliyTp7rvv1rlz55Senq6zZ8/aH5Py888/6+zZszf3GwcYEOECw/j1mst/qlGjhv1/J0yY\noIEDB5b5/q+f8vyfTzTy8PDQ1atXy71ujRo11KNHD7300ktljq9atco+bkXnnzlzRuvWrdO2bdvk\n5+dXprZfP0HYYrGoRo0aCg4O1urVq8uMwUdR41bDtBhMpWPHjtq3b5+kX6ac/v1Z740aNdLp06dl\ns9n02WeflTmnZcuW+vbbb5WXl6fCwkKNHj1aNptNFotFpaWlateundLS0mS1WmWz2fTKK6+ooKBA\nLVq00PHjxyX9sjOsPBcvXlSDBg3k5+enr776SmfOnFFxcbEk2ae8Tp48qaCgILVo0UIZGRnKycmR\nJMXFxdk/Thi4ldC5wFTCwsL06aefKiIiQqWlpfaF82nTpmnq1KkKCgpS48aNy5zj6+urKVOmaPTo\n0ZKkZ555RhaLRV26dFFkZKQ2bNigUaNGacSIEfL09FTv3r3l4+OjUaNGadq0adq7d6/uvvvucmtq\n27at/Pz8FBERoQceeEARERH64x//qAceeED+/v6aMGGCMjMzNWfOHNWqVUuzZ8/W+PHj5e3trXvv\nvbdS6zmA2fBUZACA0zEtBgBwOsIFAOB0hAsAwOkIFwCA0xEuAACnI1wAAE5HuAAAnI5wAQA43f8D\nIFuVlut06FUAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# from sklearn.metrics import confusion_matrix, accuracy_score\n", "\n", "# pd.DataFrame(confusion_matrix(y_test, y_pred), index=['No', 'Yes'], columns=['No', 'Yes'])\n", "\n", "from scikitplot.metrics import plot_confusion_matrix\n", "\n", "plot_confusion_matrix(y_test, y_pred);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 8.3.2 Fitting Regression Trees" ] }, { "cell_type": "code", "execution_count": 50, "metadata": { "collapsed": true }, "outputs": [], "source": [ "boston = pd.read_csv('../datasets/Boston.csv', index_col=0)\n", "\n", "X = boston.loc[:, 'crim':'lstat']\n", "y = boston.loc[:, 'medv']\n", "\n", "X_train, X_test, y_train, y_test = train_test_split(X, y, train_size=0.5, test_size=0.5, random_state=42)" ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(0.74614222380842765, 0.63495038846953844)" ] }, "execution_count": 51, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.tree import DecisionTreeRegressor\n", "\n", "tree_boston = DecisionTreeRegressor(min_samples_leaf=5, max_depth=2)\n", "tree_boston.fit(X_train, y_train)\n", "y_pred = tree_boston.predict(X_test)\n", "\n", "tree_boston.score(X_train, y_train), tree_boston.score(X_test, y_test)" ] }, { "cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [ { "data": { "image/svg+xml": [ "\n", "\n", "\n", "\n", "\n", "\n", "Tree\n", "\n", "\n", "0\n", "\n", "rm ≤ 6.974\n", "mse = 87.616\n", "samples = 253\n", "value = 22.749\n", "\n", "\n", "1\n", "\n", "lstat ≤ 14.4\n", "mse = 38.145\n", "samples = 214\n", "value = 19.888\n", "\n", "\n", "0->1\n", "\n", "\n", "True\n", "\n", "\n", "4\n", "\n", "rm ≤ 7.437\n", "mse = 67.845\n", "samples = 39\n", "value = 38.444\n", "\n", "\n", "0->4\n", "\n", "\n", "False\n", "\n", "\n", "2\n", "\n", "mse = 22.673\n", "samples = 127\n", "value = 23.334\n", "\n", "\n", "1->2\n", "\n", "\n", "\n", "\n", "3\n", "\n", "mse = 18.103\n", "samples = 87\n", "value = 14.859\n", "\n", "\n", "1->3\n", "\n", "\n", "\n", "\n", "5\n", "\n", "mse = 35.362\n", "samples = 22\n", "value = 33.041\n", "\n", "\n", "4->5\n", "\n", "\n", "\n", "\n", "6\n", "\n", "mse = 23.225\n", "samples = 17\n", "value = 45.435\n", "\n", "\n", "4->6\n", "\n", "\n", "\n", "\n", "\n" ], "text/plain": [ "" ] }, "execution_count": 52, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tree_boston_graph = export_graphviz(tree_boston, \n", " out_file=None, \n", " feature_names=X.columns,\n", " filled=True, \n", " rounded=True, \n", " special_characters=True)\n", "\n", "Source(tree_boston_graph)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 8.3.3 Bagging and Random Forests" ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "17.088167588932809" ] }, "execution_count": 53, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.ensemble import RandomForestRegressor\n", "from sklearn.metrics import mean_squared_error\n", "\n", "boston_bag = RandomForestRegressor(max_features=13, random_state=42)\n", "boston_bag.fit(X_train, y_train)\n", "\n", "y_pred = boston_bag.predict(X_test)\n", "\n", "mean_squared_error(y_test, y_pred)" ] }, { "cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAe0AAAFKCAYAAAAwrQetAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/D9y0mmz9EH4fgAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.regplot(y_pred, y_test);" ] }, { "cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "13.358543695652173" ] }, "execution_count": 55, "metadata": {}, "output_type": "execute_result" } ], "source": [ "boston_rf = RandomForestRegressor(max_features=6, random_state=42, n_estimators=100)\n", "boston_rf.fit(X_train, y_train)\n", "\n", "y_pred = boston_rf.predict(X_test)\n", "\n", "mean_squared_error(y_test, y_pred)" ] }, { "cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAfEAAAFKCAYAAAANP2bLAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nkU4xiBMREekUgzgREZFOMYgTERHp1P8DjSYnQ+WOn2kAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.regplot(y_pred, y_test);" ] }, { "cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeEAAAFqCAYAAAAtPeIVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Feature Importance\n", "\n", "plot_feature_importances(boston_rf, \n", " feature_names=X.columns,\n", " x_tick_rotation=45);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 8.3.4 Boosting" ] }, { "cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "16.754432073663978" ] }, "execution_count": 58, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.ensemble import GradientBoostingRegressor\n", "\n", "boston_gb = GradientBoostingRegressor(n_estimators=500, learning_rate=0.01, max_depth=4, random_state=42)\n", "boston_gb.fit(X_train, y_train)\n", "\n", "y_pred = boston_gb.predict(X_test)\n", "\n", "mean_squared_error(y_test, y_pred)" ] }, { "cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAecAAAFqCAYAAAAgI5JSAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nmIzCWURExGQUziIiIiajcBYRETGZ/w+QhKjNI3sdWQAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_feature_importances(boston_gb, \n", " feature_names=X.columns,\n", " x_tick_rotation=45);" ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhgAAAEHCAYAAADs7D/DAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Partial Dependence Plots\n", "\n", "from sklearn.ensemble.partial_dependence import plot_partial_dependence\n", "\n", "plot_partial_dependence(boston_gb, X_train, [5, 12], feature_names=X.columns);" ] }, { "cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "15.24949266884432" ] }, "execution_count": 61, "metadata": {}, "output_type": "execute_result" } ], "source": [ "boston_gb2 = GradientBoostingRegressor(n_estimators=500, learning_rate=0.2, max_depth=4, random_state=42)\n", "boston_gb2.fit(X_train, y_train)\n", "\n", "y_pred = boston_gb2.predict(X_test)\n", "\n", "mean_squared_error(y_test, y_pred)" ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAecAAAFqCAYAAAAgI5JSAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nfmNG/Bjs3QAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_feature_importances(boston_gb2, \n", " feature_names=X.columns,\n", " x_tick_rotation=45);" ] } ], "metadata": { "kernelspec": { "display_name": "Python [default]", "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": "3.6.2" } }, "nbformat": 4, "nbformat_minor": 2 }