{ "metadata": { "name": "", "signature": "sha256:35f5c1b001e341f59559e41291b26d82034ff6cb4d48670ac4fae9c35ffa7a18" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "6. Learning, a better way" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's try again, but this time only with 2 classes to learn." ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "6.1. Preparing the notebook" ] }, { "cell_type": "code", "collapsed": false, "input": [ "%matplotlib inline\n", "%config InlineBackend.figure_format='retina'" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 1 }, { "cell_type": "code", "collapsed": false, "input": [ "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import pandas as pd\n", "import seaborn as sns\n", "\n", "from matplotlib import cm as cmap\n", "\n", "from sklearn.cross_validation import StratifiedShuffleSplit\n", "from sklearn.ensemble import RandomForestClassifier\n", "from sklearn.metrics import confusion_matrix, precision_recall_curve, roc_curve, auc\n", "from sklearn.preprocessing import LabelEncoder\n", "\n", "sns.set(font='sans')" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 2 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "6.2. Learning, again, with random forest" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We aren't going to change the configuration of the cross-validation method and the random forests. But, let's save a little more data, like the `P/R` and the `ROC` scores." ] }, { "cell_type": "code", "collapsed": false, "input": [ "labelize_columns = ['medallion', 'hack_license', 'vendor_id']\n", "\n", "interize_columns = ['pickup_month', 'pickup_weekday', 'pickup_non_working_today', 'pickup_non_working_tomorrow']\n", "\n", "feature_columns = ['medallion', 'hack_license', 'vendor_id', 'pickup_month', 'pickup_weekday', 'pickup_day', 'pickup_time_in_mins',\n", " 'pickup_non_working_today', 'pickup_non_working_tomorrow', 'fare_amount', 'surcharge', 'tolls_amount',\n", " 'passenger_count', 'trip_time_in_secs', 'trip_distance', 'pickup_longitude', 'pickup_latitude',\n", " 'dropoff_longitude', 'dropoff_latitude']\n", "\n", "class_column = 'tip_label'" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 3 }, { "cell_type": "code", "collapsed": false, "input": [ "data = pd.read_csv('../data/dataset/dataset.csv')" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 4 }, { "cell_type": "code", "collapsed": false, "input": [ "for column in labelize_columns:\n", " real_column = data[column].values\n", " \n", " le = LabelEncoder()\n", " le.fit(real_column)\n", " labelized_column = le.transform(real_column)\n", " \n", " data[column] = labelized_column\n", " \n", " le = None\n", " real_column = None\n", " labelized_column = None" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 5 }, { "cell_type": "code", "collapsed": false, "input": [ "for column in interize_columns:\n", " data[column] = data[column].astype(int)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 6 }, { "cell_type": "code", "collapsed": false, "input": [ "data_features = data[feature_columns].values\n", "data_classes = data[class_column].values\n", "\n", "data = None" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 7 }, { "cell_type": "code", "collapsed": false, "input": [ "cross_validation = StratifiedShuffleSplit(data_classes, n_iter=10, test_size=0.1, random_state=0)\n", "\n", "scores = []\n", "confusion_matrices = []\n", "precision_scores = {}\n", "recall_scores = {}\n", "pr_auc_scores = {}\n", "fpr_scores = {}\n", "tpr_scores = {}\n", "roc_auc_scores = {}\n", "\n", "for train_index, test_index in cross_validation:\n", " data_features_train, data_classes_train = data_features[train_index], data_classes[train_index]\n", " data_features_test, data_classes_test = data_features[test_index], data_classes[test_index]\n", " \n", " '''\n", " You need a bit more than 8GB RAM for predicting 2 classes with 256 trees.\n", " Of course, you can use a lower number, but gradually you'll notice worse performance.\n", " '''\n", " clf = RandomForestClassifier(n_estimators=256, n_jobs=-1)\n", " clf.fit(data_features_train, data_classes_train)\n", " \n", " if not pr_auc_scores:\n", " for c in clf.classes_:\n", " precision_scores[c] = []\n", " recall_scores[c] = []\n", " pr_auc_scores[c] = []\n", " fpr_scores[c] = []\n", " tpr_scores[c] = []\n", " roc_auc_scores[c] = []\n", " \n", " # Saving the scores.\n", " test_score = clf.score(data_features_test, data_classes_test)\n", " scores.append(test_score)\n", " \n", " # Saving the confusion matrices.\n", " data_classes_pred = clf.predict(data_features_test)\n", " cm = confusion_matrix(data_classes_test, data_classes_pred)\n", " confusion_matrices.append(cm)\n", " \n", " # Saving the necesary data for the P/R and the ROC scores.\n", " prob = clf.predict_proba(data_features_test)\n", " \n", " for c in clf.classes_:\n", " prob_index = np.where(clf.classes_ == c)[0][0]\n", " \n", " precision, recall, _ = precision_recall_curve(data_classes_test, prob[:, prob_index], pos_label=c)\n", " precision_scores[c].append(precision)\n", " recall_scores[c].append(recall)\n", " pr_auc_scores[c].append(auc(recall, precision))\n", "\n", " fpr, tpr, _ = roc_curve(data_classes_test, prob[:, prob_index], pos_label=c)\n", " fpr_scores[c].append(fpr)\n", " tpr_scores[c].append(tpr)\n", " roc_auc_scores[c].append(auc(fpr, tpr))\n", "\n", "print 'Accuracy mean: ' + str(np.mean(scores))\n", "print 'Accuracy std: ' + str(np.std(scores))" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Accuracy mean: 0.717352\n", "Accuracy std: 0.000580031033653\n" ] } ], "prompt_number": 8 }, { "cell_type": "markdown", "metadata": {}, "source": [ "An accuracy of **`71.74%`**. That's a great result for a noob with a dataset in which there is no information about the passengers, a **essential** data for trying to accomplish the task." ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "6.3. More ways for measuring the performance" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's plot the confusion matrix, and the area under the curve, *AUC*, of the P/R and ROC scores." ] }, { "cell_type": "code", "collapsed": false, "input": [ "classes = [' ', '< 20', '>= 20']" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 9 }, { "cell_type": "code", "collapsed": false, "input": [ "first = True\n", "cm = None\n", "\n", "for cm_iter in confusion_matrices:\n", " if first:\n", " cm = cm_iter.copy()\n", " first = False\n", " else:\n", " cm = cm + cm_iter\n", "\n", "fig, ax = plt.subplots()\n", "\n", "colorbar = ax.matshow(cm, cmap=cmap.Blues)\n", "fig.colorbar(colorbar, ticks=[30000, 90000, 150000, 210000, 270000, 330000, 390000])\n", "\n", "ax.set_xlabel('Predicted class', fontsize=15)\n", "ax.set_ylabel('True class', fontsize=15)\n", "\n", "ax.set_xticklabels(classes)\n", "ax.set_yticklabels(classes)\n", "\n", "ax.tick_params(labelsize=12)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": { "png": { "height": 359, "width": 467 } }, "output_type": "display_data", "png": 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FkVRn5lSSJEmS1Dozp5IkSZIGzsSp6sycSpIkSZJaZ3AqSZIkSWqdw3olSZIk\nDdyMGY7r1TOZOZUkSZIktc7MqSRJkqSBc0Ek1Zk5lSRJkiS1zsypJEmSpIHrmDpVjZlTSZIkSVLr\nDE4lSZIkSa1zWK8kSZKkgXNUr+rMnEqSJEmSWmfmVJIkSdLAuSCS6sycSpIkSZJaZ3AqSZIkSWqd\nw3olSZIkDZzDelVn5lSSJEmS1Dozp5IkSZIGzsSp6sycSpIkSZJaZ+ZUkiRJ0sA551R1Zk4lSZIk\nSa0zOJUkSZIktc5hvZIkSZIGzlG9qjNzKkmSJElqnZlTSZIkSQPngkiqM3MqSZIkSWqdwakkSZIk\nqXUO65UkSZI0cI7qVZ2ZU0mSJElS68ycSpIkSRo4F0RSnZlTSZIkSVLrzJxKkiRJGjgTp6ozcypJ\nkiRJap3BqSRJkiSpdQ7rlSRJkjRwLoikOjOnkiRJkqTWmTmVJEmSNHAmTlVn5lSSJEmS1Dozp5Ik\nSZIGzjmnqjNzKkmSJElqncGpJEmSJKl1DuuVJEmSNHCO6lWdmVNJkiRJUuvMnEqSJEkaOBdEUp2Z\nU0mSJElS6wxOJUmSJEmtc1ivJEmSpIFzVK/qzJxKkiRJklpn5lSSJEnSwLkgkurMnEqSJEmSWmfm\nVJIkSdLAmTlVnZlTSZIkSVLrDE4lSZIkSa1zWK8kSZKkgXNUr+rMnEqSJEmSWmfmVJIkSdLAuSCS\n6sycSpIkSZJaZ3AqSZIkSWqdw3olSZIkDZyjelVn5lSSJEmS1Dozp5IkSZIGzgWRVGfmVJIkSZLU\nOjOnkiRJkgbOxKnqzJxKkiRJklpncCpJkiRJap3DeiVJkiQN3AzH9arGzKkkSZIkqXWtZE4jYntg\nM+A5wK+Bb2fm4230RZIkSdLgmThVXaPBaUS8GPg0MAT8e2ZeVTv/XOAc4DW1podFxGsy87Ym+yNJ\nkiRJmhqaHta7B7ATsDnwmz7nD+PZgSnAbODsiPD3E0mSJEmahpoOTjetyvMy84neExGxMHBQ9fRe\n4ABgR0omFeBlwO4N90eSJEnSJNTpdFp7aHJqOjh9UVX+ss+51wAzq3/vk5lfzMzvAbsBN1bHd2u4\nP5IkSZKkKaDp4HSZqryjz7mtqvJu5mRLycy/AadWT1/ecH8kSZIkTUIzOu09NDk1HZwuVZWP9TnX\nHfJ7QWYO1c7dVJXLNdwfSZIkSdIU0PRWMo8CiwNL9x6MiJnMyYr+rE+7R6pywYb7I0mSJGkScu6n\n6prOnN5xcV5RAAAgAElEQVRalRvXjm9f3WsIuLRPu27G9cGG+yNJkiRJmgKaDk67geebI2JjgIhY\nAvhAdfzPwK/7tFu7Km9uuD+SJEmSpCmg6eD0K1W5KHBxRFxDmU/6sur41/rMNwXYsiqvbbg/kiRJ\nkiahTqe9hyanRoPTzLwa+Gj1dAFKUNqdf/q/wH/U20TEmpTM6RBwSZP9kSRJkiRNDU1nTsnMjwA7\nA98HErgG+BSwWWY+3KfJ+6uyA/yw6f5IkiRJmnw6Lf5Pk1PTq/UCkJlnA2ePse67gHdNRD8kSZIk\nSVND45lTSZIkSZLGa0Iyp5IkSZI0khmOrlVN48FptXUMwGOZ+USf8y8BPgZsWt3/18AnMvOCpvsi\nSZIkSZoaGh3WGxHbAfcD9wEv7XN+DeDnwK7A8sAywDbAeRHx1ib7IkmSJGny6nQ6rT00OTU953SH\nqvx9Zl7V5/xngSWrfz8F3NPTjy9FxPIN90eSJEmSNAU0HZyuV5Xn109ExMrAdj3nn5eZywK7U/Y4\nXRz4p4b7I0mSJGkS6nTae2hyajo4Xa4qf9fn3PaUvUyHgP0y80GAzDwd+FFVZ9uG+yNJkiRJmgKa\nDk6Xqcp7+5zbvCqvzcwba+fOq8qXNNwfSZIkSdIU0PRqvQtXZb+gd5OqvKjPuT9V5ayG+yNJkiRp\nEprh+FrVNJ05vb8qV+49GBEvBlaqnl42Qj+earg/kiRJkqQpoOng9PdVuUPt+Fuqcgi4pE+7Fary\nLw33R5IkSdIk5IJIqmt6WO/3gVcBW0TE54GvAmsD/686f0Vm3tmn3Suq8oaG+yNJkiRJmgKazpz+\nF3B39e/9gKuBU4DFqmP/UW8QEc8B/rF6emXD/ZEkSZIkTQGNBqeZeT9lSO8d1aFu0nwI+ERmntWn\n2Y7A0tW/L2yyP5IkSZImp06n09pDk1PTw3rJzCsjIoDXAS8GHgHOz8zfD9NkJeBk4Gn6r+QrSZIk\nSZrPNR6cAmTmX4Fvj7HucRPRB0mSJEmTlwlM1TU951SSJEmSpHGbkMypJEmSJI1khqlT1Zg5lSRJ\nkiS1bsIypxGxOfA2YENgRWAJRg6GO8BQZj5novokSZIkSZqcGg9OI2ImZfXdneaiubl9SZIkaRrw\ni7/qJiJzehqwXfXvR4DfAhtVz38HPAa8CFimp80vq7pDE9AfSZIkSdIk12hwGhE7MCcwPR3YJzMf\njoinKYHnYZl5dlX35cDhlAzrwsDumXlTk/2RJEmSNDl1puCCSBGxNLALsD2wDrAC8ARwLXACcEJm\nDvXUPxF4+yiXvSAzX93nXnsB+wNrAk8B1wBHZ+b3hunbIsAHgT2AlYEHgYuAIzLzumHarAh8lBLD\nLQ3cCZwFHJmZ9w/TZhPgMGBjShx3A3A8cFxmPj3Kax1R05nTt1blvcDe1X6nvf7+HyozrwF2joiP\nAYcC50TE+pn5WMN9kiRJkqQmvAn4InAHcCFwG7A8JWD9GvBa4I099b8DDJeAezuwGvD9+omIOBo4\nGLgd+AqwECXoPDciDszML9TqLwT8GNgEuBI4kxKgvhHYPiK2zswram1WBy4DlqUEpNdRRry+D9gu\nIjbNzHtrbXYCzgD+Shkxey/weuAzwKbV32euNR2cblyVp/QJTKH/0PLDKb88rAv8M/CfDfdJkiRJ\nkppwPbBjPXsZER8GrgB2jYhdMvNMgGrU6Nn1i0TELEqW83HgxNq5TSiB6Y3ABpn5QHX805TpkEdH\nxHcz89aeZgdTAtPTM3P3nmudRgk8j4+IdXqzupQge1ngGcFuRBwDvB84CnhPz/ElgK8CTwJbZubV\n1fHDgQuA3SJi98w8bYS/34ia3krm+VV5fZ9zHUra9xmqP9D/VE93a7g/kiRJkiahGZ32HnMrMy/s\nN6w2M+8Cvlw93WIMl3obJTY6s56dBN5dlUd1A9PqHrcCX6BkUffuHo+ITtVmCPjXWr/OAS4B1urt\nV5U13Ra4uZ6FBY6gZEb3jIhFe47vRlk36NRuYFrd43HKMF/oCWbnRtPBaTcTe3ft+MNVueww7W6v\nyhc33B9JkiRJGoS/1cqR7FuVX+lzbmtKoPnDPud+UJVb9RxbHVgJyFo2td5m655j3fbn1Stn5sPA\npcBizBkZ29u+X78uBh4FXhkRz+1zfkyaDk7vqcrFasfvqsqXDNNuuapcquH+SJIkSZqEOp1Oa4+m\nRcQCzFn4qF/w1lv3lcDawPWZ+dPaucUoiyw9XGVj627sVu05Nrsqc5hbdtusMY42N4ynTWY+BdxM\nSVauNsw1R9V0cNpdBWr12vFfV+UOEdHvnrtU5T19zkmSJEnSZPZJ4B+A72Xmj0ep+66q/Gqfc0tW\n5QN9zvUen9VSm6FR2nRqbcal6eD051W5Ye14dxLwysDXqsm0RMTiEfFZYPPq/M8a7o8kSZKkSajT\nae/RpIh4L2VBot9T5pKOVHdJyoq2z1oISc0Hp90U9hbdALTyLeakk98B3B0RdwD3A++tjj8NHNtw\nfyRJkiRpQkTEAcBngd8BWw23N2iPPYFF6L8QEszJSi7Z51zv8d77DLJNZ5xtxqXR4DQzLwFOomRK\nX9pz/HFgV+YslPRcyn5A3fs/BRyQmb9osj+SJEmSNBEi4iDgc8C1lMD0z2No1l0I6b/6nczMRyh7\nqC4eEcv3qdKdA9o777M7tTLob6Q2s+mvX5vujizPalPNuV2Vss3McPu6jqrpzCmZuXdmvjkzf1Y7\nfi2wJvARyvDdG4BfUcZar5+ZX65fS5IkSdL8aSoviBQRH6CM+ryGEpj+ZQxtNqIk8K7PzItHqPoT\nSoZyuz7nXluVF3QPZOb/AbcBsyNilbG0AS6sym2rrWh6+zkT2BR4BLi81i+G6dfmlIzwZZn5ZJ/z\nY9J4cDqSzLw3Mz+amZtn5uzMfEVm/nNm/nr01pIkSZLUroj4N+ATwFXANsMMz+2nuxBSv+1jenWT\ndodGxN8XF6oCz/2Bx4AThmnzqd5gMyJ2AjYDfte7MnBm3kTZRmbV6pq9jgQWBU7JzEd7jn8b+Auw\nR0Ss13OPhYGPV0+/NMprG9ECo1eRJEmSpGbNaH5HlwkXEXtRgrenKKNBD4p41mjamzPzpFq7JYDd\nKYHlSfUGvTLz5xFxLGWRpd9ExBnAglX7WcCBmXlbrdmxwA7AbsAvIuICymK0b6RkQN/Z51b7AZcB\nn4uIbShDfTcCtqQM4T201q+HImJfSpB6UUScCtwHvJ4ypPj0zPzWSK9tNAPNnEqSJEnSFLZKVc4A\nDgIO7/PYq0+7t1Kykd8ZS6Y1Mw8B9gb+RJmnuidlbuuOmfnFPvWfALYFPkYJYA8CtgHOBDbIzCv7\ntLkJWJ+yavBGlGB4VcoCTxtn5n192pwNbAFcTFlT6ADKysPvB/YY7XWNZgr+XqHJZOF19x9quw+a\nfz16zecBWOTlB7TcE83vrjz3k213QfOxtVdcHIDf/uHhlnui6WCdlWZOme/3e/3Pr1v7HnnSW142\nZf5O08lcDeuNiCMoG7A2LjM/OhHXlSRJkjR5NLEwkeYvczvn9IhGezHHEGBwKkmSJEnTzGRbEMmf\nTyRJkqRpwC/+qpvb4HTrRnsxh/MXJUmSJGkamqvgNDMvargfkiRJkqaRGc45VY1byUiSJEmSWmdw\nKkmSJElq3WRbEEmSJEnSNOCoXtU1GpxGxJrA7ygLG+2cmeeMoc3rgbOAp4HZmfl/TfZJkiRJkjT5\nNT2s9y1V+cexBKaVc4Fbq768ZZS6kiRJkuYDnU6ntYcmp6aD0y2q8rtjbZCZQz31t2q4P5IkSZKk\nKaDp4HTNqrxmnO1+U2svSZIkSZpGml4QaVZV3jPOdvdV5VIN9kWSJEnSJOXoWtU1nTl9pCqXGGe7\nmVX5RIN9kSRJkiRNEU1nTu+kBKYbACeOo90GVXlXw/2RJEmSNAnNMHWqmqYzp5dU5ZsjYtaINSsR\nsRSwR/X0sob7I0mSJEmaApoOTk+tylnAtyJikZEqR8SiwGnMmav6zYb7I0mSJGkS6nTae2hyajQ4\nzcwLgJ9UT18N/Coi3lbPokbEUhHxdsqqvq+uDv80M3/YZH8kSZIkSVND03NOAd4C/AJYBVgDOAl4\nOiL+DDwMLA48n2cGxjcDu09AXyRJkiRJU0DTw3rJzLuBjYDeLOgMYHngxVXZe9/vAxtm5p+b7osk\nSZKkyanT6bT20OQ0EZnTboD6uojYBHgrsBmwImUl3weB2ymLJ30jM38xEX2QJEmSJE0dExKcdmXm\nZbgC73ztvis/33YXNA34PtNEW++I89ruguZjvzvqHwHY/Ut+JZJ6NT6EU1Oe7wlJkiRJUusMTiVJ\nkiRJrZvQYb2SJEmS1I8LE6nOzKkkSZIkqXVmTiVJkiQN3AwTp6oxcypJkiRJap2ZU0mSJEkDZ+ZU\ndWZOJUmSJEmtMziVJEmSJLXOYb2SJEmSBs6tZFRn5lSSJEmS1LoJz5xGxILAqsBSwIKZefFE31OS\nJEnS5OaCSKqbsOA0Il4DHAy8ClgI6ABDwHNq9fYD1gXuyMyPTFR/JEmSJEmTV+PBaUQsAHwV2GuM\nTe4C/gkYiogTM/OWpvskSZIkSZrcJmLO6ZeYE5g+AHwT+M4I9c+p6nWAnSagP5IkSZImmU6nvYcm\np0aD04jYFNinenoesGpmvhU4Zbg2mflkVRdg8yb7I0mSJEmaGpoe1vtPVflHYNfMfGSM7a4B3gj8\nQ8P9kSRJkjQJzTCFqZqmh/V2M58njiMwhRLMAryg4f5IkiRJkqaApjOn3eDy2nG2e7QqF26wL5Ik\nSZImqYlY/EZTW9Pviafm8rqzqvKBBvsiSZIkSZoimg5O/1SVLx5nu/Wr8rYG+yJJkiRJmiKaDk4v\nrcpdxtogImYCb6qeXtxwfyRJkiRNQm4lo7qmg9NTq3LdiDhwtMoRMQP4CnOG9Z7ccH8kSZIkSVNA\nowsiZeYPI+JCYCvgMxGxMnAMMNRbLyIWoKzsewTwqurwaZn5qyb7I0mSJGlycisZ1TW9Wi/AHsDP\ngdWAfwHez5yFjjoRcTPwfGCRnjbXAu+agL5IkiRJkqaAxldwzsy7gQ2Bs3vusVRPlRfxzMD0DGCz\nzHyo6b5IkiRJkqaGicickpn3AjtHxCuAt1GG7q4CLAk8DPwB+ClwcmZeMRF9kCRJkjR5OapXdRMS\nnHZl5tXA1RN5D0mSJEnS1DehwakkSZIk9TPDzKlqGp9zKkmSJEnSeJk5lSRJkjRwbiWjukaD04g4\ngdqepuOVme9sqDuSJEmSpCmi6czpXvPYfggwOJUkSZKkaWayDes1ty9JkiRNA47qVV3TwelqY6gz\nA1gG2Ah4D/AS4JvAYczjkGBJkiRJ0tTUaHCambeMsepNwBUR8WXgv4B3AA9n5j832R9JkiRJk5Nb\nyaiu1a1kMvNJ4F1AAv8UEa9tsz+SJEmSpHa0vs9pZv4NOJky3/Q9LXdHkiRJktSCybIg0o1VuV6r\nvZAkSZI0EB3XQlVN65nTyuJV+bxWeyFJkiRJasVkyZzuUpV/abUXkiRJkgbCBZFU12pwGhGLAUcC\nr6sO/azF7kiSJEmSWtJocBoRJzC2vUoXBF4IbAAsWh17Gjimyf5IkiRJmpzMnKqu6czpXnPZ7glg\nv8y8ssnOSJIkSZKmhrbnnN4C/BD4XGZe13JfJEmSJEktaTo4XW2M9R4H7s/MRxu+vyRJkqQpoNNx\nXK+eqdHgNDNvafJ6kiRJkqTpoekFkbagLIj0QGb+uslrS5IkSZp/uCCS6mY0fL0Lq8ebG76uJEmS\nJGk+1nRw+ijQAX7T8HUlSZIkSfOxphdEupOyKFLTQa8kSZKk+YjrIamu6SDyoqpcr+HrSpIkSZLm\nY00Hp18Gngb2iojlG762JEmSpPnEjE6ntYcmp0aD08y8CjgMmAX8JCLWafL6kiRJkqT501zPOY2I\nvSjbxlyYmbf3HLsT+CGwHXBNRFwCXAL8kbJg0ogy8+S57ZMkSZKkqcGtZFQ3LwsinUAJTncGbq8d\n677VZgBbVI+xGAIMTiVJkiRpmpnXYb39fu+Yl99A/P1EkiRJkqahed1KZqj2/J0NX0+SJEnSfMh1\niVTX6D6nmXlik9eTJEmSJE0PjQankiRJkjQWM5zRp5qm9zmVJEmSJGncDE4lSZIkSa2b12G9HeC9\nEfGGJjoDkJnzuqiSJEmSpEnOBZFU18Sc060buEbXEPO+4q8kSZIkaYqZbAsi+fuJJEmSNA3M8Ju/\napoITo8DrmngOuA+p5IkSZI0Lc1rcDoE/CQzz2miM5IkSZKmhxlOOlWNq/VKkiRJklpncCpJkiRJ\nat1kWxBJkiRJ0jTgqF7VmTmVJEmSJLXOzKkkSZKkgXNBJNXNa+a0g3uTSpIkSZLm0bxkTleryrua\n6IgkSZIkafqa6+A0M29psB+SJEmSphFH9arOBZEkSZIkSa1zQSRJkiRJA2eWTHW+JyRJkiRJrTNz\nKkmSJGngOk46VY2ZU0mSJElS6wxOJUmSJEmtc1ivJEmSpIFzUK/qzJxKkiRJklpn5lSSJEnSwM1w\nQSTVmDmVJEmSJLXO4FSSJEmS1DqH9UqSJEkaOAf1qs7MqSRJkiSpdWZOJUmSJA2c6yGpzsypJEmS\nJKl1Zk4lSZIkDVzH1KlqzJxKkiRJklpncCpJkiRJap3DeiVJkiQN3FTMkkXE0sAuwPbAOsAKwBPA\ntcAJwAmZOdRTfwFgf2Bd4OXAWpQYbN/M/Poo99qrarsm8BRwDXB0Zn5vmPqLAB8E9gBWBh4ELgKO\nyMzrhmmzIvBRYDtgaeBO4CzgyMy8f5g2mwCHARsDCwM3AMcDx2Xm0yO9ptFMxfeEJEmSJLXhTcBX\ngA2AnwOfAc4A1ga+BnyrVn/xqs7bgedTgj+AIUYQEUdTgt3lqvt9gxIMnxsR+/epvxDwY+DfgPuB\nzwLnAzsDV0XEhn3arA78EngHcDlwLHAT8D7g51UgXm+zE3AxsFn1uo8DFqxe46kjvaaxMDiVJEmS\nNHCdTqe1xzy4HtgxM1fMzLdl5qGZuQ/wEuB2YNeI2KWn/iPAa4EVMnMFSsA5oiozeTBwI/DSzPyX\nzDwAWA+4Fzg6Il5Ua3YwsAlwemZulJkfysy3ArsBiwLHR0T9hX8RWBY4MDN3ycwPZ+Y2lEBzNnBU\nrV9LAF/l/7d352GWVOUBxt87si8yEhA3YBD5MKKCIG4ga4ZFEdCAoKKIQCIkGCQkoERHVBIVJISI\niVE2NQoKiCAoKKuIqNERFcVPBMEVQRDZGZjOH6euXVNzb6/Tt7qb9zfPfepW3TqnTlXfB/rr7yyw\nCNguMw/OzKMoWeFvAntFxD6j3d9IDE4lSZIkaQwy84pe3Woz83bgv6vdbWvHF2XmJdXnY/XWantc\nZt5Tq+tW4BRgReCA7vEq6HwrJRv7z412XQB8ndKdeNtamQ2B+cAtmXlK4/oLgAeA/SJildrxvYC1\ngLMy83u1azxM6eYLcMg47nMpBqeSJEmSNHmPNrYTtQMl0PxKj8++XG23rx3bEFgXyCqA7Vdmh9qx\nbvlLmydn5n3AN4BVKeNK6+2iT7uuBh4EXhoRy/f4fEwMTiVJkiQNXKfF17JWTXz0pmq3V/A21npW\npUyydF+fbOtN3VNrxzauttmn2m6ZjcZR5mfjKZOZjwG3UCZ7emafOkdlcCpJkiRJk/MBYBPgosz8\n6iTqWaPa3tPn8+7xuS2VGRqlTKdRZlxcSkaSJEnSwE1yYqJpIyLeRpmQ6CfAG1tuzoxm5lSSJEmS\nJiAi/p6ybMsNwPb91gYdh25Wco0+n3eP168zyDKdcZYZF4NTSZIkSQM3p8XXshARhwMnAz+kBKa/\nn2ydmXk/8BtgtYh4So9TumNA6+M+b+w2qU+1I5XZmN56lflpvzLVmNsNKMvM3NynzlEZnEqSJEnS\nOETEUcCJwEJKYHrnMqz+MkqGcpcen+1abS/vHsjMnwO3ARtHxLyxlAGuqLbzm+ufRsTqwFaUNVqv\na7SLPu3aBlgZuDYzF/X4fEwMTiVJkiRpjCLiXcC/Af8H7JiZdy3jS3TXSz0mIv48uVAVeP4d8BBw\nep8yH6oHmxGxB7A1cENmXtU9npk3U5aR2aCqs+5YYBXgU5n5YO34OcCdwL4RsUXtGisB7692/2vs\nt7k0J0SSJEmSNHAzcUKkiNifErw9BlwDHB6xVG/aWzLzzFqZo4FnV7ubVdu3RMQ21fuvZ+ap3fMz\n85sRcSJlkqUfRMS5wArAPpSZcA/LzNsa1zwR2A3YC/hWRFwOrAfsTcmAvqXH7RwKXAucHBE7Urr6\nvhjYjtKF95j6yZl5b0QcTAlSr4yIs4C7gd0pXYo/n5mf63GdMTM4lSRJkqSxmVdt5wCH9znnSuDM\n2v7OwLaUZVioti8FXla9XwycWjufzDwyIn5IyWoeTAmGvwccn5kXNy+YmY9ExHzgaOB1VdvuAc4D\nFmTmjT3K3BwRLwTeS+mq+wrKeNeTgGMzc6klYzLzixGxLSVw/WtgJcqaqG+njL+dlJn35wpNKw8u\nGhoa/SxpYlaq/nz20KPttkOz3xYLLm27CZrFbjhuJwA2Ocbvmabej/915xnz+/0Xrv9ta79HvnrT\np86Y5/R44phTSZIkSVLr7NYrSZIkaeBm4JBTTTEzp5IkSZKk1hmcSpIkSZJaZ7deSZIkSQM3x7lZ\n1WDmVJIkSZLUOjOnkiRJkgbOCZHUZOZUkiRJktQ6g1NJkiRJUuvs1itJkiRp4DpOiKQGM6eSJEmS\npNaZOZUkSZI0cE6IpCYzp5IkSZKk1pk5lSRJkjRwcxxzqgYzp5IkSZKk1hmcSpIkSZJaZ7deSZIk\nSQPnhEhqMnMqSZIkSWqdmVNJkiRJA2fmVE1mTiVJkiRJrTM4lSRJkiS1zm69kiRJkgau4zqnajBz\nKkmSJElqnZlTSZIkSQM3x8SpGsycSpIkSZJaZ+ZUkiRJ0sA55lRNZk4lSZIkSa0zOJUkSZIktc5u\nvZIkSZIGrmOvXjWYOZUkSZIktc7MqSRJkqSBc0IkNZk5lSRJkiS1zuBUkiRJktQ6u/VKkiRJGrg5\n9upVg8HpNBYR2wCvArYGNgZWB+4Gvg/8L/DJzBwapY6NgKOB+cA6wB+Aq4DjM/N7U9d6SZIkSRo7\nu/VOUxFxDHAl8I/Ai4HVgHuBvwD+CjgduDIiVh+hjvmUQPYA4OnA/cCTgX2A6yLiDVN4C5IkSVJf\nnRb/aXoyOJ2+lqNkOU8EXgKslJlrAmsBxwKPAS8HPtGrcEQ8BTgHWBm4FJhXlX8qJeu6HHBqRDxn\niu9DkiRJkkY1q4PTiHhRRETb7ZigLwAbZOaRmfntzFwMkJl3Z+axwPuq8/aOiPV6lD+a0g34NuA1\nmfnLqvwdwP7Ad4EVgPdO8X1IkiRJS+l02ntpeprVwSnwCuDGiLgmIg4cqQvsdJOZP8jM+0Y45Yxq\nOwRsUf8gIuYA+1a7/5WZDzTqXkzJyAK8ciY9F0mSJEmz02wPTn8JLAJeBnwcuD0iPhkR27fbrGXi\nrmrbYemf43MoY0uHgEv6lL+02q5AmXBJkiRJklozq4PTzDyVMhHQ4cBCYEVgP+CyiLglIhZExLwW\nmzgZ21bbIeBHjc+eU/vsx70KZ+YfgDsowe1fTkUDJUmSpH46Lb40Pc36pWQy807gZODkiHgu8Gbg\nDcD6wAJgQURcSZn99txmF9i6iHgP8O4JNuXYaqzopFXddrt1XZeZP22c8tRqe3dmPjJCVb8B1q6d\nL0mSJEmtmPXBaV1m/gg4MiKOAnamBKq7AdtVr49ExOeAMzLzGz2quBf43QQvf+8Ey/XyPmBzSpfl\nf+jx+arV9sFR6ukG4qsto3ZJkiRJYzLHmYnU8LgKTrsy8zHgYuDiiJhLmTzozcCLgAOBAyPinZn5\ngUa5DwMfHnBzlxARrwPeQemy+47M/L8227PS4/IbpEHze6apdsNxO7XdBD0O+D3TVNvkmEtHP0ma\nxmb1mNOxyMw/AucBZwG/qg4PUSYKmlYi4pXAmdXuyZl5Yp9T76+2K49S5SrVdqRZgSVJkiRpyj1u\n8xERsSKwO/AmYBfgCdVHtwOfBj7ZUtN6iogdgXMoP7PTMvPtI5z+62r7pIhYYYRxp0+rtr+daLse\nenSiJaXRdTOmfs801bZYYLZBU6ebMTWrJS3JTr1qetwFpxHxEmB/YB9gbnX4EeBCyqRIF1XrgPYq\neyRw5AQvfXzVLXjcImJr4ALKbMNnAwePUqQ7Q28H2IQyU3GzzrUokyHVz5ckSZKkVjwugtOIWA94\nIyVLulF1eAj4ISUg/XQ1q+9oVmV4/dDxWnX0U5YWES8CLqJ00b0A2C8zR7v+TygZ4HWA+fQITqvj\nAA8D10ykbZIkSdKEmTpVw6wOTiNiK8rMttvVDt8FfBY4PTO/N576qqVglslyMGMREZsCXwFWBy4F\n9q4mcxpRZg5FxFmUmXwPjYiP1JfIqZai6XYLvjAzHXMqSZIkqVWzfUKk+ZTA9DHgEsqsvE/LzMPG\nG5gOWkRsTAlI5wJXAntm5qJxVPEB4E/AesB5EbFuVe/awBnACylZ0wXLrtWSJEnS2HRa/KfpaVZn\nToFbgWOAMzPzN203ZpyOYnhM6KbALyKi37lLjWfNzNsjYi/gfGAn4NaI+BPwxOqURcCBmfmTZd5y\nSZIkSRqnWR2cZubpbbdhEjoMj22dO9KJ9BnPmplfi4jNKOui/hVlvOxvgauBD2Vmr7GokiRJkjRw\nszo4ncky8wDggGVQz03AgZNvkSRJkrTsdOxdq4bZPuZUkiRJkjQDmDmVJEmSNHAmTtVk5lSSJEmS\n1DqDU0mSJElS6+zWK0mSJGnw7NerBjOnkiRJkqTWmTmVJEmSNHAdU6dqMHMqSZIkSWqdmVNJkiRJ\nA9cxcaoGM6eSJEmSpNYZnEqSJEmSWme3XkmSJEkDZ69eNZk5lSRJkiS1zsypJEmSpMEzdaoGM6eS\nJLw24aUAABhMSURBVEmSpNYZnEqSJEmSWme3XkmSJEkD17FfrxrMnEqSJEmSWmfmVJIkSdLAdUyc\nqsHMqSRJkiSpdWZOJUmSJA2ciVM1mTmVJEmSJLXO4FSSJEmS1Dq79UqSJEkaPPv1qsHMqSRJkiSp\ndWZOJUmSJA1cx9SpGsycSpIkSZJaZ3AqSZIkSWqd3XolSZIkDVzHXr1qMHMqSZIkSWqdmVNJkiRJ\nA2fiVE1mTiVJkiRJrTNzKkmSJGnwTJ2qwcypJEmSJKl1BqeSJEmSpNbZrVeSJEnSwHXs16sGM6eS\nJEmSpNaZOZUkSZI0cB0Tp2owcypJkiRJap3BqSRJkiSpdXbrlSRJkjRw9upVk5lTSZIkSVLrzJxK\nkiRJGjxTp2owcypJkiRJap2ZU0mSJEkD1zF1qgYzp5IkSZKk1hmcSpIkSZJaZ7deSZIkSQPXsVev\nGsycSpIkSZJaZ+ZUkiRJ0sCZOFWTmVNJkiRJUusMTiVJkiRJrbNbryRJkqTBs1+vGsycSpIkSZJa\nZ+ZUkiRJ0sB1TJ2qwcypJEmSJKl1Zk4lSZIkDVzHxKkazJxKkiRJklpncCpJkiRJap3deiVJkiQN\nnL161WTmVJIkSZLUOjOnkiRJkgbP1KkaDE4lSZIkaQwiYi9gW2AzYFNgNeB/M/ONPc6dB9w8QnVn\nZ+br+lxnf+DvgL8EHgMWAidk5kV9zl8ZOBrYF1gP+BNwJbAgM2/sU+YZwHuBXYA1gd8C5wPHZuYf\n+5R5GfAvwEuAlYCfAacB/5mZi0e41zExOJUkSZKksfkX4PnAvcCvgGcDQ6OU+T4l6Gv6Ua+TI+IE\n4Ajgl8D/ACtSgs4LI+KwzDylcf6KwFeBlwHfAc6jBKh7A6+MiB0y89uNMhsC1wJrV227EXgx8A/A\nLhGxVWbe1SizB3Au8ABwNnAXsDvw78BWwGtHeQ6jMjiVJEmSNHCdmdmv93Dgl5n584jYFrhiDGW+\nn5nvHUvlVWbyCOAmYMvMvKc6fjzwXeCEiPhSZt5aK3YEJTD9fGbuU6vrbErgeVpEPC8z60H0RymB\n6RLBbkR8GHg7cBxwSO34E4GPA4uA7TLze9XxdwOXA3tFxD6ZefZY7rMfJ0SSJEmSpDHIzCsz8+fV\n7lRE12+ttsd1A9PqurcCp1CyqAd0j0dEpyozBPxzo60XAF8HnkPpitwtsyEwH7ilmYUFFlAyo/tF\nxCq143sBawFndQPT6hoPU7LJUAtmJ8rgVJIkSdLAdTrtvQbs6RHxtxHxzmr7vBHO3YESaH6lx2df\nrrbb145tCKwLZCOb2iyzQ+1Yt/ylzZMz8z7gG8CqlHGl9XbRp11XAw8CL42I5Xt8PmYGp5IkSZI0\ndeYD/wW8v9peHxGXR8S69ZMiYlXgacB9mXl7j3pu6p5aO7Zxtc0+1+6W2WgcZX42njKZ+RhwC2XI\n6DP71DkmBqeSJEmSBq7T4mtA7qfMhrs5MLd6dcepbgdc1ug6u0a1vYfeusfntlRmaJQynUaZcXNC\nJEmSJElaxjLzDuA9jcNfj4idgGsos+MeBJw84KZNW2ZOJUmSJGlAqm6wn6h2X177qJuVXIPeusfr\na5AOskxnnGXGzeBUkiRJ0uA9Dvr1juDOartq90Bm3g/8BlgtIp7So0x3DGh93OeN1TbobaQyG9Nb\nrzI/7VcmIpYDNqAsM3NznzrHxOBUkiRJkgarOxNuM5i7jBI+79KjzK7V9vLugWpZm9uAjSNi3ljK\nMLw26/xqKZo/i4jVga0o42Wva7SLPu3aBlgZuDYzF/X4fMwMTiVJkiQNXKfFf4MQEZs3g7/q+I7A\n2ykTDH268fF/V9tjImJurcw84O+Ah4DT+5T5UP16EbEHsDVwQ2Ze1T2emTdTlpHZoKqz7lhgFeBT\nmflg7fg5lGzvvhGxRe0aK1FmIYYyE/GkOCGSJEmSJI1BROwJ7Fntdrveviwizqje35GZ/1S9PxF4\nVkRcC/y6OvZ8yjqjQ8C7MrOenSQzvxkRJwJHAD+IiHOBFYB9KDPhHpaZtzWadSKwG7AX8K2IuBxY\nD9ibkgF9S49bORS4Fji5CpZvpEzQtB2lC+8xjXbdGxEHU4LUKyPiLOBuYHdKl+LPZ+bnej60cTBz\nKkmSJEljsynwJuCNlPVLhygZyDdVr7+unftJYCGwJWVW3kOADYGzgW0y8197XSAzjwQOAH4HHAzs\nB/wQeFVmfrTH+Y9UbXkfJYA9HNgROA/YMjO/06PMzcALgTMoQekR1X2cBLwkM+/uUeaLlKVwrq7u\n8++BhylZ4H173ct4TY/hwJqxHlw0NNR2GzR7rVT17Xjo0XbbodlviwWXtt0EzWI3HLcTAJsc4/dM\nU+/H/7rzjPn9/tY/PNTa75Hr/8VKM+Y5PZ6YOZU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"text": [ "" ] } ], "prompt_number": 10 }, { "cell_type": "markdown", "metadata": {}, "source": [ "A very nice confusion matrix!" ] }, { "cell_type": "code", "collapsed": false, "input": [ "# A function for plotting a couple of AUC, one per class.\n", "def plot_auc(a_scores, b_scores, auc_scores, messages):\n", " \n", " # First axis.\n", " \n", " a_scores_copy = {}\n", " a_scores_avg = {}\n", " \n", " max_length = 0\n", " \n", " for a in a_scores[classes[1]] + a_scores[classes[2]]:\n", " length = len(a)\n", " if length > max_length:\n", " max_length = length\n", " \n", " for c in classes[1:]:\n", " a_scores_copy[c] = []\n", " \n", " for a in a_scores[c]:\n", " length = len(a)\n", " \n", " if length < max_length:\n", " for i in range(length, max_length):\n", " a = np.append(a, a[length - 1])\n", " \n", " a_scores_copy[c].append(a)\n", " \n", " a_scores_avg[c] = np.average(np.array(a_scores_copy[c]), axis=0)\n", "\n", " # Second axis.\n", "\n", " b_scores_copy = {}\n", " b_scores_avg = {}\n", "\n", " for c in classes[1:]:\n", " b_scores_copy[c] = []\n", " \n", " for b in b_scores[c]:\n", " length = len(b)\n", " \n", " if length < max_length:\n", " for i in range(length, max_length):\n", " b = np.append(b, b[length - 1])\n", " \n", " b_scores_copy[c].append(b)\n", " \n", " b_scores_avg[c] = np.average(np.array(b_scores_copy[c]), axis=0)\n", "\n", " # Plotting.\n", "\n", " fig, ax = plt.subplots(1, 2, figsize=(12, 6))\n", " i = 0\n", "\n", " for c in classes[1:]:\n", " a = a_scores_avg[c]\n", " b = b_scores_avg[c]\n", " auc_score = np.mean(auc_scores[c])\n", "\n", " if messages['title'] == 'ROC':\n", " ax[i].plot([0, 1], [0, 1], 'k--')\n", " ax[i].plot(a, b)\n", " else:\n", " ax[i].plot(b, a)\n", "\n", " ax[i].set_xlim([0.0, 1.0])\n", " ax[i].set_ylim([0.0, 1.0])\n", " \n", " if messages['title'] == 'ROC':\n", " ax[i].fill_between(a, b, alpha=0.5)\n", " else:\n", " ax[i].fill_between(b, a, alpha=0.5)\n", " \n", " ax[i].set_title(messages['title'] + ' curve (AUC = %0.2f) | Class \"%s\"' % (auc_score, c), fontsize=15)\n", " ax[i].set_xlabel(messages['x_label'], fontsize=15)\n", " ax[i].set_ylabel(messages['y_label'], fontsize=15)\n", " \n", " ax[i].tick_params(labelsize=12)\n", " \n", " i += 1\n", "\n", " fig.tight_layout()" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 11 }, { "cell_type": "code", "collapsed": false, "input": [ "messages = {'title': 'P/R', 'x_label': 'Recall', 'y_label': 'Precision'}\n", "plot_auc(precision_scores, recall_scores, pr_auc_scores, messages)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": { "png": { "height": 425, "width": 857 } }, "output_type": "display_data", "png": 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13r9bKl8SeE3bFXZpQHbp+PWSzZeUzZc0PD73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\nZHeSd1RV5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"text": [ "" ] } ], "prompt_number": 12 }, { "cell_type": "code", "collapsed": false, "input": [ "messages = {'title': 'ROC', 'x_label': 'False positive rate', 'y_label': 'True positive rate'}\n", "plot_auc(fpr_scores, tpr_scores, roc_auc_scores, messages)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": { "png": { "height": 425, "width": 857 } }, "output_type": "display_data", "png": 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hCFfETd9rZm9JtKCZHWJme5XacH6A0H8FLw8Ibi4OXq8Qf7GajouOZO4OvhcD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\nDH3z2z/S0AO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"text": [ "" ] } ], "prompt_number": 13 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Both kind of curves look very good, specially the AUC ones, with an area of `0.75`." ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "6.4. Predicting a pseudo-real example" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's create an example and check how the classifier predict it.\n", "\n", "Imagine you are a CFO that works near the [NYSE](https://www.nyse.com) and you go out the building at 11:30 a.m. to catch a train in Penn Station to go to Boston and sign a contract with, for example, [Boston Dynamics](http://www.bostondynamics.com/). As Google Maps [suggest](https://www.google.com/maps/dir/40.707129,+-74.010729/40.749714,+-73.991562/@40.7308984,-74.0198038,14z/data=!3m1!4b1!4m10!4m9!1m3!2m2!1d-74.010729!2d40.707129!1m3!2m2!1d-73.991562!2d40.749714!3e0), it's a 24 minutes trip, with a distance of 4.4 miles. And, as we can check in [TaxiFareFinder](http://www.taxifarefinder.com/main.php?city=NY&from=NYSE%2C+Wall+Street%2C+New+York%2C+NY%2C+United+States&to=Penn+Station%2C+New+York%2C+NY%2C+United+States&fromCoord=40.706877,-74.01126499999998&toCoord=40.75058,-73.99358000000001), the trip will cost $16.30.\n", "\n", "So, if you are a CFO in company located in Wall Street, are you going to give a tip less than `20%`?" ] }, { "cell_type": "code", "collapsed": false, "input": [ "pseudo_real_features = np.array([1624.0, 10429.0, 0.0, 9.0, 4.0, 5.0, 690, 0.0, 0.0, 16.30, 0.0, 0.0, 1.0, 1440, 4.4,\n", " -74.010729, 40.707129, -73.991562, 40.749714])" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 14 }, { "cell_type": "code", "collapsed": false, "input": [ "prediction = clf.predict(pseudo_real_features)\n", "prediction.tolist()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 15, "text": [ "['>= 20']" ] } ], "prompt_number": 15 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Of course **not**.\n", "\n", "Let's check the [last notebook](7. A brief conclusions.ipynb) and see a brief conclusions about the work done in this project." ] } ], "metadata": {} } ] }