{ "cells": [ { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# HIDDEN\n", "import matplotlib\n", "#matplotlib.use('Agg')\n", "from datascience import *\n", "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "from mpl_toolkits.mplot3d import Axes3D\n", "import numpy as np\n", "import math\n", "import scipy.stats as stats\n", "plt.style.use('fivethirtyeight')" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# HIDDEN\n", "\n", "def standard_units(x):\n", " return (x - np.mean(x))/np.std(x)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# HIDDEN\n", "\n", "def distance(pt1, pt2):\n", " \"\"\"The Euclidean distance between two arrays of numbers.\"\"\"\n", " return np.sqrt(np.sum((pt1 - pt2)**2))\n", "\n", "def distance_from_individual(attribute_table, i, p):\n", " \"\"\"The Euclidean distance between p (an array of numbers) and the numbers in row i of attribute_table.\"\"\"\n", " return distance(np.array(attribute_table.row(i)), p)\n", "\n", "def table_with_dists(training, p):\n", " \"\"\"A copy of the training table with the Euclidean distance from each row to array p.\"\"\"\n", " dists = make_array()\n", " attributes = training.drop('Class')\n", " for i in np.arange(training.num_rows):\n", " dists = np.append(dists, distance_from_individual(attributes, i , p))\n", " return training.with_column('Distance', dists)\n", "\n", "def closest(training, p, k):\n", " \"\"\"A table containing the k closest rows in the training table to array p.\"\"\"\n", " with_dists = table_with_dists(training, p)\n", " sorted_by_dist = with_dists.sort('Distance')\n", " topk = sorted_by_dist.take(np.arange(k))\n", " return topk\n", "\n", "def majority(topkclasses):\n", " \"\"\"1 if the majority of the \"Class\" column is 1s, and 0 otherwise.\"\"\"\n", " ones = topkclasses.where('Class', are.equal_to(1)).num_rows\n", " zeros = topkclasses.where('Class', are.equal_to(0)).num_rows\n", " if ones > zeros:\n", " return 1\n", " else:\n", " return 0\n", "\n", "def classify(training, p, k):\n", " \"\"\"Classify an example with attributes p using k-nearest neighbor classification with the given training table.\"\"\"\n", " closestk = closest(training, p, k)\n", " topkclasses = closestk.select('Class')\n", " return majority(topkclasses)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Nearest Neighbors ###\n", "In this section we'll develop the *nearest neighbor* method of classification. Just focus on the ideas for now and don't worry if some of the code is mysterious. Later in the chapter we'll see how to organize our ideas into code that performs the classification." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Chronic kidney disease\n", "\n", "Let's work through an example. We're going to work with a data set that was collected to help doctors diagnose chronic kidney disease (CKD). Each row in the data set represents a single patient who was treated in the past and whose diagnosis is known. For each patient, we have a bunch of measurements from a blood test. We'd like to find which measurements are most useful for diagnosing CKD, and develop a way to classify future patients as \"has CKD\" or \"doesn't have CKD\" based on their blood test results." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
Age | Blood Pressure | Specific Gravity | Albumin | Sugar | Red Blood Cells | Pus Cell | Pus Cell clumps | Bacteria | Glucose | Blood Urea | Serum Creatinine | Sodium | Potassium | Hemoglobin | Packed Cell Volume | White Blood Cell Count | Red Blood Cell Count | Hypertension | Diabetes Mellitus | Coronary Artery Disease | Appetite | Pedal Edema | Anemia | Class | \n", "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
48 | 70 | 1.005 | 4 | 0 | normal | abnormal | present | notpresent | 117 | 56 | 3.8 | 111 | 2.5 | 11.2 | 32 | 6700 | 3.9 | yes | no | no | poor | yes | yes | 1 | \n", "
53 | 90 | 1.02 | 2 | 0 | abnormal | abnormal | present | notpresent | 70 | 107 | 7.2 | 114 | 3.7 | 9.5 | 29 | 12100 | 3.7 | yes | yes | no | poor | no | yes | 1 | \n", "
63 | 70 | 1.01 | 3 | 0 | abnormal | abnormal | present | notpresent | 380 | 60 | 2.7 | 131 | 4.2 | 10.8 | 32 | 4500 | 3.8 | yes | yes | no | poor | yes | no | 1 | \n", "
68 | 80 | 1.01 | 3 | 2 | normal | abnormal | present | present | 157 | 90 | 4.1 | 130 | 6.4 | 5.6 | 16 | 11000 | 2.6 | yes | yes | yes | poor | yes | no | 1 | \n", "
61 | 80 | 1.015 | 2 | 0 | abnormal | abnormal | notpresent | notpresent | 173 | 148 | 3.9 | 135 | 5.2 | 7.7 | 24 | 9200 | 3.2 | yes | yes | yes | poor | yes | yes | 1 | \n", "
48 | 80 | 1.025 | 4 | 0 | normal | abnormal | notpresent | notpresent | 95 | 163 | 7.7 | 136 | 3.8 | 9.8 | 32 | 6900 | 3.4 | yes | no | no | good | no | yes | 1 | \n", "
69 | 70 | 1.01 | 3 | 4 | normal | abnormal | notpresent | notpresent | 264 | 87 | 2.7 | 130 | 4 | 12.5 | 37 | 9600 | 4.1 | yes | yes | yes | good | yes | no | 1 | \n", "
73 | 70 | 1.005 | 0 | 0 | normal | normal | notpresent | notpresent | 70 | 32 | 0.9 | 125 | 4 | 10 | 29 | 18900 | 3.5 | yes | yes | no | good | yes | no | 1 | \n", "
73 | 80 | 1.02 | 2 | 0 | abnormal | abnormal | notpresent | notpresent | 253 | 142 | 4.6 | 138 | 5.8 | 10.5 | 33 | 7200 | 4.3 | yes | yes | yes | good | no | no | 1 | \n", "
46 | 60 | 1.01 | 1 | 0 | normal | normal | notpresent | notpresent | 163 | 92 | 3.3 | 141 | 4 | 9.8 | 28 | 14600 | 3.2 | yes | yes | no | good | no | no | 1 | \n", "
... (148 rows omitted)
\n", " \n", "... (148 rows omitted)
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ckd.scatter('Hemoglobin', 'Glucose', colors='Color')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Suppose Alice is a new patient who is not in the data set. If I tell you Alice's hemoglobin level and blood glucose level, could you predict whether she has CKD? It sure looks like it! You can see a very clear pattern here: points in the lower-right tend to represent people who don't have CKD, and the rest tend to be folks with CKD. To a human, the pattern is obvious. But how can we program a computer to automatically detect patterns such as this one?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### A Nearest Neighbor Classifier ###\n", "\n", "There are lots of kinds of patterns one might look for, and lots of algorithms for classification. But I'm going to tell you about one that turns out to be surprisingly effective. It is called *nearest neighbor classification*. Here's the idea. If we have Alice's hemoglobin and glucose numbers, we can put her somewhere on this scatterplot; the hemoglobin is her x-coordinate, and the glucose is her y-coordinate. Now, to predict whether she has CKD or not, we find the nearest point in the scatterplot and check whether it is blue or gold; we predict that Alice should receive the same diagnosis as that patient.\n", "\n", "In other words, to classify Alice as CKD or not, we find the patient in the training set who is \"nearest\" to Alice, and then use that patient's diagnosis as our prediction for Alice. The intuition is that if two points are near each other in the scatterplot, then the corresponding measurements are pretty similar, so we might expect them to receive the same diagnosis (more likely than not). We don't know Alice's diagnosis, but we do know the diagnosis of all the patients in the training set, so we find the patient in the training set who is most similar to Alice, and use that patient's diagnosis to predict Alice's diagnosis." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the graph below, the red dot represents Alice. It is joined with a black line to the point that is nearest to it – its *nearest neighbor* in the training set. The figure is drawn by a function called `show_closest`. It takes an array that represents the $x$ and $y$ coordinates of Alice's point. Vary those to see how the closest point changes! Note especially when the closest point is blue and when it is gold." ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# HIDDEN\n", "\n", "def show_closest(point):\n", " \"\"\"point = array([x,y]) \n", " gives the coordinates of a new point\n", " shown in red\"\"\"\n", " \n", " HemoGl = ckd.drop('White Blood Cell Count', 'Color')\n", " t = closest(HemoGl, point, 1)\n", " x_closest = t.row(0).item(1)\n", " y_closest = t.row(0).item(2)\n", " ckd.scatter('Hemoglobin', 'Glucose', colors='Color')\n", " plt.scatter(point.item(0), point.item(1), color='red', s=30)\n", " plt.plot(make_array(point.item(0), x_closest), make_array(point.item(1), y_closest), color='k', lw=2);" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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D67ps2LCXb74poW/fLAYMyGkV3fxXXHEFGRkZTJs2DcdxePbZZykvL+fxxx/X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"text/plain": [ "WaveletVar | WaveletSkew | WaveletCurt | Entropy | Class | \n", "
---|---|---|---|---|
3.6216 | 8.6661 | -2.8073 | -0.44699 | 0 | \n", "
4.5459 | 8.1674 | -2.4586 | -1.4621 | 0 | \n", "
3.866 | -2.6383 | 1.9242 | 0.10645 | 0 | \n", "
3.4566 | 9.5228 | -4.0112 | -3.5944 | 0 | \n", "
0.32924 | -4.4552 | 4.5718 | -0.9888 | 0 | \n", "
4.3684 | 9.6718 | -3.9606 | -3.1625 | 0 | \n", "
3.5912 | 3.0129 | 0.72888 | 0.56421 | 0 | \n", "
2.0922 | -6.81 | 8.4636 | -0.60216 | 0 | \n", "
3.2032 | 5.7588 | -0.75345 | -0.61251 | 0 | \n", "
1.5356 | 9.1772 | -2.2718 | -0.73535 | 0 | \n", "
... (1362 rows omitted)
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "banknotes.scatter('WaveletVar', 'WaveletCurt', colors='Color')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Pretty interesting! Those two measurements do seem helpful for predicting whether the banknote is counterfeit or not. However, in this example you can now see that there is some overlap between the blue cluster and the gold cluster. This indicates that there will be some images where it's hard to tell whether the banknote is legitimate based on just these two numbers. Still, you could use a $k$-nearest neighbor classifier to predict the legitimacy of a banknote.\n", "\n", "Take a minute and think it through: Suppose we used $k=11$ (say). What parts of the plot would the classifier get right, and what parts would it make errors on? What would the decision boundary look like?\n", "\n", "The patterns that show up in the data can get pretty wild. For instance, here's what we'd get if used a different pair of measurements from the images:" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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z0dCQ4g9/WI3jqGHTKYmEQ1dXibVr+5k5s27o9vHjMxx33HTK5TIbN27crj9O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\npQYPQghwHJmqoc7PEtxzzxDd3Rl27pw1T5NSUK0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X4vkem7flMUbgellGJ9qZaSM1wsfg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\nR4uByGgJRqRLDRPjTaoGF0y0sVGdSMWzKPuAnQo67r//furr6zn66K23D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u7cufzgBz/g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\nzsVms7FgwQI6dOjgrSpcs4MHD/L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