Java tutorial
/* LICENSE Copyright (c) 2013-2016, Jesse Hostetler (jessehostetler@gmail.com) All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ /** * */ package edu.oregonstate.eecs.mcplan.ml; import java.io.PrintStream; import java.util.ArrayList; import java.util.Set; import org.apache.commons.math3.linear.RealVector; import org.apache.commons.math3.util.ArithmeticUtils; import org.apache.commons.math3.util.FastMath; import edu.oregonstate.eecs.mcplan.util.Csv; import edu.oregonstate.eecs.mcplan.util.Fn; /** * The contingency table of two partitions. The statistics in the table can * be used to compute various measures of clustering quality. * * We use the notation and function names of: * @article{vinh2010information, * title={Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance}, * author={Vinh, Nguyen Xuan and Epps, Julien and Bailey, James}, * journal={Journal of Machine Learning Research}, * volume={11}, * pages={2837--2854}, * year={2010} * } * * @author jhostetler */ public class ClusterContingencyTable { public final int R; public final int C; public final int[][] n; public final int N; public final int[] a; public final int[] b; public ClusterContingencyTable(final ArrayList<Set<RealVector>> U, final ArrayList<Set<RealVector>> V) { R = U.size(); C = V.size(); int N = 0; a = new int[R]; b = new int[C]; n = new int[R][C]; for (int i = 0; i < R; ++i) { final Set<RealVector> u = U.get(i); for (int j = 0; j < C; ++j) { final Set<RealVector> v = V.get(j); for (final RealVector uu : u) { if (v.contains(uu)) { a[i] += 1; b[j] += 1; n[i][j] += 1; N += 1; } } } } this.N = N; } private ClusterContingencyTable(final int R, final int C, final int[][] n, final int N, final int[] a, final int[] b) { this.R = R; this.C = C; this.n = n; this.N = N; this.a = a; this.b = b; } public double entropyU() { double h = 0.0; for (int i = 0; i < R; ++i) { final double p = a[i] / ((double) N); if (p == 0.0) { continue; } h += -p * FastMath.log(2, p); } return h; } public double entropyV() { double h = 0.0; for (int j = 0; j < C; ++j) { final double p = b[j] / ((double) N); if (p == 0.0) { continue; } h += -p * FastMath.log(2, p); } return h; } public double mutualInformation() { final double Nd = N; double mi = 0.0; for (int i = 0; i < R; ++i) { for (int j = 0; j < C; ++j) { final double p = n[i][j] / Nd; if (p == 0) { continue; } final double q = p / ((a[i] * b[j]) / (Nd * Nd)); mi += p * FastMath.log(2, q); } } return mi; } public double normalizedMutualInformation_max() { return mutualInformation() / Math.max(entropyU(), entropyV()); } public double expectedMutualInformation() { double emi = 0.0; for (int i = 0; i < R; ++i) { for (int j = 0; j < C; ++j) { // We take max( _, 1 ) instead of max( _, 0 ) as in the paper // because when nij is 0, the product is 0, but log( 0 ) // causes NaN. final int start = Math.max(a[i] + b[j] - N, 1); final int end = Math.min(a[i], b[j]); for (int nij = start; nij <= end; ++nij) { final double p = nij / ((double) N); final double L = FastMath.log(2, N * nij / ((double) a[i] * b[j])); final double logNum = ArithmeticUtils.factorialLog(a[i]) + ArithmeticUtils.factorialLog(b[j]) + ArithmeticUtils.factorialLog(N - a[i]) + ArithmeticUtils.factorialLog(N - b[j]); final double logDenom = ArithmeticUtils.factorialLog(N) + ArithmeticUtils.factorialLog(nij) + ArithmeticUtils.factorialLog(a[i] - nij) + ArithmeticUtils.factorialLog(b[j] - nij) + ArithmeticUtils.factorialLog(N - a[i] - b[j] + nij); final double all = p * L * FastMath.exp(logNum - logDenom); emi += all; } } } return emi; } public double adjustedMutualInformation_max() { if (C == 1 && R == 1) { return 1.0; } final double emi = expectedMutualInformation(); assert (!Double.isNaN(emi)); final double HU = entropyU(); final double HV = entropyV(); if (HU < 1e-100 && HV < 1e-100) { return 1.0; } final double num = mutualInformation() - emi; final double denom = Math.max(HU, HV) - emi; // if( Math.abs( denom ) < 1e-100 && Math.abs( num ) < 1e-100 ) { // return 0.0; // } return num / denom; } public ClusterContingencyTable plus(final ClusterContingencyTable that) { assert (R == that.R); assert (C == that.C); final int[][] n = Fn.copy(this.n); for (int r = 0; r < R; ++r) { for (int c = 0; c < C; ++c) { n[r][c] += that.n[r][c]; } } final int[] a = Fn.copy(this.a); for (int r = 0; r < R; ++r) { a[r] += that.a[r]; } final int[] b = Fn.copy(this.b); for (int c = 0; c < C; ++c) { b[c] += that.b[c]; } return new ClusterContingencyTable(R, C, n, N + that.N, a, b); } public void writeCsv(final PrintStream out) { final Csv.Writer csv = new Csv.Writer(out); for (int r = 0; r < R; ++r) { for (int c = 0; c < C; ++c) { csv.cell(n[r][c]); } csv.newline(); } } @Override public String toString() { final StringBuilder sb = new StringBuilder(); final int width = 5; final String fmt = "%" + width + "d"; for (int i = 0; i < width; ++i) { sb.append(" "); } sb.append("|"); for (int j = 0; j < C; ++j) { sb.append(" ").append(String.format(fmt, j)); } sb.append("| ai"); sb.append("\n"); for (int j = 0; j < (width + 1) * (C + 2); ++j) { sb.append("-"); } sb.append("\n"); for (int i = 0; i < R; ++i) { sb.append(String.format(fmt, i)).append("|"); final int max = Fn.argmax(n[i]); for (int j = 0; j < C; ++j) { if (j == max + 1) { sb.append("*"); } else { sb.append(" "); } sb.append(String.format(fmt, n[i][j])); } sb.append("| ").append(String.format(fmt, a[i])); sb.append("\n"); } for (int j = 0; j < (width + 1) * (C + 2); ++j) { sb.append("-"); } sb.append("\n"); sb.append(" bj |"); for (int j = 0; j < C; ++j) { sb.append(" ").append(String.format(fmt, b[j])); } sb.append("| ").append(N); // sb.append( "\n" ); return sb.toString(); } }