001/* 002 * BioJava development code 003 * 004 * This code may be freely distributed and modified under the 005 * terms of the GNU Lesser General Public Licence. This should 006 * be distributed with the code. If you do not have a copy, 007 * see: 008 * 009 * http://www.gnu.org/copyleft/lesser.html 010 * 011 * Copyright for this code is held jointly by the individual 012 * authors. These should be listed in @author doc comments. 013 * 014 * For more information on the BioJava project and its aims, 015 * or to join the biojava-l mailing list, visit the home page 016 * at: 017 * 018 * http://www.biojava.org/ 019 * 020 */ 021/* 022 * @(#)NormalizingKernel.java 0.1 00/01/20 023 * 024 * By Thomas Down <td2@sanger.ac.uk> 025 */ 026 027package org.biojava.stats.svm; 028 029/** 030 * Performs a normalization on the results of a nested kernel. 031 * <p> 032 * This is equivalent to making the locations in feature space of the nested 033 * kernel unit vectors lying on a unit sphere. The dot product in feature space 034 * then becomes just <code>cos theta</code> rather than 035 * <code>||a|| * ||b|| * cos theta</code> as both lengths are 1. The length of 036 * a in the feature space of kernel k is <code>sqrt( k(a, a) )</code>, so that 037 * the normalizing kernel ends up calculating 038 * <code>k(a, b) / sqrt( k(a, a) * k(b, b) )</code>. 039 * <p> 040 * As the values of k(x, x) are required repeatedly, it may be worth making the 041 * nested kernel a DiagonalCachingKernel. 042 * 043 * @author Thomas Down 044 * @author Matthew Pocock 045 */ 046public class NormalizingKernel extends NestedKernel { 047 public NormalizingKernel() {} 048 049 public NormalizingKernel(SVMKernel k) { 050 setNestedKernel(k); 051 } 052 053 public double evaluate(Object a, Object b) { 054 SVMKernel k = getNestedKernel(); 055 double kAA = k.evaluate(a, a); 056 double kBB = k.evaluate(b, b); 057 double kAB = k.evaluate(a, b); 058 return kAB / Math.sqrt(kAA * kBB); 059 } 060 061 public String toString() { 062 return "Normalizing Kernel K(x, y | k) = " + 063 " k(x, y) / sqrt(k(x, x) * k(y, y)); k(x,y) = " + 064 getNestedKernel().toString(); 065 } 066}