www.gusucode.com > 支持向量机工具箱 - LIBSVM OSU_SVM LS_SVM源码程序 > 支持向量机工具箱 - LIBSVM OSU_SVM LS_SVM\stprtool\bayes\bhattach.m
function [eps]=bhattach(M1,M2,C1,C2,P1,P2) % BHATTACH upper estimate on Bayes class. error. % [eps]=bhattach(M1,M2,C1,C2,P1,P2) % % BHATTACH calculates Bhattacharya's limit, i.e. upper estimate % of mean classification error for Bayesian classifier % minimizing errorneous classification into two classes for % normally (Gauss) distributed conditional probabilities p(x|k). % The conditional probabilities are p(x|k) are described by % a pair of mean value and covariance matrix. % % Input: % M1 [Nx1] - mean value for class 1 % M2 [Nx1] - mean value for class 2 % C1 [NxN] - covariance matrix for class 1 % C2 [NxN] - covariance matrix for class 2 % P1 [1x1] - apriori probability for class 1 % P2 [1x1] - apriori probability for class 2 % % where N is dimension of the feature space. % % Output: % eps - upper limint of the mean classification error % % See also BAYESCLN. % % Statistical Pattern Recognition Toolbox, Vojtech Franc, Vaclav Hlavac % (c) Czech Technical University Prague, http://cmp.felk.cvut.cz % Written Vojtech Franc (diploma thesis) 02.01.2000 % Modifications % 24. 6.00 V. Hlavac, comments into English. M1=M1(:); M2=M2(:); d=(1/8)*(M2-M1)'*inv((C1+C2)/2)*(M2-M1)+(1/2)*... log( det((C1+C2)/2) / sqrt(det(C1)*det(C2)) ); eps=sqrt(P1*P2)*exp(-d);