?? bhattach.m
字號(hào):
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);
?? 快捷鍵說(shuō)明
復(fù)制代碼
Ctrl + C
搜索代碼
Ctrl + F
全屏模式
F11
切換主題
Ctrl + Shift + D
顯示快捷鍵
?
增大字號(hào)
Ctrl + =
減小字號(hào)
Ctrl + -