annotate toolboxes/FullBNT-1.0.7/netlab3.3/gmmpost.m @ 0:e9a9cd732c1e tip

first hg version after svn
author wolffd
date Tue, 10 Feb 2015 15:05:51 +0000
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wolffd@0 1 function [post, a] = gmmpost(mix, x)
wolffd@0 2 %GMMPOST Computes the class posterior probabilities of a Gaussian mixture model.
wolffd@0 3 %
wolffd@0 4 % Description
wolffd@0 5 % This function computes the posteriors POST (i.e. the probability of
wolffd@0 6 % each component conditioned on the data P(J|X)) for a Gaussian mixture
wolffd@0 7 % model. The data structure MIX defines the mixture model, while the
wolffd@0 8 % matrix X contains the data vectors. Each row of X represents a
wolffd@0 9 % single vector.
wolffd@0 10 %
wolffd@0 11 % See also
wolffd@0 12 % GMM, GMMACTIV, GMMPROB
wolffd@0 13 %
wolffd@0 14
wolffd@0 15 % Copyright (c) Ian T Nabney (1996-2001)
wolffd@0 16
wolffd@0 17 % Check that inputs are consistent
wolffd@0 18 errstring = consist(mix, 'gmm', x);
wolffd@0 19 if ~isempty(errstring)
wolffd@0 20 error(errstring);
wolffd@0 21 end
wolffd@0 22
wolffd@0 23 ndata = size(x, 1);
wolffd@0 24
wolffd@0 25 a = gmmactiv(mix, x);
wolffd@0 26
wolffd@0 27 post = (ones(ndata, 1)*mix.priors).*a;
wolffd@0 28 s = sum(post, 2);
wolffd@0 29 if any(s==0)
wolffd@0 30 warning('Some zero posterior probabilities')
wolffd@0 31 % Set any zeros to one before dividing
wolffd@0 32 zero_rows = find(s==0);
wolffd@0 33 s = s + (s==0);
wolffd@0 34 post(zero_rows, :) = 1/mix.ncentres;
wolffd@0 35 end
wolffd@0 36 post = post./(s*ones(1, mix.ncentres));