BNW using Octave instead of Matlab.

This version of BNW should perform the same as the original version. The only difference is that it uses Octave instead of Matlab when running BayesNet Toolbox during parameter learning.

I am calling this BNW_1.02. It can be accessed at:
compbio.uthsc.edu/BNW_1.02

1 files changed, 26 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/netlab3.3/mdnpost.m b/sourcecodes/bnt-master/netlab3.3/mdnpost.m
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+function [post, a] = mdnpost(mixparams, t)
+%MDNPOST Computes the posterior probability for each MDN mixture component.
+%
+%	Description
+%	POST = MDNPOST(MIXPARAMS, T) computes the posterior probability
+%	P(J|T) of each data vector in T under the Gaussian mixture model
+%	represented by the corresponding entries in MIXPARAMS. Each row of T
+%	represents a single vector.
+%
+%	[POST, A] = MDNPOST(MIXPARAMS, T) also computes the activations A
+%	(i.e. the probability P(T|J) of the data conditioned on each
+%	component density) for a Gaussian mixture model.
+%
+%	See also
+%	MDNGRAD, MDNPROB
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+%	David J Evans (1998)
+
+[prob a] = mdnprob(mixparams, t);
+
+s = sum(prob, 2);
+% Set any zeros to one before dividing
+s = s + (s==0);
+post = prob./(s*ones(1, mixparams.ncentres));