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, 33 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/netlab3.3/mdnerr.m b/sourcecodes/bnt-master/netlab3.3/mdnerr.m
new file mode 100644
index 00000000..a0b686e0
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+++ b/sourcecodes/bnt-master/netlab3.3/mdnerr.m
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+function e = mdnerr(net, x, t)
+%MDNERR	Evaluate error function for Mixture Density Network.
+%
+%	Description
+%	 E = MDNERR(NET, X, T) takes a mixture density network data structure
+%	NET, a matrix X of input vectors and a matrix T of target vectors,
+%	and evaluates the error function E. The error function is the
+%	negative log likelihood of the target data under the conditional
+%	density given by the mixture model parameterised by the MLP.  Each
+%	row of X corresponds to one input vector and each row of T
+%	corresponds to one target vector.
+%
+%	See also
+%	MDN, MDNFWD, MDNGRAD
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+%	David J Evans (1998)
+
+% Check arguments for consistency
+errstring = consist(net, 'mdn', x, t);
+if ~isempty(errstring)
+  error(errstring);
+end
+
+% Get the output mixture models
+mixparams = mdnfwd(net, x);
+
+% Compute the probabilities of mixtures
+probs     = mdnprob(mixparams, t);
+% Compute the error
+e       = sum( -log(max(eps, sum(probs, 2))));
+