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authorziejd22018-03-14 23:23:33 -0500
committerGitHub2018-03-14 23:23:33 -0500
commit1ff6baa44e22b91eefb48aea6f3befa078c0489b (patch)
treee0fd79d2e32fd2aedda2eadaed0f19af3514c520 /sourcecodes/bnt-master/netlab3.3/mdnerr.m
parent6882395afdadf4e982b25b5215071a0932730950 (diff)
parentc80226899f5cdd9f11c163817d59445213f5bef0 (diff)
downloadBNW-1ff6baa44e22b91eefb48aea6f3befa078c0489b.tar.gz
Merge pull request #1 from ziejd2/octave_php_separate
Octave php separate
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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))));
+