annotate toolboxes/FullBNT-1.0.7/netlab3.3/mdnerr.m @ 0:cc4b1211e677 tip

initial commit to HG from Changeset: 646 (e263d8a21543) added further path and more save "camirversion.m"
author Daniel Wolff
date Fri, 19 Aug 2016 13:07:06 +0200
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Daniel@0 1 function e = mdnerr(net, x, t)
Daniel@0 2 %MDNERR Evaluate error function for Mixture Density Network.
Daniel@0 3 %
Daniel@0 4 % Description
Daniel@0 5 % E = MDNERR(NET, X, T) takes a mixture density network data structure
Daniel@0 6 % NET, a matrix X of input vectors and a matrix T of target vectors,
Daniel@0 7 % and evaluates the error function E. The error function is the
Daniel@0 8 % negative log likelihood of the target data under the conditional
Daniel@0 9 % density given by the mixture model parameterised by the MLP. Each
Daniel@0 10 % row of X corresponds to one input vector and each row of T
Daniel@0 11 % corresponds to one target vector.
Daniel@0 12 %
Daniel@0 13 % See also
Daniel@0 14 % MDN, MDNFWD, MDNGRAD
Daniel@0 15 %
Daniel@0 16
Daniel@0 17 % Copyright (c) Ian T Nabney (1996-2001)
Daniel@0 18 % David J Evans (1998)
Daniel@0 19
Daniel@0 20 % Check arguments for consistency
Daniel@0 21 errstring = consist(net, 'mdn', x, t);
Daniel@0 22 if ~isempty(errstring)
Daniel@0 23 error(errstring);
Daniel@0 24 end
Daniel@0 25
Daniel@0 26 % Get the output mixture models
Daniel@0 27 mixparams = mdnfwd(net, x);
Daniel@0 28
Daniel@0 29 % Compute the probabilities of mixtures
Daniel@0 30 probs = mdnprob(mixparams, t);
Daniel@0 31 % Compute the error
Daniel@0 32 e = sum( -log(max(eps, sum(probs, 2))));
Daniel@0 33