Mercurial > hg > camir-aes2014
view toolboxes/FullBNT-1.0.7/netlab3.3/errbayes.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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function [e, edata, eprior] = errbayes(net, edata) %ERRBAYES Evaluate Bayesian error function for network. % % Description % E = ERRBAYES(NET, EDATA) takes a network data structure NET together % the data contribution to the error for a set of inputs and targets. % It returns the regularised error using any zero mean Gaussian priors % on the weights defined in NET. % % [E, EDATA, EPRIOR] = ERRBAYES(NET, X, T) additionally returns the % data and prior components of the error. % % See also % GLMERR, MLPERR, RBFERR % % Copyright (c) Ian T Nabney (1996-2001) % Evaluate the data contribution to the error. if isfield(net, 'beta') e1 = net.beta*edata; else e1 = edata; end % Evaluate the prior contribution to the error. if isfield(net, 'alpha') w = netpak(net); if size(net.alpha) == [1 1] eprior = 0.5*(w*w'); e2 = eprior*net.alpha; else if (isfield(net, 'mask')) nindx_cols = size(net.index, 2); nmask_rows = size(find(net.mask), 1); index = reshape(net.index(logical(repmat(net.mask, ... 1, nindx_cols))), nmask_rows, nindx_cols); else index = net.index; end eprior = 0.5*(w.^2)*index; e2 = eprior*net.alpha; end else eprior = 0; e2 = 0; end e = e1 + e2;