diff toolboxes/FullBNT-1.0.7/netlab3.3/errbayes.m @ 0:e9a9cd732c1e tip

first hg version after svn

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/toolboxes/FullBNT-1.0.7/netlab3.3/errbayes.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,49 @@
+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;