diff toolboxes/FullBNT-1.0.7/netlab3.3/mlpevfwd.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/mlpevfwd.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,26 @@
+function [y, extra, invhess] = mlpevfwd(net, x, t, x_test, invhess)
+%MLPEVFWD Forward propagation with evidence for MLP
+%
+%	Description
+%	Y = MLPEVFWD(NET, X, T, X_TEST) takes a network data structure  NET
+%	together with the input X and target T training data and input test
+%	data X_TEST. It returns the normal forward propagation through the
+%	network Y together with a matrix EXTRA which consists of error bars
+%	(variance) for a regression problem or moderated outputs for a
+%	classification problem. The optional argument (and return value)
+%	INVHESS is the inverse of the network Hessian computed on the
+%	training data inputs and targets.  Passing it in avoids recomputing
+%	it, which can be a significant saving for large training sets.
+%
+%	See also
+%	FEVBAYES
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+[y, z, a] = mlpfwd(net, x_test);
+if nargin == 4
+  [extra, invhess] = fevbayes(net, y, a, x, t, x_test);
+else
+  [extra, invhess] = fevbayes(net, y, a, x, t, x_test, invhess);
+end
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