view toolboxes/FullBNT-1.0.7/netlab3.3/mlpevfwd.m @ 0:e9a9cd732c1e tip

first hg version after svn

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