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