06 Nov 2002
02 Dec 2002)
Pattern analysis toolbox.
|glmevfwd(net, x, t, x_test, invhess)
function [y, extra, invhess] = glmevfwd(net, x, t, x_test, invhess)
%GLMEVFWD Forward propagation with evidence for GLM
% Y = GLMEVFWD(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
% Copyright (c) Ian T Nabney (1996-2001)
[y, a] = glmfwd(net, x_test);
if nargin == 4
[extra, invhess] = fevbayes(net, y, a, x, t, x_test);
[extra, invhess] = fevbayes(net, y, a, x, t, x_test, invhess);