📄 mlpevfwd.m
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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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