[y, extra] = netevfwd(w, net, x, t, x_test) [y, extra, invhess] = netevfwd(w, net, x, t, x_test, invhess)
[y, extra] = netevfwd(w, net, x, t, x_test)takes a network data structure
nettogether with the input
ttraining data and input test data
x_test. It returns the normal forward propagation through the network
ytogether with a matrix
extrawhich 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.
Copyright (c) Ian T Nabney (1996-9)