extra = fevbayes(net, y, a, x, t, x_test) [extra, invhess] = fevbayes(net, y, a, x, t, x_test, invhess)
extra = fevbayes(net, y, a, x, t, x_test) takes a network data structure
net together with a set of hidden unit activations a from
test inputs x_test, training data inputs x and t and
outputs a matrix of extra information extra that 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.
This is called by network-specific functions such as mlpevfwd which
are needed since the return values (predictions and hidden unit activations)
for different network types are in different orders (for good reasons).
mlpevfwd, rbfevfwd, glmevfwdCopyright (c) Ian T Nabney (1996-9)