g = gbayes(net, gdata) [g, gdata, gprior] = gbayes(net, gdata)
g = gbayes(net, gdata) takes a network data structure net together
the data contribution to the error gradient
for a set of inputs and targets.
It returns the regularised error gradient using any zero mean Gaussian priors
on the weights defined in
net. In addition, if a mask is defined in net, then
the entries in g that correspond to weights with a 0 in the
mask are removed.
[g, gdata, gprior] = gbayes(net, gdata) additionally returns the
data and prior components of the error.
errbayes, glmgrad, mlpgrad, rbfgradCopyright (c) Ian T Nabney (1996-9)