wolffd@0: wolffd@0:
wolffd@0:wolffd@0: e = errbayes(net, edata) wolffd@0: [e, edata, eprior] = errbayes(net, edata) wolffd@0:wolffd@0: wolffd@0: wolffd@0:
e = errbayes(net, edata) takes a network data structure
wolffd@0: net together
wolffd@0: the data contribution to the error for a set of inputs and targets.
wolffd@0: It returns the regularised error using any zero mean Gaussian priors
wolffd@0: on the weights defined in
wolffd@0: net.
wolffd@0:
wolffd@0: [e, edata, eprior] = errbayes(net, x, t) additionally returns the
wolffd@0: data and prior components of the error.
wolffd@0:
wolffd@0:
glmerr, mlperr, rbferrCopyright (c) Ian T Nabney (1996-9) wolffd@0: wolffd@0: wolffd@0: wolffd@0: