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Diffstat (limited to 'sourcecodes/bnt-master/netlab3.3/errbayes.m')
| -rw-r--r-- | sourcecodes/bnt-master/netlab3.3/errbayes.m | 49 |
1 files changed, 49 insertions, 0 deletions
diff --git a/sourcecodes/bnt-master/netlab3.3/errbayes.m b/sourcecodes/bnt-master/netlab3.3/errbayes.m new file mode 100644 index 00000000..7c2a330b --- /dev/null +++ b/sourcecodes/bnt-master/netlab3.3/errbayes.m @@ -0,0 +1,49 @@ +function [e, edata, eprior] = errbayes(net, edata) +%ERRBAYES Evaluate Bayesian error function for network. +% +% Description +% E = ERRBAYES(NET, EDATA) takes a network data structure NET together +% the data contribution to the error for a set of inputs and targets. +% It returns the regularised error using any zero mean Gaussian priors +% on the weights defined in NET. +% +% [E, EDATA, EPRIOR] = ERRBAYES(NET, X, T) additionally returns the +% data and prior components of the error. +% +% See also +% GLMERR, MLPERR, RBFERR +% + +% Copyright (c) Ian T Nabney (1996-2001) + +% Evaluate the data contribution to the error. +if isfield(net, 'beta') + e1 = net.beta*edata; +else + e1 = edata; +end + +% Evaluate the prior contribution to the error. +if isfield(net, 'alpha') + w = netpak(net); + if size(net.alpha) == [1 1] + eprior = 0.5*(w*w'); + e2 = eprior*net.alpha; + else + if (isfield(net, 'mask')) + nindx_cols = size(net.index, 2); + nmask_rows = size(find(net.mask), 1); + index = reshape(net.index(logical(repmat(net.mask, ... + 1, nindx_cols))), nmask_rows, nindx_cols); + else + index = net.index; + end + eprior = 0.5*(w.^2)*index; + e2 = eprior*net.alpha; + end +else + eprior = 0; + e2 = 0; +end + +e = e1 + e2; |
