📄 errbayes.m
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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; endelse eprior = 0; e2 = 0;ende = e1 + e2;
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