www.gusucode.com > Rebel工具包 > matlab代做 修改 程序Rebel工具包/16316248ReBEL-0.2.7/ReBEL-0.2.7/netlab/glmerr.m
function [e, edata, eprior, y, a, mse] = glmerr(net, x, t) %GLMERR Evaluate error function for generalized linear model. % % Description % E = GLMERR(NET, X, T) takes a generalized linear model data % structure NET together with a matrix X of input vectors and a matrix % T of target vectors, and evaluates the error function E. The choice % of error function corresponds to the output unit activation function. % Each row of X corresponds to one input vector and each row of T % corresponds to one target vector. % % [E, EDATA, EPRIOR, Y, A] = GLMERR(NET, X, T) also returns the data % and prior components of the total error. % % [E, EDATA, EPRIOR, Y, A] = GLMERR(NET, X) also returns a matrix Y % giving the outputs of the models and a matrix A giving the summed % inputs to each output unit, where each row corresponds to one % pattern. % % See also % GLM, GLMPAK, GLMUNPAK, GLMFWD, GLMGRAD, GLMTRAIN % % Copyright (c) Ian T Nabney (1996-2001) % Check arguments for consistency errstring = consist(net, 'glm', x, t); if ~isempty(errstring); error(errstring); end [y, a] = glmfwd(net, x); switch net.outfn case 'linear' % Linear outputs edata = 0.5*sum(sum((y - t).^2)); case 'logistic' % Logistic outputs edata = - sum(sum(t.*log(y) + (1 - t).*log(1 - y))); case 'softmax' % Softmax outputs edata = - sum(sum(t.*log(y))); otherwise error(['Unknown activation function ', net.outfn]); end mse = (2*edata) / size(t,1); [e, edata, eprior] = errbayes(net, edata);