wolffd@0: wolffd@0: wolffd@0: wolffd@0: Netlab Reference Manual glmerr wolffd@0: wolffd@0: wolffd@0: wolffd@0:

glmerr wolffd@0:

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wolffd@0: Purpose wolffd@0:

wolffd@0: Evaluate error function for generalized linear model. wolffd@0: wolffd@0:

wolffd@0: Synopsis wolffd@0:

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wolffd@0: e = glmerr(net, x, t)
wolffd@0: [e, edata, eprior] = glmerr(net, x, t)
wolffd@0: [e, edata, eprior, y, a] = glmerr(net, x, t)
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wolffd@0: Description wolffd@0:

wolffd@0: wolffd@0: e = glmerr(net, x, t) takes a generalized wolffd@0: linear model data structure net together with a matrix x wolffd@0: of input vectors and a matrix t of target vectors, and evaluates wolffd@0: the error function e. The choice of error function corresponds wolffd@0: to the output unit activation function. Each row of x wolffd@0: corresponds to one input vector and each row of t corresponds to wolffd@0: one target vector. wolffd@0: wolffd@0:

[e, edata, eprior, y, a] = glmerr(net, x, t) also returns wolffd@0: the data and prior components of the total error. wolffd@0: wolffd@0:

[e, edata, eprior, y, a] = glmerr(net, x) also returns a matrix y wolffd@0: giving the outputs of the models and a matrix a wolffd@0: giving the summed inputs to each output unit, where each row wolffd@0: corresponds to one pattern. wolffd@0: wolffd@0:

wolffd@0: See Also wolffd@0:

wolffd@0: glm, glmpak, glmunpak, glmfwd, glmgrad, glmtrain

wolffd@0: Pages: wolffd@0: Index wolffd@0:

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