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<html> <head> <title> Netlab Reference Manual glmerr </title> </head> <body> <H1> glmerr </H1> <h2> Purpose </h2> Evaluate error function for generalized linear model. <p><h2> Synopsis </h2> <PRE> e = glmerr(net, x, t) [e, edata, eprior] = glmerr(net, x, t) [e, edata, eprior, y, a] = glmerr(net, x, t) </PRE> <p><h2> Description </h2> <CODE>e = glmerr(net, x, t)</CODE> takes a generalized linear model data structure <CODE>net</CODE> together with a matrix <CODE>x</CODE> of input vectors and a matrix <CODE>t</CODE> of target vectors, and evaluates the error function <CODE>e</CODE>. The choice of error function corresponds to the output unit activation function. Each row of <CODE>x</CODE> corresponds to one input vector and each row of <CODE>t</CODE> corresponds to one target vector. <p><CODE>[e, edata, eprior, y, a] = glmerr(net, x, t)</CODE> also returns the data and prior components of the total error. <p><CODE>[e, edata, eprior, y, a] = glmerr(net, x)</CODE> also returns a matrix <CODE>y</CODE> giving the outputs of the models and a matrix <CODE>a</CODE> giving the summed inputs to each output unit, where each row corresponds to one pattern. <p><h2> See Also </h2> <CODE><a href="glm.htm">glm</a></CODE>, <CODE><a href="glmpak.htm">glmpak</a></CODE>, <CODE><a href="glmunpak.htm">glmunpak</a></CODE>, <CODE><a href="glmfwd.htm">glmfwd</a></CODE>, <CODE><a href="glmgrad.htm">glmgrad</a></CODE>, <CODE><a href="glmtrain.htm">glmtrain</a></CODE><hr> <b>Pages:</b> <a href="index.htm">Index</a> <hr> <p>Copyright (c) Ian T Nabney (1996-9) </body> </html>