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📄 mlperr.htm

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<html><head><title>Netlab Reference Manual mlperr</title></head><body><H1> mlperr</H1><h2>Purpose</h2>Evaluate error function for 2-layer network.<p><h2>Synopsis</h2><PRE>e = mlperr(net, x, t)</PRE><p><h2>Description</h2><CODE>e = mlperr(net, x, t)</CODE> takes a network data structure <CODE>net</CODE> together with a matrix <CODE>x</CODE> of input vectors and a matrix <CODE>t</CODE> of targetvectors, and evaluates the error function <CODE>e</CODE>. The choice of errorfunction corresponds to the output unit activation function. Each rowof <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] = mlperr(net, x, t)</CODE> additionally returns thedata and prior components of the error, assuming a zero mean Gaussianprior on the weights with inverse variance parameters <CODE>alpha</CODE> and<CODE>beta</CODE> taken from the network data structure <CODE>net</CODE>.<p><h2>See Also</h2><CODE><a href="mlp.htm">mlp</a></CODE>, <CODE><a href="mlppak.htm">mlppak</a></CODE>, <CODE><a href="mlpunpak.htm">mlpunpak</a></CODE>, <CODE><a href="mlpfwd.htm">mlpfwd</a></CODE>, <CODE><a href="mlpbkp.htm">mlpbkp</a></CODE>, <CODE><a href="mlpgrad.htm">mlpgrad</a></CODE><hr><b>Pages:</b><a href="index.htm">Index</a><hr><p>Copyright (c) Ian T Nabney (1996-9)</body></html>

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