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<html><head><title>Netlab Reference Manual gperr</title></head><body><H1> gperr</H1><h2>Purpose</h2>Evaluate error function for Gaussian Process.<p><h2>Synopsis</h2><PRE>edata = gperr(net, x, t)[e, edata, eprior] = gperr(net, x, t)</PRE><p><h2>Description</h2><CODE>e = gperr(net, x, t)</CODE> takes a Gaussian Process 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>. 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] = gperr(net, x, t)</CODE> additionally returns thedata and hyperprior components of the error, assuming a Gaussianprior on the weights with mean and variance parameters <CODE>prmean</CODE> and<CODE>prvariance</CODE> taken from the network data structure <CODE>net</CODE>.<p><h2>See Also</h2><CODE><a href="gp.htm">gp</a></CODE>, <CODE><a href="gpcovar.htm">gpcovar</a></CODE>, <CODE><a href="gpfwd.htm">gpfwd</a></CODE>, <CODE><a href="gpgrad.htm">gpgrad</a></CODE><hr><b>Pages:</b><a href="index.htm">Index</a><hr><p>Copyright (c) Ian T Nabney (1996-9)</body></html>⌨️ 快捷键说明
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