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<title>
Netlab Reference Manual gperr
</title>
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<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 target
vectors, and evaluates the error function <CODE>e</CODE>. 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] = gperr(net, x, t)</CODE> additionally returns the
data and hyperprior components of the error, assuming a Gaussian
prior 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)
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