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<title>
Netlab Reference Manual gbayes
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<H1> gbayes
</H1>
<h2>
Purpose
</h2>
Evaluate gradient of Bayesian error function for network.
<p><h2>
Synopsis
</h2>
<PRE>
g = gbayes(net, gdata)
[g, gdata, gprior] = gbayes(net, gdata)
</PRE>
<p><h2>
Description
</h2>
<CODE>g = gbayes(net, gdata)</CODE> takes a network data structure <CODE>net</CODE> together
the data contribution to the error gradient
for a set of inputs and targets.
It returns the regularised error gradient using any zero mean Gaussian priors
on the weights defined in
<CODE>net</CODE>. In addition, if a <CODE>mask</CODE> is defined in <CODE>net</CODE>, then
the entries in <CODE>g</CODE> that correspond to weights with a 0 in the
mask are removed.
<p><CODE>[g, gdata, gprior] = gbayes(net, gdata)</CODE> additionally returns the
data and prior components of the error.
<p><h2>
See Also
</h2>
<CODE><a href="errbayes.htm">errbayes</a></CODE>, <CODE><a href="glmgrad.htm">glmgrad</a></CODE>, <CODE><a href="mlpgrad.htm">mlpgrad</a></CODE>, <CODE><a href="rbfgrad.htm">rbfgrad</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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