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author wolffd
date Tue, 10 Feb 2015 15:05:51 +0000
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wolffd@0 1 <html>
wolffd@0 2 <head>
wolffd@0 3 <title>
wolffd@0 4 Netlab Reference Manual errbayes
wolffd@0 5 </title>
wolffd@0 6 </head>
wolffd@0 7 <body>
wolffd@0 8 <H1> errbayes
wolffd@0 9 </H1>
wolffd@0 10 <h2>
wolffd@0 11 Purpose
wolffd@0 12 </h2>
wolffd@0 13 Evaluate Bayesian error function for network.
wolffd@0 14
wolffd@0 15 <p><h2>
wolffd@0 16 Synopsis
wolffd@0 17 </h2>
wolffd@0 18 <PRE>
wolffd@0 19 e = errbayes(net, edata)
wolffd@0 20 [e, edata, eprior] = errbayes(net, edata)
wolffd@0 21 </PRE>
wolffd@0 22
wolffd@0 23
wolffd@0 24 <p><h2>
wolffd@0 25 Description
wolffd@0 26 </h2>
wolffd@0 27 <CODE>e = errbayes(net, edata)</CODE> takes a network data structure
wolffd@0 28 <CODE>net</CODE> together
wolffd@0 29 the data contribution to the error for a set of inputs and targets.
wolffd@0 30 It returns the regularised error using any zero mean Gaussian priors
wolffd@0 31 on the weights defined in
wolffd@0 32 <CODE>net</CODE>.
wolffd@0 33
wolffd@0 34 <p><CODE>[e, edata, eprior] = errbayes(net, x, t)</CODE> additionally returns the
wolffd@0 35 data and prior components of the error.
wolffd@0 36
wolffd@0 37 <p><h2>
wolffd@0 38 See Also
wolffd@0 39 </h2>
wolffd@0 40 <CODE><a href="glmerr.htm">glmerr</a></CODE>, <CODE><a href="mlperr.htm">mlperr</a></CODE>, <CODE><a href="rbferr.htm">rbferr</a></CODE><hr>
wolffd@0 41 <b>Pages:</b>
wolffd@0 42 <a href="index.htm">Index</a>
wolffd@0 43 <hr>
wolffd@0 44 <p>Copyright (c) Ian T Nabney (1996-9)
wolffd@0 45
wolffd@0 46
wolffd@0 47 </body>
wolffd@0 48 </html>