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authorziejd22017-09-28 15:04:40 -0500
committerziejd22017-09-28 15:04:40 -0500
commit8070dc963753142bb86c4ed698d91fd623ed28e7 (patch)
treed0f6dd8fc46a49b819aa55c1a90faa14d8448883 /sourcecodes/bnt-master/nethelp3.3/gbayes.htm
parent7cc31810d53176e805532b2789955f4eedbce6bb (diff)
downloadBNW-8070dc963753142bb86c4ed698d91fd623ed28e7.tar.gz
BNW using Octave instead of Matlab.
This version of BNW should perform the same as the original version. The only difference is that it uses Octave instead of Matlab when running BayesNet Toolbox during parameter learning.

I am calling this BNW_1.02. It can be accessed at:
compbio.uthsc.edu/BNW_1.02
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+<html>
+<head>
+<title>
+Netlab Reference Manual gbayes
+</title>
+</head>
+<body>
+<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)
+
+
+</body>
+</html>
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