Mercurial > hg > camir-aes2014

diff toolboxes/FullBNT-1.0.7/nethelp3.3/glmevfwd.htm @ 0:e9a9cd732c1e tip
first hg version after svn
author: wolffd
date: Tue, 10 Feb 2015 15:05:51 +0000
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+<html>
+<head>
+<title>
+Netlab Reference Manual glmevfwd
+</title>
+</head>
+<body>
+<H1> glmevfwd
+</H1>
+<h2>
+Purpose
+</h2>
+Forward propagation with evidence for GLM
+
+<p><h2>
+Synopsis
+</h2>
+<PRE>
+
+[y, extra] = glmevfwd(net, x, t, x_test)
+[y, extra, invhess] = glmevfwd(net, x, t, x_test, invhess)
+</PRE>
+
+
+<p><h2>
+Description
+</h2>
+<CODE>y = glmevfwd(net, x, t, x_test)</CODE> takes a network data structure 
+<CODE>net</CODE> together with the input <CODE>x</CODE> and target <CODE>t</CODE> training data
+and input test data <CODE>x_test</CODE>.
+It returns the normal forward propagation through the network <CODE>y</CODE>
+together with a matrix <CODE>extra</CODE> which consists of error bars (variance)
+for a regression problem or moderated outputs for a classification problem.
+
+<p>The optional argument (and return value) 
+<CODE>invhess</CODE> is the inverse of the network Hessian
+computed on the training data inputs and targets.  Passing it in avoids
+recomputing it, which can be a significant saving for large training sets.
+
+<p><h2>
+See Also
+</h2>
+<CODE><a href="fevbayes.htm">fevbayes</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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