Mercurial > hg > camir-aes2014

<html>
<head>
<title>
Netlab Reference Manual netevfwd
</title>
</head>
<body>
<H1> netevfwd
</H1>
<h2>
Purpose
</h2>
Generic forward propagation with evidence for network

<p><h2>
Synopsis
</h2>
<PRE>

[y, extra] = netevfwd(w, net, x, t, x_test)
[y, extra, invhess] = netevfwd(w, net, x, t, x_test, invhess)
</PRE>


<p><h2>
Description
</h2>
<CODE>[y, extra] = netevfwd(w, 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="mlpevfwd.htm">mlpevfwd</a></CODE>, <CODE><a href="rbfevfwd.htm">rbfevfwd</a></CODE>, <CODE><a href="glmevfwd.htm">glmevfwd</a></CODE>, <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>
author	wolffd
date	Tue, 10 Feb 2015 15:05:51 +0000
parents
children