Mercurial > hg > camir-aes2014
diff toolboxes/FullBNT-1.0.7/nethelp3.3/netevfwd.htm @ 0:e9a9cd732c1e tip
first hg version after svn
| author | wolffd |
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| date | Tue, 10 Feb 2015 15:05:51 +0000 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/toolboxes/FullBNT-1.0.7/nethelp3.3/netevfwd.htm Tue Feb 10 15:05:51 2015 +0000 @@ -0,0 +1,52 @@ +<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> \ No newline at end of file