Mercurial > hg > camir-aes2014
diff toolboxes/FullBNT-1.0.7/nethelp3.3/glmhess.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/glmhess.htm Tue Feb 10 15:05:51 2015 +0000 @@ -0,0 +1,74 @@ +<html> +<head> +<title> +Netlab Reference Manual glmhess +</title> +</head> +<body> +<H1> glmhess +</H1> +<h2> +Purpose +</h2> +Evaluate the Hessian matrix for a generalised linear model. + +<p><h2> +Synopsis +</h2> +<PRE> +h = glmhess(net, x, t) +[h, hdata] = glmhess(net, x, t) +h = glmhess(net, x, t, hdata) +</PRE> + + +<p><h2> +Description +</h2> +<CODE>h = glmhess(net, x, t)</CODE> takes a GLM network data structure <CODE>net</CODE>, +a matrix <CODE>x</CODE> of input values, and a matrix <CODE>t</CODE> of target +values and returns the full Hessian matrix <CODE>h</CODE> corresponding to +the second derivatives of the negative log posterior distribution, +evaluated for the current weight and bias values as defined by +<CODE>net</CODE>. Note that the target data is not required in the calculation, +but is included to make the interface uniform with <CODE>nethess</CODE>. For +linear and logistic outputs, the computation is very simple and is +done (in effect) in one line in <CODE>glmtrain</CODE>. + +<p><CODE>[h, hdata] = glmhess(net, x, t)</CODE> returns both the Hessian matrix +<CODE>h</CODE> and the contribution <CODE>hdata</CODE> arising from the data dependent +term in the Hessian. + +<p><CODE>h = glmhess(net, x, t, hdata)</CODE> takes a network data structure +<CODE>net</CODE>, a matrix <CODE>x</CODE> of input values, and a matrix <CODE>t</CODE> of +target values, together with the contribution <CODE>hdata</CODE> arising from +the data dependent term in the Hessian, and returns the full Hessian +matrix <CODE>h</CODE> corresponding to the second derivatives of the negative +log posterior distribution. This version saves computation time if +<CODE>hdata</CODE> has already been evaluated for the current weight and bias +values. + +<p><h2> +Example +</h2> +The Hessian matrix is used by <CODE>glmtrain</CODE> to take a Newton step for +softmax outputs. +<PRE> + +Hessian = glmhess(net, x, t); +deltaw = -gradient*pinv(Hessian); +</PRE> + + +<p><h2> +See Also +</h2> +<CODE><a href="glm.htm">glm</a></CODE>, <CODE><a href="glmtrain.htm">glmtrain</a></CODE>, <CODE><a href="hesschek.htm">hesschek</a></CODE>, <CODE><a href="nethess.htm">nethess</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