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| author | ziejd2 | 2017-09-28 15:04:40 -0500 |
|---|---|---|
| committer | ziejd2 | 2017-09-28 15:04:40 -0500 |
| commit | 8070dc963753142bb86c4ed698d91fd623ed28e7 (patch) | |
| tree | d0f6dd8fc46a49b819aa55c1a90faa14d8448883 /sourcecodes/bnt-master/nethelp3.3/mlphdotv.htm | |
| parent | 7cc31810d53176e805532b2789955f4eedbce6bb (diff) | |
| download | BNW-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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diff --git a/sourcecodes/bnt-master/nethelp3.3/mlphdotv.htm b/sourcecodes/bnt-master/nethelp3.3/mlphdotv.htm new file mode 100644 index 00000000..7ecf2765 --- /dev/null +++ b/sourcecodes/bnt-master/nethelp3.3/mlphdotv.htm @@ -0,0 +1,45 @@ +<html> +<head> +<title> +Netlab Reference Manual mlphdotv +</title> +</head> +<body> +<H1> mlphdotv +</H1> +<h2> +Purpose +</h2> +Evaluate the product of the data Hessian with a vector. + +<p><h2> +Synopsis +</h2> +<PRE> +hdv = mlphdotv(net, x, t, v)</PRE> + + +<p><h2> +Description +</h2> + +<p><CODE>hdv = mlphdotv(net, x, t, v)</CODE> takes an MLP network data structure +<CODE>net</CODE>, together with the matrix <CODE>x</CODE> of input vectors, the +matrix <CODE>t</CODE> of target vectors and an arbitrary row vector <CODE>v</CODE> +whose length equals the number of parameters in the network, and +returns the product of the data-dependent contribution to the Hessian +matrix with <CODE>v</CODE>. The implementation is based on the R-propagation +algorithm of Pearlmutter. + +<p><h2> +See Also +</h2> +<CODE><a href="mlp.htm">mlp</a></CODE>, <CODE><a href="mlphess.htm">mlphess</a></CODE>, <CODE><a href="hesschek.htm">hesschek</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 |