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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/netderiv.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/netderiv.htm b/sourcecodes/bnt-master/nethelp3.3/netderiv.htm new file mode 100644 index 00000000..3275eced --- /dev/null +++ b/sourcecodes/bnt-master/nethelp3.3/netderiv.htm @@ -0,0 +1,42 @@ +<html> +<head> +<title> +Netlab Reference Manual netderiv +</title> +</head> +<body> +<H1> netderiv +</H1> +<h2> +Purpose +</h2> +Evaluate derivatives of network outputs by weights generically. + +<p><h2> +Synopsis +</h2> +<PRE> +g = netderiv(w, net, x)</PRE> + + +<p><h2> +Description +</h2> + +<p><CODE>g = netderiv(w, net, x)</CODE> takes a weight vector <CODE>w</CODE> and a network +data structure <CODE>net</CODE>, together with the matrix <CODE>x</CODE> of input +vectors, and returns the +gradient of the outputs with respect to the weights evaluated at <CODE>w</CODE>. + +<p><h2> +See Also +</h2> +<CODE><a href="netevfwd.htm">netevfwd</a></CODE>, <CODE><a href="netopt.htm">netopt</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 |