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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/glmderiv.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/glmderiv.htm b/sourcecodes/bnt-master/nethelp3.3/glmderiv.htm new file mode 100644 index 00000000..56887889 --- /dev/null +++ b/sourcecodes/bnt-master/nethelp3.3/glmderiv.htm @@ -0,0 +1,49 @@ +<html> +<head> +<title> +Netlab Reference Manual glmderiv +</title> +</head> +<body> +<H1> glmderiv +</H1> +<h2> +Purpose +</h2> +Evaluate derivatives of GLM outputs with respect to weights. + +<p><h2> +Synopsis +</h2> +<PRE> + +g = glmderiv(net, x) +</PRE> + + +<p><h2> +Description +</h2> +<CODE>g = glmderiv(net, x)</CODE> takes a network data structure <CODE>net</CODE> and a matrix +of input vectors <CODE>x</CODE> and returns a three-index matrix mat{g} whose +<CODE>i</CODE>, <CODE>j</CODE>, <CODE>k</CODE> +element contains the derivative of network output <CODE>k</CODE> with respect to +weight or bias parameter <CODE>j</CODE> for input pattern <CODE>i</CODE>. The ordering of the +weight and bias parameters is defined by <CODE>glmunpak</CODE>. + +<p><h2> +See also +</h2> +<PRE> +glm, glmunpak, glmgrad</PRE> + + +<p><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 |