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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/demgtm1.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/demgtm1.htm b/sourcecodes/bnt-master/nethelp3.3/demgtm1.htm new file mode 100644 index 00000000..1422c764 --- /dev/null +++ b/sourcecodes/bnt-master/nethelp3.3/demgtm1.htm @@ -0,0 +1,42 @@ +<html> +<head> +<title> +Netlab Reference Manual demgtm1 +</title> +</head> +<body> +<H1> demgtm1 +</H1> +<h2> +Purpose +</h2> +Demonstrate EM for GTM. + +<p><h2> +Synopsis +</h2> +<PRE> +demgtm1</PRE> + + +<p><h2> +Description +</h2> + +This script demonstrates the use of the EM +algorithm to fit a one-dimensional GTM to a two-dimensional set of data +using maximum likelihood. The location and spread of the Gaussian kernels +in the data space is shown during training. + +<p><h2> +See Also +</h2> +<CODE><a href="demgtm2.htm">demgtm2</a></CODE>, <CODE><a href="gtm.htm">gtm</a></CODE>, <CODE><a href="gtmem.htm">gtmem</a></CODE>, <CODE><a href="gtmpost.htm">gtmpost</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 |