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| author | ziejd2 | 2017-09-28 15:04:40 -0500 |
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| committer | ziejd2 | 2017-09-28 15:04:40 -0500 |
| commit | 8070dc963753142bb86c4ed698d91fd623ed28e7 (patch) | |
| tree | d0f6dd8fc46a49b819aa55c1a90faa14d8448883 /sourcecodes/bnt-master/nethelp3.3/demns1.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/demns1.htm b/sourcecodes/bnt-master/nethelp3.3/demns1.htm new file mode 100644 index 00000000..9a6bcae7 --- /dev/null +++ b/sourcecodes/bnt-master/nethelp3.3/demns1.htm @@ -0,0 +1,42 @@ +<html> +<head> +<title> +Netlab Reference Manual demns1 +</title> +</head> +<body> +<H1> demns1 +</H1> +<h2> +Purpose +</h2> +Demonstrate Neuroscale for visualisation. + +<p><h2> +Synopsis +</h2> +<PRE> +demns1</PRE> + + +<p><h2> +Description +</h2> +This script demonstrates the use of the Neuroscale algorithm for +topographic projection and visualisation. A data sample is generated +from a mixture of two Gaussians in 4d space, and an RBF is trained +with the stress error function to project the data into 2d. The training +data and a test sample are both plotted in this projection. + +<p><h2> +See Also +</h2> +<CODE><a href="rbf.htm">rbf</a></CODE>, <CODE><a href="rbftrain.htm">rbftrain</a></CODE>, <CODE><a href="rbfprior.htm">rbfprior</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 |