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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/demknn1.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/demknn1.htm b/sourcecodes/bnt-master/nethelp3.3/demknn1.htm new file mode 100644 index 00000000..6c0d4031 --- /dev/null +++ b/sourcecodes/bnt-master/nethelp3.3/demknn1.htm @@ -0,0 +1,47 @@ +<html> +<head> +<title> +Netlab Reference Manual demknn1 +</title> +</head> +<body> +<H1> demknn1 +</H1> +<h2> +Purpose +</h2> +Demonstrate nearest neighbour classifier. + +<p><h2> +Synopsis +</h2> +<PRE> +demknn1</PRE> + + +<p><h2> +Description +</h2> +The problem consists of data in a two-dimensional space. +The data is +drawn from three spherical Gaussian distributions with priors 0.3, +0.5 and 0.2; centres (2, 3.5), (0, 0) and (0,2); and standard deviations +0.2, 0.5 and 1.0. The first figure contains a +scatter plot of the data. The data is the same as in <CODE>demgmm1</CODE>. + +<p>The second +figure shows the data labelled with the corresponding class given +by the classifier. + +<p><h2> +See Also +</h2> +<CODE><a href="dem2ddat.htm">dem2ddat</a></CODE>, <CODE><a href="demgmm1.htm">demgmm1</a></CODE>, <CODE><a href="knn.htm">knn</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 |