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| author | ziejd2 | 2018-03-14 23:23:33 -0500 |
|---|---|---|
| committer | GitHub | 2018-03-14 23:23:33 -0500 |
| commit | 1ff6baa44e22b91eefb48aea6f3befa078c0489b (patch) | |
| tree | e0fd79d2e32fd2aedda2eadaed0f19af3514c520 /sourcecodes/bnt-master/nethelp3.3/knn.htm | |
| parent | 6882395afdadf4e982b25b5215071a0932730950 (diff) | |
| parent | c80226899f5cdd9f11c163817d59445213f5bef0 (diff) | |
| download | BNW-1ff6baa44e22b91eefb48aea6f3befa078c0489b.tar.gz | |
Merge pull request #1 from ziejd2/octave_php_separate
Octave php separate
Diffstat (limited to 'sourcecodes/bnt-master/nethelp3.3/knn.htm')
| -rw-r--r-- | sourcecodes/bnt-master/nethelp3.3/knn.htm | 54 |
1 files changed, 54 insertions, 0 deletions
diff --git a/sourcecodes/bnt-master/nethelp3.3/knn.htm b/sourcecodes/bnt-master/nethelp3.3/knn.htm new file mode 100644 index 00000000..31f032bc --- /dev/null +++ b/sourcecodes/bnt-master/nethelp3.3/knn.htm @@ -0,0 +1,54 @@ +<html> +<head> +<title> +Netlab Reference Manual knn +</title> +</head> +<body> +<H1> knn +</H1> +<h2> +Purpose +</h2> +Creates a K-nearest-neighbour classifier. + +<p><h2> +Synopsis +</h2> +<PRE> + +net = knn(nin, nout, k, tr_in, tr_targets) +</PRE> + + +<p><h2> +Description +</h2> +<CODE>net = knn(nin, nout, k, tr_in, tr_targets)</CODE> creates a KNN model <CODE>net</CODE> +with input dimension <CODE>nin</CODE>, output dimension <CODE>nout</CODE> and <CODE>k</CODE> +neighbours. The training data is also stored in the data structure and the +targets are assumed to be using a 1-of-N coding. + +<p>The fields in <CODE>net</CODE> are +<PRE> + + type = 'knn' + nin = number of inputs + nout = number of outputs + tr_in = training input data + tr_targets = training target data +</PRE> + + +<p><h2> +See Also +</h2> +<CODE><a href="kmeans.htm">kmeans</a></CODE>, <CODE><a href="knnfwd.htm">knnfwd</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 |