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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/kmeans.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/kmeans.htm b/sourcecodes/bnt-master/nethelp3.3/kmeans.htm new file mode 100644 index 00000000..092e51d3 --- /dev/null +++ b/sourcecodes/bnt-master/nethelp3.3/kmeans.htm @@ -0,0 +1,89 @@ +<html> +<head> +<title> +Netlab Reference Manual kmeans +</title> +</head> +<body> +<H1> kmeans +</H1> +<h2> +Purpose +</h2> +Trains a k means cluster model. + +<p><h2> +Synopsis +</h2> +<PRE> +centres = kmeans(centres, data, options) +[centres, options] = kmeans(centres, data, options) +[centres, options, post, errlog] = kmeans(centres, data, options) +</PRE> + + +<p><h2> +Description +</h2> + +<CODE>centres = kmeans(centres, data, options)</CODE> +uses the batch K-means algorithm to set the centres of a cluster model. +The matrix <CODE>data</CODE> represents the data +which is being clustered, with each row corresponding to a vector. +The sum of squares error function is used. The point at which +a local minimum is achieved is returned as <CODE>centres</CODE>. The +error value at that point is returned in <CODE>options(8)</CODE>. + +<p><CODE>[centres, options, post, errlog] = kmeans(centres, data, options)</CODE> +also returns the cluster number (in a one-of-N encoding) for each data +point in <CODE>post</CODE> and a log of the error values after each cycle in +<CODE>errlog</CODE>. + +The optional parameters have the following interpretations. + +<p><CODE>options(1)</CODE> is set to 1 to display error values; also logs error +values in the return argument <CODE>errlog</CODE>. +If <CODE>options(1)</CODE> is set to 0, +then only warning messages are displayed. If <CODE>options(1)</CODE> is -1, +then nothing is displayed. + +<p><CODE>options(2)</CODE> is a measure of the absolute precision required for the value +of <CODE>centres</CODE> at the solution. If the absolute difference between +the values of <CODE>centres</CODE> between two successive steps is less than +<CODE>options(2)</CODE>, then this condition is satisfied. + +<p><CODE>options(3)</CODE> is a measure of the precision required of the error +function at the solution. If the absolute difference between the +error functions between two successive steps is less than +<CODE>options(3)</CODE>, then this condition is satisfied. +Both this and the previous condition must be +satisfied for termination. + +<p><CODE>options(14)</CODE> is the maximum number of iterations; default 100. + +<p><h2> +Example +</h2> +<CODE>kmeans</CODE> can be used to initialise the centres of a Gaussian +mixture model that is then trained with the EM algorithm. +<PRE> + +[priors, centres, var] = gmmunpak(p, md); +centres = kmeans(centres, data, options); +p = gmmpak(priors, centres, var); +p = gmmem(p, md, data, options); +</PRE> + + +<p><h2> +See Also +</h2> +<CODE><a href="gmminit.htm">gmminit</a></CODE>, <CODE><a href="gmmem.htm">gmmem</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 |