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author wolffd
date Tue, 10 Feb 2015 15:05:51 +0000
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+<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>
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