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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd"><!--NewPage--><HTML><HEAD><!-- Generated by javadoc (build 1.4.2_05) on Mon Mar 07 15:26:58 NZDT 2005 --><TITLE>weka.clusterers</TITLE><META NAME="keywords" CONTENT="weka.clusterers package"><LINK REL ="stylesheet" TYPE="text/css" HREF="../../stylesheet.css" TITLE="Style"><SCRIPT type="text/javascript">function windowTitle(){ parent.document.title="weka.clusterers";}</SCRIPT></HEAD><BODY BGCOLOR="white" onload="windowTitle();"><!-- ========= START OF TOP NAVBAR ======= --><A NAME="navbar_top"><!-- --></A><A HREF="#skip-navbar_top" title="Skip navigation links"></A><TABLE BORDER="0" WIDTH="100%" CELLPADDING="1" CELLSPACING="0" SUMMARY=""><TR><TD COLSPAN=3 BGCOLOR="#EEEEFF" CLASS="NavBarCell1"><A NAME="navbar_top_firstrow"><!-- --></A><TABLE BORDER="0" CELLPADDING="0" CELLSPACING="3" SUMMARY=""> <TR ALIGN="center" VALIGN="top"> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A 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SIZE="+2"><B>Interface Summary</B></FONT></TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../weka/clusterers/NumberOfClustersRequestable.html" title="interface in weka.clusterers">NumberOfClustersRequestable</A></B></TD><TD>Interface to a clusterer that can generate a requested number of clusters</TD></TR></TABLE> <P><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TD COLSPAN=2><FONT SIZE="+2"><B>Class Summary</B></FONT></TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../weka/clusterers/Clusterer.html" title="class in weka.clusterers">Clusterer</A></B></TD><TD>Abstract clusterer.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../weka/clusterers/ClusterEvaluation.html" title="class in weka.clusterers">ClusterEvaluation</A></B></TD><TD>Class for evaluating clustering models.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../weka/clusterers/Cobweb.html" title="class in weka.clusterers">Cobweb</A></B></TD><TD>Class implementing the Cobweb and Classit clustering algorithms.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../weka/clusterers/DensityBasedClusterer.html" title="class in weka.clusterers">DensityBasedClusterer</A></B></TD><TD>Abstract clustering model that produces (for each test instance) an estimate of the membership in each cluster (ie.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../weka/clusterers/EM.html" title="class in weka.clusterers">EM</A></B></TD><TD>Simple EM (expectation maximisation) class.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../weka/clusterers/FarthestFirst.html" title="class in weka.clusterers">FarthestFirst</A></B></TD><TD>Implements the "Farthest First Traversal Algorithm" by Hochbaum and Shmoys 1985: A best possible heuristic for the k-center problem, Mathematics of Operations Research, 10(2):180-184, as cited by Sanjoy Dasgupta "performance guarantees for hierarchical clustering", colt 2002, sydney works as a fast simple approximate clusterer modelled after SimpleKMeans, might be a useful initializer for it Valid options are:</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../weka/clusterers/MakeDensityBasedClusterer.html" title="class in weka.clusterers">MakeDensityBasedClusterer</A></B></TD><TD>Class for wrapping a Clusterer to make it return a distribution and density.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../weka/clusterers/SimpleKMeans.html" title="class in weka.clusterers">SimpleKMeans</A></B></TD><TD>Simple k means clustering class.</TD></TR></TABLE> <P><HR><!-- ======= START OF BOTTOM NAVBAR ====== --><A NAME="navbar_bottom"><!-- --></A><A HREF="#skip-navbar_bottom" title="Skip navigation 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