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📄 algorithmkmeans.html,v

📁 包含了模式识别中常用的一些分类器设计算法
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<TH ALIGN="left" COLSPAN="1"><FONT SIZE="+2"><B>Field Detail</B></FONT></TH></TR></TABLE><A NAME="RAND_SEED"><!-- --></A><H3>RAND_SEED</H3><PRE>public static final long <B>RAND_SEED</B></PRE><DL><DD>The random number generator<P><DL><DT><B>See Also:</B><DD><A HREF="constant-values.html#AlgorithmKMeans.RAND_SEED">Constant Field Values</A></DL></DL><!-- ========= CONSTRUCTOR DETAIL ======== --><A NAME="constructor_detail"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="1"><FONT SIZE="+2"><B>Constructor Detail</B></FONT></TH></TR></TABLE><A NAME="AlgorithmKMeans()"><!-- --></A><H3>AlgorithmKMeans</H3><PRE>public <B>AlgorithmKMeans</B>()</PRE><DL></DL><!-- ============ METHOD DETAIL ========== --><A NAME="method_detail"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="1"><FONT SIZE="+2"><B>Method Detail</B></FONT></TH></TR></TABLE><A NAME="initialize()"><!-- --></A><H3>initialize</H3><PRE>public boolean <B>initialize</B>()</PRE><DL><DD>Overrides the initialize() method in the base class.  Initializes member data and prepares for execution of first step.  This method "resets" the algorithm.<P><DD><DL><DT><B>Specified by:</B><DD><CODE><A HREF="Algorithm.html#initialize()">initialize</A></CODE> in class <CODE><A HREF="Algorithm.html" title="class in &lt;Unnamed&gt;">Algorithm</A></CODE></DL></DD><DD><DL><DT><B>Returns:</B><DD>Returns false</DL></DD></DL><HR><A NAME="run()"><!-- --></A><H3>run</H3><PRE>public void <B>run</B>()</PRE><DL><DD>Implementation of the run function from the Runnable interface. Determines what the current step is and calls the appropriate method.<P><DD><DL><DT><B>Specified by:</B><DD><CODE>run</CODE> in interface <CODE>java.lang.Runnable</CODE><DT><B>Specified by:</B><DD><CODE><A HREF="Algorithm.html#run()">run</A></CODE> in class <CODE><A HREF="Algorithm.html" title="class in &lt;Unnamed&gt;">Algorithm</A></CODE></DL></DD><DD><DL></DL></DD></DL><HR><A NAME="generatePool()"><!-- --></A><H3>generatePool</H3><PRE>public void <B>generatePool</B>()</PRE><DL><DD>Collects all the data points of all the data sets<P><DD><DL></DL></DD></DL><HR><A NAME="generateMeans(int)"><!-- --></A><H3>generateMeans</H3><PRE>public void <B>generateMeans</B>(int&nbsp;numMeans)</PRE><DL><DD>Generates random initial guesses (means) for the data set<P><DD><DL><DT><B>Parameters:</B><DD><CODE>numMeans</CODE> - number of mean points</DL></DD></DL><HR><A NAME="initializeKmeans()"><!-- --></A><H3>initializeKmeans</H3><PRE>public void <B>initializeKmeans</B>()</PRE><DL><DD>Initializes the kmean array with the original data sets<P><DD><DL></DL></DD></DL><HR><A NAME="classify(DecisionRegion)"><!-- --></A><H3>classify</H3><PRE>public void <B>classify</B>(<A HREF="DecisionRegion.html" title="class in &lt;Unnamed&gt;">DecisionRegion</A>&nbsp;region)</PRE><DL><DD>Classifies the data sets based on the k-means iterative algorithm<P><DD><DL><DT><B>Parameters:</B><DD><CODE>region</CODE> - - stored data sets from the classification<DT><B>See Also:</B><DD><A HREF="DecisionRegion.html" title="class in &lt;Unnamed&gt;"><CODE>DecisionRegion</CODE></A></DL></DD></DL><HR><A NAME="computeMeans(DecisionRegion)"><!-- --></A><H3>computeMeans</H3><PRE>public void <B>computeMeans</B>(<A HREF="DecisionRegion.html" title="class in &lt;Unnamed&gt;">DecisionRegion</A>&nbsp;region)</PRE><DL><DD>Computes the means of the data sets after each iteraion<P><DD><DL><DT><B>Parameters:</B><DD><CODE>region</CODE> - - classified data sets<DT><B>See Also:</B><DD><A HREF="DecisionRegion.html" title="class in &lt;Unnamed&gt;"><CODE>DecisionRegion</CODE></A></DL></DD></DL><HR><A NAME="getClosestSet(MyPoint)"><!-- --></A><H3>getClosestSet</H3><PRE>public int <B>getClosestSet</B>(MyPoint&nbsp;mean)</PRE><DL><DD>Determines the closest data sets to the cluster<P><DD><DL><DT><B>Parameters:</B><DD><CODE>mean</CODE> - mean point of the cluster<DT><B>Returns:</B><DD>closest data set to the cluster<DT><B>See Also:</B><DD><CODE>MyPoint</CODE></DL></DD></DL><HR><A NAME="displayClusterError(int, java.util.Vector, int)"><!-- --></A><H3>displayClusterError</H3><PRE>public int <B>displayClusterError</B>(int&nbsp;closest,                               java.util.Vector&nbsp;cluster,                               int&nbsp;id)</PRE><DL><DD>determines the number of points in error, i.e, not classified by finding the distance of the datapoints from the closest of the vector set<P><DD><DL><DT><B>Parameters:</B><DD><CODE>closest</CODE> - the data specifying which of the dataset is the                  closest.<DD><CODE>cluster</CODE> - the data points which form a closest cluster<DD><CODE>id</CODE> - unused in current implementation<DT><B>Returns:</B><DD>error   number of data points which lie out of the                   classification</DL></DD></DL><HR><A NAME="getDecisionRegion(java.util.Vector)"><!-- --></A><H3>getDecisionRegion</H3><PRE>public java.util.Vector&lt;MyPoint&gt; <B>getDecisionRegion</B>(java.util.Vector&lt;MyPoint&gt;&nbsp;vec)</PRE><DL><DD>Computes the k-mean decision region - nearest neighbor algorithm<P><DD><DL><DT><B>Parameters:</B><DD><CODE>vec</CODE> - vector of initial guesses<DT><B>Returns:</B><DD>vector of desision region points</DL></DD></DL><HR><A NAME="outputDecisionRegion()"><!-- --></A><H3>outputDecisionRegion</H3><PRE>public void <B>outputDecisionRegion</B>()</PRE><DL><DD>displays the decision region on the output panel<P><DD><DL></DL></DD></DL><!-- ========= END OF CLASS DATA ========= --><HR><!-- ======= START OF BOTTOM NAVBAR ====== --><A NAME="navbar_bottom"><!-- --></A><A HREF="#skip-navbar_bottom" title="Skip navigation links"></A><TABLE BORDER="0" WIDTH="100%" CELLPADDING="1" CELLSPACING="0" SUMMARY=""><TR><TD COLSPAN=2 BGCOLOR="#EEEEFF" CLASS="NavBarCell1"><A NAME="navbar_bottom_firstrow"><!-- --></A><TABLE BORDER="0" CELLPADDING="0" CELLSPACING="3" SUMMARY="">  <TR ALIGN="center" VALIGN="top">  <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1">    <A HREF="package-summary.html"><FONT CLASS="NavBarFont1"><B>Package</B></FONT></A>&nbsp;</TD>  <TD BGCOLOR="#FFFFFF" CLASS="NavBarCell1Rev"> &nbsp;<FONT CLASS="NavBarFont1Rev"><B>Class</B></FONT>&nbsp;</TD>  <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1">    <A HREF="package-tree.html"><FONT CLASS="NavBarFont1"><B>Tree</B></FONT></A>&nbsp;</TD>  <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1">    <A HREF="deprecated-list.html"><FONT CLASS="NavBarFont1"><B>Deprecated</B></FONT></A>&nbsp;</TD>  <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1">    <A HREF="index-all.html"><FONT CLASS="NavBarFont1"><B>Index</B></FONT></A>&nbsp;</TD>  <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1">    <A HREF="help-doc.html"><FONT CLASS="NavBarFont1"><B>Help</B></FONT></A>&nbsp;</TD>  </TR></TABLE></TD><TD ALIGN="right" VALIGN="top" ROWSPAN=3><EM></EM></TD></TR><TR><TD BGCOLOR="white" CLASS="NavBarCell2"><FONT SIZE="-2">&nbsp;<A HREF="AlgorithmKF.html" title="class in &lt;Unnamed&gt;"><B>PREV CLASS</B></A>&nbsp;&nbsp;<A HREF="AlgorithmLBG.html" title="class in &lt;Unnamed&gt;"><B>NEXT CLASS</B></A></FONT></TD><TD BGCOLOR="white" CLASS="NavBarCell2"><FONT SIZE="-2">  <A HREF="index.html?AlgorithmKMeans.html" target="_top"><B>FRAMES</B></A>  &nbsp;&nbsp;<A HREF="AlgorithmKMeans.html" target="_top"><B>NO FRAMES</B></A>  &nbsp;&nbsp;<SCRIPT type="text/javascript">  <!--  if(window==top) {    document.writeln('<A HREF="allclasses-noframe.html"><B>All Classes</B></A>');  }  //--></SCRIPT><NOSCRIPT>  <A HREF="allclasses-noframe.html"><B>All Classes</B></A></NOSCRIPT></FONT></TD></TR><TR><TD VALIGN="top" CLASS="NavBarCell3"><FONT SIZE="-2">  SUMMARY:&nbsp;NESTED&nbsp;|&nbsp;<A HREF="#field_summary">FIELD</A>&nbsp;|&nbsp;<A HREF="#constructor_summary">CONSTR</A>&nbsp;|&nbsp;<A HREF="#method_summary">METHOD</A></FONT></TD><TD VALIGN="top" CLASS="NavBarCell3"><FONT SIZE="-2">DETAIL:&nbsp;<A HREF="#field_detail">FIELD</A>&nbsp;|&nbsp;<A HREF="#constructor_detail">CONSTR</A>&nbsp;|&nbsp;<A HREF="#method_detail">METHOD</A></FONT></TD></TR></TABLE><A NAME="skip-navbar_bottom"></A><!-- ======== END OF BOTTOM NAVBAR ======= --><HR></BODY></HTML>@1.1log@temp.text@text@d5 1a5 1<!-- Generated by javadoc (build 1.5.0_03) on Fri Jun 03 16:18:38 CDT 2005 -->d53 1a53 1&nbsp;<A HREF="AlgorithmED.html" title="class in &lt;Unnamed&gt;"><B>PREV CLASS</B></A>&nbsp;d196 1a196 1<TD><CODE><B><A HREF="AlgorithmKMeans.html#getClosestSet(MyPoint)">getClosestSet</A></B>(<A HREF="MyPoint.html" title="class in &lt;Unnamed&gt;">MyPoint</A>&nbsp;mean)</CODE>d203 2a204 2<CODE>&nbsp;java.util.Vector&lt;<A HREF="MyPoint.html" title="class in &lt;Unnamed&gt;">MyPoint</A>&gt;</CODE></FONT></TD><TD><CODE><B><A HREF="AlgorithmKMeans.html#getDecisionRegion(java.util.Vector)">getDecisionRegion</A></B>(java.util.Vector&lt;<A HREF="MyPoint.html" title="class in &lt;Unnamed&gt;">MyPoint</A>&gt;&nbsp;vec)</CODE>d415 1a415 1public int <B>getClosestSet</B>(<A HREF="MyPoint.html" title="class in &lt;Unnamed&gt;">MyPoint</A>&nbsp;mean)</PRE>d421 1a421 1<DT><B>Returns:</B><DD>closest data set to the cluster<DT><B>See Also:</B><DD><A HREF="MyPoint.html" title="class in &lt;Unnamed&gt;"><CODE>MyPoint</CODE></A></DL>d449 1a449 1public java.util.Vector&lt;<A HREF="MyPoint.html" title="class in &lt;Unnamed&gt;">MyPoint</A>&gt; <B>getDecisionRegion</B>(java.util.Vector&lt;<A HREF="MyPoint.html" title="class in &lt;Unnamed&gt;">MyPoint</A>&gt;&nbsp;vec)</PRE>d500 1a500 1&nbsp;<A HREF="AlgorithmED.html" title="class in &lt;Unnamed&gt;"><B>PREV CLASS</B></A>&nbsp;@

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