adaboostm1.html

< 数据挖掘--实用机器学习技术及java实现> 一书结合数据挖掘和机器学习的知识,作者陈述了自动挖掘模式的基础理论,并且以java语言实现了具有代表性的各类数据挖掘方法.例如:class

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Returns an enumeration describing the available options</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>static&nbsp;void</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../weka/classifiers/AdaBoostM1.html#main(java.lang.String[])">main</A></B>(java.lang.String[]&nbsp;argv)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Main method for testing this class.</TD>
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<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>protected &nbsp;<A HREF="../../weka/core/Instances.html">Instances</A></CODE></FONT></TD>
<TD><CODE><B><A HREF="../../weka/classifiers/AdaBoostM1.html#selectWeightQuantile(weka.core.Instances, double)">selectWeightQuantile</A></B>(<A HREF="../../weka/core/Instances.html">Instances</A>&nbsp;data,
                     double&nbsp;quantile)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Select only instances with weights that contribute to 
 the specified quantile of the weight distribution</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>&nbsp;void</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../weka/classifiers/AdaBoostM1.html#setClassifier(weka.classifiers.Classifier)">setClassifier</A></B>(<A HREF="../../weka/classifiers/Classifier.html">Classifier</A>&nbsp;newClassifier)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Set the classifier for boosting.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>&nbsp;void</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../weka/classifiers/AdaBoostM1.html#setDebug(boolean)">setDebug</A></B>(boolean&nbsp;debug)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Set debugging mode</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>&nbsp;void</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../weka/classifiers/AdaBoostM1.html#setMaxIterations(int)">setMaxIterations</A></B>(int&nbsp;maxIterations)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Set the maximum number of boost iterations</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>&nbsp;void</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../weka/classifiers/AdaBoostM1.html#setOptions(java.lang.String[])">setOptions</A></B>(java.lang.String[]&nbsp;options)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Parses a given list of options.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>&nbsp;void</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../weka/classifiers/AdaBoostM1.html#setSeed(int)">setSeed</A></B>(int&nbsp;seed)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Set seed for resampling.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>&nbsp;void</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../weka/classifiers/AdaBoostM1.html#setUseResampling(boolean)">setUseResampling</A></B>(boolean&nbsp;r)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Set resampling mode</TD>
</TR>
<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>&nbsp;void</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../weka/classifiers/AdaBoostM1.html#setWeightThreshold(int)">setWeightThreshold</A></B>(int&nbsp;threshold)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Set weight threshold</TD>
</TR>
<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>&nbsp;java.lang.String</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../weka/classifiers/AdaBoostM1.html#toSource(java.lang.String)">toSource</A></B>(java.lang.String&nbsp;className)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Returns the boosted model as Java source code.</TD>
</TR>
<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>&nbsp;java.lang.String</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../weka/classifiers/AdaBoostM1.html#toString()">toString</A></B>()</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Returns description of the boosted classifier.</TD>
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</TABLE>
&nbsp;<A NAME="methods_inherited_from_class_weka.classifiers.DistributionClassifier"><!-- --></A>
<TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%">
<TR BGCOLOR="#EEEEFF" CLASS="TableSubHeadingColor">
<TD><B>Methods inherited from class weka.classifiers.<A HREF="../../weka/classifiers/DistributionClassifier.html">DistributionClassifier</A></B></TD>
</TR>
<TR BGCOLOR="white" CLASS="TableRowColor">
<TD><CODE><A HREF="../../weka/classifiers/DistributionClassifier.html#classifyInstance(weka.core.Instance)">classifyInstance</A></CODE></TD>
</TR>
</TABLE>
&nbsp;<A NAME="methods_inherited_from_class_weka.classifiers.Classifier"><!-- --></A>
<TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%">
<TR BGCOLOR="#EEEEFF" CLASS="TableSubHeadingColor">
<TD><B>Methods inherited from class weka.classifiers.<A HREF="../../weka/classifiers/Classifier.html">Classifier</A></B></TD>
</TR>
<TR BGCOLOR="white" CLASS="TableRowColor">
<TD><CODE><A HREF="../../weka/classifiers/Classifier.html#forName(java.lang.String, java.lang.String[])">forName</A>, <A HREF="../../weka/classifiers/Classifier.html#makeCopies(weka.classifiers.Classifier, int)">makeCopies</A></CODE></TD>
</TR>
</TABLE>
&nbsp;<A NAME="methods_inherited_from_class_java.lang.Object"><!-- --></A>
<TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%">
<TR BGCOLOR="#EEEEFF" CLASS="TableSubHeadingColor">
<TD><B>Methods inherited from class java.lang.Object</B></TD>
</TR>
<TR BGCOLOR="white" CLASS="TableRowColor">
<TD><CODE>clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait</CODE></TD>
</TR>
</TABLE>
&nbsp;
<P>

<!-- ============ FIELD DETAIL =========== -->

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<B>Field Detail</B></FONT></TD>
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<A NAME="m_Classifier"><!-- --></A><H3>
m_Classifier</H3>
<PRE>
protected <A HREF="../../weka/classifiers/Classifier.html">Classifier</A> <B>m_Classifier</B></PRE>
<DL>
<DD>The model base classifier to use</DL>
<HR>

<A NAME="m_Classifiers"><!-- --></A><H3>
m_Classifiers</H3>
<PRE>
protected <A HREF="../../weka/classifiers/Classifier.html">Classifier</A>[] <B>m_Classifiers</B></PRE>
<DL>
<DD>Array for storing the generated base classifiers.</DL>
<HR>

<A NAME="m_Betas"><!-- --></A><H3>
m_Betas</H3>
<PRE>
protected double[] <B>m_Betas</B></PRE>
<DL>
<DD>Array for storing the weights for the votes.</DL>
<HR>

<A NAME="m_MaxIterations"><!-- --></A><H3>
m_MaxIterations</H3>
<PRE>
protected int <B>m_MaxIterations</B></PRE>
<DL>
<DD>The maximum number of boost iterations</DL>
<HR>

<A NAME="m_NumIterations"><!-- --></A><H3>
m_NumIterations</H3>
<PRE>
protected int <B>m_NumIterations</B></PRE>
<DL>
<DD>The number of successfully generated base classifiers.</DL>
<HR>

<A NAME="m_WeightThreshold"><!-- --></A><H3>
m_WeightThreshold</H3>
<PRE>
protected int <B>m_WeightThreshold</B></PRE>
<DL>
<DD>Weight Threshold. The percentage of weight mass used in training</DL>
<HR>

<A NAME="m_Debug"><!-- --></A><H3>
m_Debug</H3>
<PRE>
protected boolean <B>m_Debug</B></PRE>
<DL>
<DD>Debugging mode, gives extra output if true</DL>
<HR>

<A NAME="m_UseResampling"><!-- --></A><H3>
m_UseResampling</H3>
<PRE>
protected boolean <B>m_UseResampling</B></PRE>
<DL>
<DD>Use boosting with reweighting?</DL>
<HR>

<A NAME="m_Seed"><!-- --></A><H3>
m_Seed</H3>
<PRE>
protected int <B>m_Seed</B></PRE>
<DL>
<DD>Seed for boosting with resampling.</DL>
<HR>

<A NAME="m_NumClasses"><!-- --></A><H3>
m_NumClasses</H3>
<PRE>
protected int <B>m_NumClasses</B></PRE>
<DL>
<DD>The number of classes</DL>

<!-- ========= CONSTRUCTOR DETAIL ======== -->

<A NAME="constructor_detail"><!-- --></A>
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<TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor">
<TD COLSPAN=1><FONT SIZE="+2">
<B>Constructor Detail</B></FONT></TD>
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<A NAME="AdaBoostM1()"><!-- --></A><H3>
AdaBoostM1</H3>
<PRE>
public <B>AdaBoostM1</B>()</PRE>
<DL>
</DL>

<!-- ============ METHOD DETAIL ========== -->

<A NAME="method_detail"><!-- --></A>
<TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%">
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<B>Method Detail</B></FONT></TD>
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<A NAME="selectWeightQuantile(weka.core.Instances, double)"><!-- --></A><H3>
selectWeightQuantile</H3>
<PRE>
protected <A HREF="../../weka/core/Instances.html">Instances</A> <B>selectWeightQuantile</B>(<A HREF="../../weka/core/Instances.html">Instances</A>&nbsp;data,
                                         double&nbsp;quantile)</PRE>
<DL>
<DD>Select only instances with weights that contribute to 
 the specified quantile of the weight distribution<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>data</CODE> - the input instances<DD><CODE>quantile</CODE> - the specified quantile eg 0.9 to select 
 90% of the weight mass<DT><B>Returns:</B><DD>the selected instances</DL>
</DD>
</DL>
<HR>

<A NAME="listOptions()"><!-- --></A><H3>
listOptions</H3>
<PRE>
public java.util.Enumeration <B>listOptions</B>()</PRE>
<DL>
<DD>Returns an enumeration describing the available options<DD><DL>
<DT><B>Specified by: </B><DD><CODE><A HREF="../../weka/core/OptionHandler.html#listOptions()">listOptions</A></CODE> in interface <CODE><A HREF="../../weka/core/OptionHandler.html">OptionHandler</A></CODE></DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>an enumeration of all the available options</DL>
</DD>
</DL>
<HR>

<A NAME="setOptions(java.lang.String[])"><!-- --></A><H3>
setOptions</H3>
<PRE>
public void <B>setOptions</B>(java.lang.String[]&nbsp;options)
                throws java.lang.Exception</PRE>
<DL>
<DD>Parses a given list of options. Valid options are:<p>

 -D <br>
 Turn on debugging output.<p>

 -W classname <br>
 Specify the full class name of a classifier as the basis for 
 boosting (required).<p>

 -I num <br>
 Set the number of boost iterations (default 10). <p>

 -P num <br>
 Set the percentage of weight mass used to build classifiers
 (default 100). <p>

 -Q <br>
 Use resampling instead of reweighting.<p>

 -S seed <br>
 Random number seed for resampling (default 1).<p>

 Options after -- are passed to the designated classifier.<p><DD><DL>
<DT><B>Specified by: </B><DD><CODE><A HREF="../../weka/core/OptionHandler.html#setOptions(java.lang.String[])">setOptions</A></CODE> in interface <CODE><A HREF="../../weka/core/OptionHandler.html">OptionHandler</A></CODE></DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>options</CODE> - the list of options as an array of strings<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if an option is not supported</DL>
</DD>
</DL>
<HR>

<A NAME="getOptions()"><!-- --></A><H3>
getOptions</H3>
<PRE>
public java.lang.String[] <B>getOptions</B>()</PRE>
<DL>
<DD>Gets the current settings of the Classifier.<DD><DL>
<DT><B>Specified by: </B><DD><CODE><A HREF="../../weka/core/OptionHandler.html#getOptions()">getOptions</A></CODE> in interface <CODE><A HREF="../../weka/core/OptionHandler.html">OptionHandler</A></CODE></DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>an array of strings suitable for passing to setOptions</DL>
</DD>
</DL>
<HR>