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< 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;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/adtree/ADTree.html#setRandomSeed(int)">setRandomSeed</A></B>(int&nbsp;seed)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Sets random seed for a random walk.</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/adtree/ADTree.html#setSaveInstanceData(boolean)">setSaveInstanceData</A></B>(boolean&nbsp;v)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Sets whether the tree is to save instance data.</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/adtree/ADTree.html#setSearchPath(weka.core.SelectedTag)">setSearchPath</A></B>(<A HREF="../../../weka/core/SelectedTag.html">SelectedTag</A>&nbsp;newMethod)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Sets the method of searching the tree for a new insertion.</TD>
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<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/adtree/ADTree.html#toString()">toString</A></B>()</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Returns a description of the classifier.</TD>
</TR>
<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>protected &nbsp;java.lang.String</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#toString(weka.classifiers.adtree.PredictionNode, int)">toString</A></B>(<A HREF="../../../weka/classifiers/adtree/PredictionNode.html">PredictionNode</A>&nbsp;currentNode,
         int&nbsp;level)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Traverses the tree, forming a string that describes it.</TD>
</TR>
</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>equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait</CODE></TD>
</TR>
</TABLE>
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<P>

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

<A NAME="field_detail"><!-- --></A>
<TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%">
<TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor">
<TD COLSPAN=1><FONT SIZE="+2">
<B>Field Detail</B></FONT></TD>
</TR>
</TABLE>

<A NAME="SEARCHPATH_ALL"><!-- --></A><H3>
SEARCHPATH_ALL</H3>
<PRE>
public static final int <B>SEARCHPATH_ALL</B></PRE>
<DL>
<DD>The search modes</DL>
<HR>

<A NAME="SEARCHPATH_HEAVIEST"><!-- --></A><H3>
SEARCHPATH_HEAVIEST</H3>
<PRE>
public static final int <B>SEARCHPATH_HEAVIEST</B></PRE>
<DL>
</DL>
<HR>

<A NAME="SEARCHPATH_ZPURE"><!-- --></A><H3>
SEARCHPATH_ZPURE</H3>
<PRE>
public static final int <B>SEARCHPATH_ZPURE</B></PRE>
<DL>
</DL>
<HR>

<A NAME="SEARCHPATH_RANDOM"><!-- --></A><H3>
SEARCHPATH_RANDOM</H3>
<PRE>
public static final int <B>SEARCHPATH_RANDOM</B></PRE>
<DL>
</DL>
<HR>

<A NAME="TAGS_SEARCHPATH"><!-- --></A><H3>
TAGS_SEARCHPATH</H3>
<PRE>
public static final <A HREF="../../../weka/core/Tag.html">Tag</A>[] <B>TAGS_SEARCHPATH</B></PRE>
<DL>
</DL>
<HR>

<A NAME="m_trainInstances"><!-- --></A><H3>
m_trainInstances</H3>
<PRE>
protected <A HREF="../../../weka/core/Instances.html">Instances</A> <B>m_trainInstances</B></PRE>
<DL>
<DD>The instances used to train the tree</DL>
<HR>

<A NAME="m_root"><!-- --></A><H3>
m_root</H3>
<PRE>
protected <A HREF="../../../weka/classifiers/adtree/PredictionNode.html">PredictionNode</A> <B>m_root</B></PRE>
<DL>
<DD>The root of the tree</DL>
<HR>

<A NAME="m_random"><!-- --></A><H3>
m_random</H3>
<PRE>
protected java.util.Random <B>m_random</B></PRE>
<DL>
<DD>The random number generator - used for the random search heuristic</DL>
<HR>

<A NAME="m_lastAddedSplitNum"><!-- --></A><H3>
m_lastAddedSplitNum</H3>
<PRE>
protected int <B>m_lastAddedSplitNum</B></PRE>
<DL>
<DD>The number of the last splitter added to the tree</DL>
<HR>

<A NAME="m_numericAttIndices"><!-- --></A><H3>
m_numericAttIndices</H3>
<PRE>
protected int[] <B>m_numericAttIndices</B></PRE>
<DL>
<DD>An array containing the inidices to the numeric attributes in the data</DL>
<HR>

<A NAME="m_nominalAttIndices"><!-- --></A><H3>
m_nominalAttIndices</H3>
<PRE>
protected int[] <B>m_nominalAttIndices</B></PRE>
<DL>
<DD>An array containing the inidices to the nominal attributes in the data</DL>
<HR>

<A NAME="m_trainTotalWeight"><!-- --></A><H3>
m_trainTotalWeight</H3>
<PRE>
protected double <B>m_trainTotalWeight</B></PRE>
<DL>
<DD>The total weight of the instances - used to speed Z calculations</DL>
<HR>

<A NAME="m_posTrainInstances"><!-- --></A><H3>
m_posTrainInstances</H3>
<PRE>
protected <A HREF="../../../weka/classifiers/adtree/ReferenceInstances.html">ReferenceInstances</A> <B>m_posTrainInstances</B></PRE>
<DL>
<DD>The training instances with positive class - referencing the training dataset</DL>
<HR>

<A NAME="m_negTrainInstances"><!-- --></A><H3>
m_negTrainInstances</H3>
<PRE>
protected <A HREF="../../../weka/classifiers/adtree/ReferenceInstances.html">ReferenceInstances</A> <B>m_negTrainInstances</B></PRE>
<DL>
<DD>The training instances with negative class - referencing the training dataset</DL>
<HR>

<A NAME="m_search_bestInsertionNode"><!-- --></A><H3>
m_search_bestInsertionNode</H3>
<PRE>
protected <A HREF="../../../weka/classifiers/adtree/PredictionNode.html">PredictionNode</A> <B>m_search_bestInsertionNode</B></PRE>
<DL>
<DD>The best node to insert under, as found so far by the latest search</DL>
<HR>

<A NAME="m_search_bestSplitter"><!-- --></A><H3>
m_search_bestSplitter</H3>
<PRE>
protected <A HREF="../../../weka/classifiers/adtree/Splitter.html">Splitter</A> <B>m_search_bestSplitter</B></PRE>
<DL>
<DD>The best splitter to insert, as found so far by the latest search</DL>
<HR>

<A NAME="m_search_smallestZ"><!-- --></A><H3>
m_search_smallestZ</H3>
<PRE>
protected double <B>m_search_smallestZ</B></PRE>
<DL>
<DD>The smallest Z value found so far by the latest search</DL>
<HR>

<A NAME="m_search_bestPathPosInstances"><!-- --></A><H3>
m_search_bestPathPosInstances</H3>
<PRE>
protected <A HREF="../../../weka/core/Instances.html">Instances</A> <B>m_search_bestPathPosInstances</B></PRE>
<DL>
<DD>The positive instances that apply to the best path found so far</DL>
<HR>

<A NAME="m_search_bestPathNegInstances"><!-- --></A><H3>
m_search_bestPathNegInstances</H3>
<PRE>
protected <A HREF="../../../weka/core/Instances.html">Instances</A> <B>m_search_bestPathNegInstances</B></PRE>
<DL>
<DD>The negative instances that apply to the best path found so far</DL>
<HR>

<A NAME="m_nodesExpanded"><!-- --></A><H3>
m_nodesExpanded</H3>
<PRE>
protected int <B>m_nodesExpanded</B></PRE>
<DL>
<DD>Statistics - the number of prediction nodes investigated during search</DL>
<HR>

<A NAME="m_examplesCounted"><!-- --></A><H3>
m_examplesCounted</H3>
<PRE>
protected int <B>m_examplesCounted</B></PRE>
<DL>
<DD>Statistics - the number of instances processed during search</DL>
<HR>

<A NAME="m_boostingIterations"><!-- --></A><H3>
m_boostingIterations</H3>
<PRE>
protected int <B>m_boostingIterations</B></PRE>
<DL>
<DD>Option - the number of boosting iterations o perform</DL>
<HR>

<A NAME="m_searchPath"><!-- --></A><H3>
m_searchPath</H3>
<PRE>
protected int <B>m_searchPath</B></PRE>
<DL>
<DD>Option - the search mode</DL>
<HR>

<A NAME="m_randomSeed"><!-- --></A><H3>
m_randomSeed</H3>
<PRE>
protected int <B>m_randomSeed</B></PRE>
<DL>
<DD>Option - the seed to use for a random search</DL>
<HR>

<A NAME="m_saveInstanceData"><!-- --></A><H3>
m_saveInstanceData</H3>
<PRE>
protected boolean <B>m_saveInstanceData</B></PRE>
<DL>
<DD>Option - whether the tree should remember the instance data</DL>

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

<A NAME="constructor_detail"><!-- --></A>
<TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%">
<TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor">
<TD COLSPAN=1><FONT SIZE="+2">
<B>Constructor Detail</B></FONT></TD>
</TR>
</TABLE>

<A NAME="ADTree()"><!-- --></A><H3>
ADTree</H3>
<PRE>
public <B>ADTree</B>()</PRE>
<DL>
</DL>

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

<A NAME="method_detail"><!-- --></A>
<TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%">
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<TD COLSPAN=1><FONT SIZE="+2">
<B>Method Detail</B></FONT></TD>
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<A NAME="initClassifier(weka.core.Instances)"><!-- --></A><H3>
initClassifier</H3>
<PRE>
public void <B>initClassifier</B>(<A HREF="../../../weka/core/Instances.html">Instances</A>&nbsp;instances)
                    throws java.lang.Exception</PRE>
<DL>
<DD>Sets up the tree ready to be trained, using two-class optimized method.<DD><DL>
<DT><B>Specified by: </B><DD><CODE><A HREF="../../../weka/classifiers/IterativeClassifier.html#initClassifier(weka.core.Instances)">initClassifier</A></CODE> in interface <CODE><A HREF="../../../weka/classifiers/IterativeClassifier.html">IterativeClassifier</A></CODE></DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>instances</CODE> - the instances to train the tree with<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if training data is unsuitable</DL>
</DD>
</DL>
<HR>