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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

</DL>
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<A NAME="getCostMatrixSource()"><!-- --></A><H3>
getCostMatrixSource</H3>
<PRE>
public <A HREF="../../weka/core/SelectedTag.html">SelectedTag</A> <B>getCostMatrixSource</B>()</PRE>
<DL>
<DD>Gets the source location method of the cost matrix. Will be one of
 MATRIX_ON_DEMAND or MATRIX_SUPPLIED.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the cost matrix source.</DL>
</DD>
</DL>
<HR>

<A NAME="setCostMatrixSource(weka.core.SelectedTag)"><!-- --></A><H3>
setCostMatrixSource</H3>
<PRE>
public void <B>setCostMatrixSource</B>(<A HREF="../../weka/core/SelectedTag.html">SelectedTag</A>&nbsp;newMethod)</PRE>
<DL>
<DD>Sets the source location of the cost matrix. Values other than
 MATRIX_ON_DEMAND or MATRIX_SUPPLIED will be ignored.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>newMethod</CODE> - the cost matrix location method.</DL>
</DD>
</DL>
<HR>

<A NAME="getOnDemandDirectory()"><!-- --></A><H3>
getOnDemandDirectory</H3>
<PRE>
public java.io.File <B>getOnDemandDirectory</B>()</PRE>
<DL>
<DD>Returns the directory that will be searched for cost files when
 loading on demand.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>The cost file search directory.</DL>
</DD>
</DL>
<HR>

<A NAME="setOnDemandDirectory(java.io.File)"><!-- --></A><H3>
setOnDemandDirectory</H3>
<PRE>
public void <B>setOnDemandDirectory</B>(java.io.File&nbsp;newDir)</PRE>
<DL>
<DD>Sets the directory that will be searched for cost files when
 loading on demand.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>newDir</CODE> - The cost file search directory.</DL>
</DD>
</DL>
<HR>

<A NAME="setClassifier(weka.classifiers.Classifier)"><!-- --></A><H3>
setClassifier</H3>
<PRE>
public void <B>setClassifier</B>(<A HREF="../../weka/classifiers/Classifier.html">Classifier</A>&nbsp;classifier)</PRE>
<DL>
<DD>Sets the distribution classifier<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>classifier</CODE> - the distribution classifier with all options set.</DL>
</DD>
</DL>
<HR>

<A NAME="getClassifier()"><!-- --></A><H3>
getClassifier</H3>
<PRE>
public <A HREF="../../weka/classifiers/Classifier.html">Classifier</A> <B>getClassifier</B>()</PRE>
<DL>
<DD>Gets the distribution classifier used.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the classifier</DL>
</DD>
</DL>
<HR>

<A NAME="getClassifierSpec()"><!-- --></A><H3>
getClassifierSpec</H3>
<PRE>
protected java.lang.String <B>getClassifierSpec</B>()</PRE>
<DL>
<DD>Gets the classifier specification string, which contains the class name of
 the classifier and any options to the classifier<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the classifier string.</DL>
</DD>
</DL>
<HR>

<A NAME="getBagSizePercent()"><!-- --></A><H3>
getBagSizePercent</H3>
<PRE>
public int <B>getBagSizePercent</B>()</PRE>
<DL>
<DD>Gets the size of each bag, as a percentage of the training set size.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the bag size, as a percentage.</DL>
</DD>
</DL>
<HR>

<A NAME="setBagSizePercent(int)"><!-- --></A><H3>
setBagSizePercent</H3>
<PRE>
public void <B>setBagSizePercent</B>(int&nbsp;newBagSizePercent)</PRE>
<DL>
<DD>Sets the size of each bag, as a percentage of the training set size.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>newBagSizePercent</CODE> - the bag size, as a percentage.</DL>
</DD>
</DL>
<HR>

<A NAME="setNumIterations(int)"><!-- --></A><H3>
setNumIterations</H3>
<PRE>
public void <B>setNumIterations</B>(int&nbsp;numIterations)</PRE>
<DL>
<DD>Sets the number of bagging iterations<DD><DL>
</DL>
</DD>
</DL>
<HR>

<A NAME="getNumIterations()"><!-- --></A><H3>
getNumIterations</H3>
<PRE>
public int <B>getNumIterations</B>()</PRE>
<DL>
<DD>Gets the number of bagging iterations<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the maximum number of bagging iterations</DL>
</DD>
</DL>
<HR>

<A NAME="getCostMatrix()"><!-- --></A><H3>
getCostMatrix</H3>
<PRE>
public <A HREF="../../weka/classifiers/CostMatrix.html">CostMatrix</A> <B>getCostMatrix</B>()</PRE>
<DL>
<DD>Gets the misclassification cost matrix.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the cost matrix</DL>
</DD>
</DL>
<HR>

<A NAME="setCostMatrix(weka.classifiers.CostMatrix)"><!-- --></A><H3>
setCostMatrix</H3>
<PRE>
public void <B>setCostMatrix</B>(<A HREF="../../weka/classifiers/CostMatrix.html">CostMatrix</A>&nbsp;newCostMatrix)</PRE>
<DL>
<DD>Sets the misclassification cost matrix.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>the</CODE> - cost matrix</DL>
</DD>
</DL>
<HR>

<A NAME="setSeed(int)"><!-- --></A><H3>
setSeed</H3>
<PRE>
public void <B>setSeed</B>(int&nbsp;seed)</PRE>
<DL>
<DD>Set seed for resampling.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>seed</CODE> - the seed for resampling</DL>
</DD>
</DL>
<HR>

<A NAME="getSeed()"><!-- --></A><H3>
getSeed</H3>
<PRE>
public int <B>getSeed</B>()</PRE>
<DL>
<DD>Get seed for resampling.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the seed for resampling</DL>
</DD>
</DL>
<HR>

<A NAME="buildClassifier(weka.core.Instances)"><!-- --></A><H3>
buildClassifier</H3>
<PRE>
public void <B>buildClassifier</B>(<A HREF="../../weka/core/Instances.html">Instances</A>&nbsp;data)
                     throws java.lang.Exception</PRE>
<DL>
<DD>Builds the model of the base learner.<DD><DL>
<DT><B>Overrides:</B><DD><CODE><A HREF="../../weka/classifiers/Classifier.html#buildClassifier(weka.core.Instances)">buildClassifier</A></CODE> in class <CODE><A HREF="../../weka/classifiers/Classifier.html">Classifier</A></CODE></DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>data</CODE> - the training data<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if the classifier could not be built successfully</DL>
</DD>
</DL>
<HR>

<A NAME="classifyInstance(weka.core.Instance)"><!-- --></A><H3>
classifyInstance</H3>
<PRE>
public double <B>classifyInstance</B>(<A HREF="../../weka/core/Instance.html">Instance</A>&nbsp;instance)
                        throws java.lang.Exception</PRE>
<DL>
<DD>Classifies a given test instance.<DD><DL>
<DT><B>Overrides:</B><DD><CODE><A HREF="../../weka/classifiers/Classifier.html#classifyInstance(weka.core.Instance)">classifyInstance</A></CODE> in class <CODE><A HREF="../../weka/classifiers/Classifier.html">Classifier</A></CODE></DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>instance</CODE> - the instance to be classified<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if instance could not be classified
 successfully</DL>
</DD>
</DL>
<HR>

<A NAME="toString()"><!-- --></A><H3>
toString</H3>
<PRE>
public java.lang.String <B>toString</B>()</PRE>
<DL>
<DD>Output a representation of this classifier<DD><DL>
<DT><B>Overrides:</B><DD><CODE>toString</CODE> in class <CODE>java.lang.Object</CODE></DL>
</DD>
</DL>
<HR>

<A NAME="main(java.lang.String[])"><!-- --></A><H3>
main</H3>
<PRE>
public static void <B>main</B>(java.lang.String[]&nbsp;argv)</PRE>
<DL>
<DD>Main method for testing this class.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>argv</CODE> - should contain the following arguments:
 -t training file [-T test file] [-c class index]</DL>
</DD>
</DL>
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