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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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<A NAME="m_ClassifierIndex"><!-- --></A><H3>
m_ClassifierIndex</H3>
<PRE>
protected int <B>m_ClassifierIndex</B></PRE>
<DL>
<DD>The index into the vector for the selected scheme</DL>
<HR>

<A NAME="m_NumXValFolds"><!-- --></A><H3>
m_NumXValFolds</H3>
<PRE>
protected int <B>m_NumXValFolds</B></PRE>
<DL>
<DD>Number of folds to use for cross validation (0 means use training
 error for selection)</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_Seed"><!-- --></A><H3>
m_Seed</H3>
<PRE>
protected int <B>m_Seed</B></PRE>
<DL>
<DD>Random number seed</DL>

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

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<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>

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

 -B classifierstring <br>
 Classifierstring should contain the full class name of a scheme
 included for selection followed by options to the classifier
 (required, option should be used once for each classifier).<p>

 -X num_folds <br>
 Use cross validation error as the basis for classifier selection.
 (default 0, is to use error on the training data instead)<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>

<A NAME="setClassifiers(weka.classifiers.Classifier[])"><!-- --></A><H3>
setClassifiers</H3>
<PRE>
public void <B>setClassifiers</B>(<A HREF="../../weka/classifiers/Classifier.html">Classifier</A>[]&nbsp;classifiers)</PRE>
<DL>
<DD>Sets the list of possible classifers to choose from.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>classifiers</CODE> - an array of classifiers with all options set.</DL>
</DD>
</DL>
<HR>

<A NAME="getClassifiers()"><!-- --></A><H3>
getClassifiers</H3>
<PRE>
public <A HREF="../../weka/classifiers/Classifier.html">Classifier</A>[] <B>getClassifiers</B>()</PRE>
<DL>
<DD>Gets the list of possible classifers to choose from.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the array of Classifiers</DL>
</DD>
</DL>
<HR>

<A NAME="getClassifier(int)"><!-- --></A><H3>
getClassifier</H3>
<PRE>
public <A HREF="../../weka/classifiers/Classifier.html">Classifier</A> <B>getClassifier</B>(int&nbsp;index)</PRE>
<DL>
<DD>Gets a single classifier from the set of available classifiers.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>index</CODE> - the index of the classifier wanted<DT><B>Returns:</B><DD>the Classifier</DL>
</DD>
</DL>
<HR>

<A NAME="getClassifierSpec(int)"><!-- --></A><H3>
getClassifierSpec</H3>
<PRE>
protected java.lang.String <B>getClassifierSpec</B>(int&nbsp;index)</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>Parameters:</B><DD><CODE>index</CODE> - the index of the classifier string to retrieve, starting from
 0.<DT><B>Returns:</B><DD>the classifier string, or the empty string if no classifier
 has been assigned (or the index given is out of range).</DL>
</DD>
</DL>
<HR>

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

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

<A NAME="getNumFolds()"><!-- --></A><H3>
getNumFolds</H3>
<PRE>
public int <B>getNumFolds</B>()</PRE>
<DL>
<DD>Gets the number of folds for cross-validation. A number less
 than 2 specifies using training error rather than cross-validation.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the number of folds for cross-validation</DL>
</DD>
</DL>
<HR>

<A NAME="setNumFolds(int)"><!-- --></A><H3>
setNumFolds</H3>
<PRE>
public void <B>setNumFolds</B>(int&nbsp;numFolds)</PRE>
<DL>
<DD>Sets the number of folds for cross-validation. A number less
 than 2 specifies using training error rather than cross-validation.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>numFolds</CODE> - the number of folds for cross-validation</DL>
</DD>
</DL>
<HR>

<A NAME="setDebug(boolean)"><!-- --></A><H3>
setDebug</H3>
<PRE>
public void <B>setDebug</B>(boolean&nbsp;debug)</PRE>
<DL>
<DD>Set debugging mode<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>debug</CODE> - true if debug output should be printed</DL>
</DD>
</DL>
<HR>

<A NAME="getDebug()"><!-- --></A><H3>
getDebug</H3>
<PRE>
public boolean <B>getDebug</B>()</PRE>
<DL>
<DD>Get whether debugging is turned on<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>true if debugging output is on</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>Buildclassifier selects a classifier from the set of classifiers
 by minimising error on the training data.<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 to be used for generating the
 boosted classifier.<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 instance using the selected classifier.<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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