vfi.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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<TD><B>Methods inherited from class weka.classifiers.<A HREF="../../weka/classifiers/Classifier.html">Classifier</A></B></TD>
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<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>
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&nbsp;<A NAME="methods_inherited_from_class_java.lang.Object"><!-- --></A>
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<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>
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&nbsp;
<P>

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<B>Field Detail</B></FONT></TD>
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<A NAME="m_ClassIndex"><!-- --></A><H3>
m_ClassIndex</H3>
<PRE>
protected int <B>m_ClassIndex</B></PRE>
<DL>
<DD>The index of the class attribute</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>
<HR>

<A NAME="m_Instances"><!-- --></A><H3>
m_Instances</H3>
<PRE>
protected <A HREF="../../weka/core/Instances.html">Instances</A> <B>m_Instances</B></PRE>
<DL>
<DD>The training data</DL>
<HR>

<A NAME="m_counts"><!-- --></A><H3>
m_counts</H3>
<PRE>
protected double[][][] <B>m_counts</B></PRE>
<DL>
<DD>The class counts for each interval of each attribute</DL>
<HR>

<A NAME="m_globalCounts"><!-- --></A><H3>
m_globalCounts</H3>
<PRE>
protected double[] <B>m_globalCounts</B></PRE>
<DL>
<DD>The global class counts</DL>
<HR>

<A NAME="m_intervalBounds"><!-- --></A><H3>
m_intervalBounds</H3>
<PRE>
protected double[][] <B>m_intervalBounds</B></PRE>
<DL>
<DD>The lower bounds for each attribute</DL>
<HR>

<A NAME="m_maxEntrop"><!-- --></A><H3>
m_maxEntrop</H3>
<PRE>
protected double <B>m_maxEntrop</B></PRE>
<DL>
<DD>The maximum entropy for the class</DL>
<HR>

<A NAME="m_weightByConfidence"><!-- --></A><H3>
m_weightByConfidence</H3>
<PRE>
protected boolean <B>m_weightByConfidence</B></PRE>
<DL>
<DD>Exponentially bias more confident intervals</DL>
<HR>

<A NAME="m_bias"><!-- --></A><H3>
m_bias</H3>
<PRE>
protected double <B>m_bias</B></PRE>
<DL>
<DD>Bias towards more confident intervals</DL>

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

<A NAME="constructor_detail"><!-- --></A>
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<B>Constructor Detail</B></FONT></TD>
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<A NAME="VFI()"><!-- --></A><H3>
VFI</H3>
<PRE>
public <B>VFI</B>()</PRE>
<DL>
</DL>

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<A NAME="globalInfo()"><!-- --></A><H3>
globalInfo</H3>
<PRE>
public java.lang.String <B>globalInfo</B>()</PRE>
<DL>
<DD>Returns a string describing this search method<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>a description of the search method suitable for
 displaying in the explorer/experimenter gui</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>

 -C <br>
 Don't weight voting intervals by confidence. <p>

 -B <bias> <br>
 Set exponential bias towards confident intervals. default = 1.0 <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="weightByConfidenceTipText()"><!-- --></A><H3>
weightByConfidenceTipText</H3>
<PRE>
public java.lang.String <B>weightByConfidenceTipText</B>()</PRE>
<DL>
<DD>Returns the tip text for this property<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>tip text for this property suitable for
 displaying in the explorer/experimenter gui</DL>
</DD>
</DL>
<HR>

<A NAME="setWeightByConfidence(boolean)"><!-- --></A><H3>
setWeightByConfidence</H3>
<PRE>
public void <B>setWeightByConfidence</B>(boolean&nbsp;c)</PRE>
<DL>
<DD>Set weighting by confidence<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>c</CODE> - true if feature intervals are to be weighted by confidence</DL>
</DD>
</DL>
<HR>

<A NAME="getWeightByConfidence()"><!-- --></A><H3>
getWeightByConfidence</H3>
<PRE>
public boolean <B>getWeightByConfidence</B>()</PRE>
<DL>
<DD>Get whether feature intervals are being weighted by confidence<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>true if weighting by confidence is selected</DL>
</DD>
</DL>
<HR>

<A NAME="biasTipText()"><!-- --></A><H3>
biasTipText</H3>
<PRE>
public java.lang.String <B>biasTipText</B>()</PRE>
<DL>
<DD>Returns the tip text for this property<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>tip text for this property suitable for
 displaying in the explorer/experimenter gui</DL>
</DD>
</DL>
<HR>

<A NAME="setBias(double)"><!-- --></A><H3>
setBias</H3>
<PRE>
public void <B>setBias</B>(double&nbsp;b)</PRE>
<DL>
<DD>Set the value of the exponential bias towards more confident intervals<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>b</CODE> - the value of the bias parameter</DL>
</DD>
</DL>
<HR>

<A NAME="getBias()"><!-- --></A><H3>
getBias</H3>
<PRE>
public double <B>getBias</B>()</PRE>
<DL>
<DD>Get the value of the bias parameter<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the bias parameter</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 VFI<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="buildClassifier(weka.core.Instances)"><!-- --></A><H3>
buildClassifier</H3>
<PRE>
public void <B>buildClassifier</B>(<A HREF="../../weka/core/Instances.html">Instances</A>&nbsp;instances)
                     throws java.lang.Exception</PRE>
<DL>
<DD>Generates the classifier.<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>instances</CODE> - set of instances serving as training data<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if the classifier has not been generated successfully</DL>
</DD>
</DL>
<HR>

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

<A NAME="distributionForInstance(weka.core.Instance)"><!-- --></A><H3>
distributionForInstance</H3>
<PRE>
public double[] <B>distributionForInstance</B>(<A HREF="../../weka/core/Instance.html">Instance</A>&nbsp;instance)
                                 throws java.lang.Exception</PRE>
<DL>
<DD>Classifies the given test instance.<DD><DL>
<DT><B>Overrides:</B><DD><CODE><A HREF="../../weka/classifiers/DistributionClassifier.html#distributionForInstance(weka.core.Instance)">distributionForInstance</A></CODE> in class <CODE><A HREF="../../weka/classifiers/DistributionClassifier.html">DistributionClassifier</A></CODE></DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>instance</CODE> - the instance to be classified<DT><B>Returns:</B><DD>the predicted class for the instance<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if the instance can't be classified</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;args)</PRE>
<DL>
<DD>Main method for testing this class.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>args</CODE> - should contain command line arguments for evaluation
 (see Evaluation).</DL>
</DD>
</DL>
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