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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

</TABLE>

<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;insts)
                     throws java.lang.Exception</PRE>
<DL>
<DD>Method for building 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>insts</CODE> - the set of training instances<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if the classifier can't be built successfully</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;inst)
                                 throws java.lang.Exception</PRE>
<DL>
<DD>Outputs the distribution for the given output.

 Pipes output of SVM through sigmoid function.<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>inst</CODE> - the instance for which distribution is to be computed<DT><B>Returns:</B><DD>the distribution<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if something goes wrong</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 num <br>
 The complexity constant C. (default 1)<p>

 -E num <br>
 The exponent for the polynomial kernel. (default 1) <p>

 -N <br>
 Don't normalize the training instances. <p>

 -L <br>
 Rescale kernel. <p>

 -O <br>
 Use lower-order terms. <p>

 -A num <br>
 Sets the size of the kernel cache. Should be a prime number. (default 1000003) <p>

 -T num <br>
 Sets the tolerance parameter. (default 1.0e-3)<p>

 -P num <br>
 Sets the epsilon for round-off error. (default 1.0e-12)<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="toString()"><!-- --></A><H3>
toString</H3>
<PRE>
public java.lang.String <B>toString</B>()</PRE>
<DL>
<DD>Prints out the 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 the classifier as a string</DL>
</DD>
</DL>
<HR>

<A NAME="getExponent()"><!-- --></A><H3>
getExponent</H3>
<PRE>
public double <B>getExponent</B>()</PRE>
<DL>
<DD>Get the value of exponent.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>Value of exponent.</DL>
</DD>
</DL>
<HR>

<A NAME="setExponent(double)"><!-- --></A><H3>
setExponent</H3>
<PRE>
public void <B>setExponent</B>(double&nbsp;v)</PRE>
<DL>
<DD>Set the value of exponent. If linear kernel
 is used, rescaling and lower-order terms are
 turned off.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>v</CODE> - Value to assign to exponent.</DL>
</DD>
</DL>
<HR>

<A NAME="getC()"><!-- --></A><H3>
getC</H3>
<PRE>
public double <B>getC</B>()</PRE>
<DL>
<DD>Get the value of C.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>Value of C.</DL>
</DD>
</DL>
<HR>

<A NAME="setC(double)"><!-- --></A><H3>
setC</H3>
<PRE>
public void <B>setC</B>(double&nbsp;v)</PRE>
<DL>
<DD>Set the value of C.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>v</CODE> - Value to assign to C.</DL>
</DD>
</DL>
<HR>

<A NAME="getToleranceParameter()"><!-- --></A><H3>
getToleranceParameter</H3>
<PRE>
public double <B>getToleranceParameter</B>()</PRE>
<DL>
<DD>Get the value of tolerance parameter.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>Value of tolerance parameter.</DL>
</DD>
</DL>
<HR>

<A NAME="setToleranceParameter(double)"><!-- --></A><H3>
setToleranceParameter</H3>
<PRE>
public void <B>setToleranceParameter</B>(double&nbsp;v)</PRE>
<DL>
<DD>Set the value of tolerance parameter.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>v</CODE> - Value to assign to tolerance parameter.</DL>
</DD>
</DL>
<HR>

<A NAME="getEpsilon()"><!-- --></A><H3>
getEpsilon</H3>
<PRE>
public double <B>getEpsilon</B>()</PRE>
<DL>
<DD>Get the value of epsilon.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>Value of epsilon.</DL>
</DD>
</DL>
<HR>

<A NAME="setEpsilon(double)"><!-- --></A><H3>
setEpsilon</H3>
<PRE>
public void <B>setEpsilon</B>(double&nbsp;v)</PRE>
<DL>
<DD>Set the value of epsilon.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>v</CODE> - Value to assign to epsilon.</DL>
</DD>
</DL>
<HR>

<A NAME="getCacheSize()"><!-- --></A><H3>
getCacheSize</H3>
<PRE>
public int <B>getCacheSize</B>()</PRE>
<DL>
<DD>Get the size of the kernel cache<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>Size of kernel cache.</DL>
</DD>
</DL>
<HR>

<A NAME="setCacheSize(int)"><!-- --></A><H3>
setCacheSize</H3>
<PRE>
public void <B>setCacheSize</B>(int&nbsp;v)</PRE>
<DL>
<DD>Set the value of the kernel cache.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>v</CODE> - Size of kernel cache.</DL>
</DD>
</DL>
<HR>

<A NAME="getNormalizeData()"><!-- --></A><H3>
getNormalizeData</H3>
<PRE>
public boolean <B>getNormalizeData</B>()</PRE>
<DL>
<DD>Check whether data is to be normalized.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>true if data is to be normalized</DL>
</DD>
</DL>
<HR>

<A NAME="setNormalizeData(boolean)"><!-- --></A><H3>
setNormalizeData</H3>
<PRE>
public void <B>setNormalizeData</B>(boolean&nbsp;v)</PRE>
<DL>
<DD>Set whether data is to be normalized.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>v</CODE> - true if data is to be normalized</DL>
</DD>
</DL>
<HR>

<A NAME="getRescaleKernel()"><!-- --></A><H3>
getRescaleKernel</H3>
<PRE>
public boolean <B>getRescaleKernel</B>()
                         throws java.lang.Exception</PRE>
<DL>
<DD>Check whether kernel is being rescaled.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>Value of rescale.</DL>
</DD>
</DL>
<HR>

<A NAME="setRescaleKernel(boolean)"><!-- --></A><H3>
setRescaleKernel</H3>
<PRE>
public void <B>setRescaleKernel</B>(boolean&nbsp;v)
                      throws java.lang.Exception</PRE>
<DL>
<DD>Set whether kernel is to be rescaled. Defaults
 to false if a linear machine is built.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>v</CODE> - Value to assign to rescale.</DL>
</DD>
</DL>
<HR>

<A NAME="getLowerOrderTerms()"><!-- --></A><H3>
getLowerOrderTerms</H3>
<PRE>
public boolean <B>getLowerOrderTerms</B>()</PRE>
<DL>
<DD>Check whether lower-order terms are being used.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>Value of lowerOrder.</DL>
</DD>
</DL>
<HR>

<A NAME="setLowerOrderTerms(boolean)"><!-- --></A><H3>
setLowerOrderTerms</H3>
<PRE>
public void <B>setLowerOrderTerms</B>(boolean&nbsp;v)</PRE>
<DL>
<DD>Set whether lower-order terms are to be used. Defaults
 to false if a linear machine is built.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>v</CODE> - Value to assign to lowerOrder.</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>
</DL>
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