checkclassifier.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

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

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

<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>

 -W classname <br>
 Specify the full class name of a classifier to perform the 
 tests on (required).<p>

 Options after -- are passed to the designated classifier<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 CheckClassifier.<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="doTests()"><!-- --></A><H3>
doTests</H3>
<PRE>
public void <B>doTests</B>()</PRE>
<DL>
<DD>Begin the tests, reporting results to System.out<DD><DL>
</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="setClassifier(weka.classifiers.Classifier)"><!-- --></A><H3>
setClassifier</H3>
<PRE>
public void <B>setClassifier</B>(<A HREF="../../weka/classifiers/Classifier.html">Classifier</A>&nbsp;newClassifier)</PRE>
<DL>
<DD>Set the classifier for boosting.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>newClassifier</CODE> - the Classifier to use.</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>Get the classifier used as the classifier<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the classifier used as the classifier</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>Test method for this class<DD><DL>
</DL>
</DD>
</DL>
<HR>

<A NAME="testsPerClassType(boolean, boolean, boolean)"><!-- --></A><H3>
testsPerClassType</H3>
<PRE>
protected void <B>testsPerClassType</B>(boolean&nbsp;numericClass,
                                 boolean&nbsp;updateable,
                                 boolean&nbsp;weighted)</PRE>
<DL>
<DD>Run a battery of tests for a given class attribute type<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>numericClass</CODE> - true if the class attribute should be numeric<DD><CODE>updateable</CODE> - true if the classifier is updateable<DD><CODE>weighted</CODE> - true if the classifier says it handles weights</DL>
</DD>
</DL>
<HR>

<A NAME="canTakeOptions()"><!-- --></A><H3>
canTakeOptions</H3>
<PRE>
protected boolean <B>canTakeOptions</B>()</PRE>
<DL>
<DD>Checks whether the scheme can take command line options.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>true if the classifier can take options</DL>
</DD>
</DL>
<HR>

<A NAME="distributionClassifier()"><!-- --></A><H3>
distributionClassifier</H3>
<PRE>
protected boolean <B>distributionClassifier</B>()</PRE>
<DL>
<DD>Checks whether the scheme is a distribution classifier.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>true if the classifier produces distributions</DL>
</DD>
</DL>
<HR>

<A NAME="updateableClassifier()"><!-- --></A><H3>
updateableClassifier</H3>
<PRE>
protected boolean <B>updateableClassifier</B>()</PRE>
<DL>
<DD>Checks whether the scheme can build models incrementally.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>true if the classifier can train incrementally</DL>
</DD>
</DL>
<HR>

<A NAME="weightedInstancesHandler()"><!-- --></A><H3>
weightedInstancesHandler</H3>
<PRE>
protected boolean <B>weightedInstancesHandler</B>()</PRE>
<DL>
<DD>Checks whether the scheme says it can handle instance weights.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>true if the classifier handles instance weights</DL>
</DD>
</DL>
<HR>

<A NAME="canPredict(boolean, boolean, boolean)"><!-- --></A><H3>
canPredict</H3>
<PRE>
protected boolean <B>canPredict</B>(boolean&nbsp;nominalPredictor,
                             boolean&nbsp;numericPredictor,
                             boolean&nbsp;numericClass)</PRE>
<DL>
<DD>Checks basic prediction of the scheme, for simple non-troublesome
 datasets.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>nominalPredictor</CODE> - if true use nominal predictor attributes<DD><CODE>numericPredictor</CODE> - if true use numeric predictor attributes<DD><CODE>numericClass</CODE> - if true use a numeric class attribute otherwise a
 nominal class attribute<DT><B>Returns:</B><DD>true if the test was passed</DL>
</DD>
</DL>
<HR>

<A NAME="canHandleNClasses(boolean, boolean, int)"><!-- --></A><H3>
canHandleNClasses</H3>
<PRE>
protected boolean <B>canHandleNClasses</B>(boolean&nbsp;nominalPredictor,
                                    boolean&nbsp;numericPredictor,
                                    int&nbsp;numClasses)</PRE>
<DL>
<DD>Checks whether nominal schemes can handle more than two classes.
 If a scheme is only designed for two-class problems it should
 throw an appropriate exception for multi-class problems.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>nominalPredictor</CODE> - if true use nominal predictor attributes<DD><CODE>numericPredictor</CODE> - if true use numeric predictor attributes<DD><CODE>numClasses</CODE> - the number of classes to test<DT><B>Returns:</B><DD>true if the test was passed</DL>
</DD>
</DL>
<HR>

<A NAME="canHandleZeroTraining(boolean, boolean, boolean)"><!-- --></A><H3>
canHandleZeroTraining</H3>
<PRE>
protected boolean <B>canHandleZeroTraining</B>(boolean&nbsp;nominalPredictor,
                                        boolean&nbsp;numericPredictor,
                                        boolean&nbsp;numericClass)</PRE>
<DL>
<DD>Checks whether the scheme can handle zero training instances.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>nominalPredictor</CODE> - if true use nominal predictor attributes<DD><CODE>numericPredictor</CODE> - if true use numeric predictor attributes<DD><CODE>numericClass</CODE> - if true use a numeric class attribute otherwise a
 nominal class attribute<DT><B>Returns:</B><DD>true if the test was passed</DL>
</DD>
</DL>
<HR>

<A NAME="correctBuildInitialisation(boolean, boolean, boolean)"><!-- --></A><H3>
correctBuildInitialisation</H3>
<PRE>
protected boolean <B>correctBuildInitialisation</B>(boolean&nbsp;nominalPredictor,
                                             boolean&nbsp;numericPredictor,
                                             boolean&nbsp;numericClass)</PRE>
<DL>
<DD>Checks whether the scheme correctly initialises models when 
 buildClassifier is called. This test calls buildClassifier with
 one training dataset and records performance on a test set. 
 buildClassifier is then called on a training set with different
 structure, and then again with the original training set. The
 performance on the test set is compared with the original results
 and any performance difference noted as incorrect build initialisation.<DD><DL>
</DL>