bagging.html

weka是机器学习和数据挖掘领域最有影响力的开源项目之一

</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.
<P>
<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.
<P>
<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="calcOutOfBagTipText()"><!-- --></A><H3>
calcOutOfBagTipText</H3>
<PRE>
public java.lang.String <B>calcOutOfBagTipText</B>()</PRE>
<DL>
<DD>Returns the tip text for this property
<P>
<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="setCalcOutOfBag(boolean)"><!-- --></A><H3>
setCalcOutOfBag</H3>
<PRE>
public void <B>setCalcOutOfBag</B>(boolean&nbsp;calcOutOfBag)</PRE>
<DL>
<DD>Set whether the out of bag error is calculated.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>calcOutOfBag</CODE> - whether to calculate the out of bag error</DL>
</DD>
</DL>
<HR>

<A NAME="getCalcOutOfBag()"><!-- --></A><H3>
getCalcOutOfBag</H3>
<PRE>
public boolean <B>getCalcOutOfBag</B>()</PRE>
<DL>
<DD>Get whether the out of bag error is calculated.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>whether the out of bag error is calculated</DL>
</DD>
</DL>
<HR>

<A NAME="measureOutOfBagError()"><!-- --></A><H3>
measureOutOfBagError</H3>
<PRE>
public double <B>measureOutOfBagError</B>()</PRE>
<DL>
<DD>Gets the out of bag error that was calculated as the classifier
 was built.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the out of bag error</DL>
</DD>
</DL>
<HR>

<A NAME="enumerateMeasures()"><!-- --></A><H3>
enumerateMeasures</H3>
<PRE>
public java.util.Enumeration <B>enumerateMeasures</B>()</PRE>
<DL>
<DD>Returns an enumeration of the additional measure names.
<P>
<DD><DL>
<DT><B>Specified by:</B><DD><CODE><A HREF="../../../weka/core/AdditionalMeasureProducer.html#enumerateMeasures()">enumerateMeasures</A></CODE> in interface <CODE><A HREF="../../../weka/core/AdditionalMeasureProducer.html" title="interface in weka.core">AdditionalMeasureProducer</A></CODE></DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>an enumeration of the measure names</DL>
</DD>
</DL>
<HR>

<A NAME="getMeasure(java.lang.String)"><!-- --></A><H3>
getMeasure</H3>
<PRE>
public double <B>getMeasure</B>(java.lang.String&nbsp;additionalMeasureName)</PRE>
<DL>
<DD>Returns the value of the named measure.
<P>
<DD><DL>
<DT><B>Specified by:</B><DD><CODE><A HREF="../../../weka/core/AdditionalMeasureProducer.html#getMeasure(java.lang.String)">getMeasure</A></CODE> in interface <CODE><A HREF="../../../weka/core/AdditionalMeasureProducer.html" title="interface in weka.core">AdditionalMeasureProducer</A></CODE></DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>additionalMeasureName</CODE> - the name of the measure to query for its value
<DT><B>Returns:</B><DD>the value of the named measure
<DT><B>Throws:</B>
<DD><CODE>java.lang.IllegalArgumentException</CODE> - if the named measure is not supported</DL>
</DD>
</DL>
<HR>

<A NAME="resampleWithWeights(weka.core.Instances, java.util.Random, boolean[])"><!-- --></A><H3>
resampleWithWeights</H3>
<PRE>
public final <A HREF="../../../weka/core/Instances.html" title="class in weka.core">Instances</A> <B>resampleWithWeights</B>(<A HREF="../../../weka/core/Instances.html" title="class in weka.core">Instances</A>&nbsp;data,
                                           java.util.Random&nbsp;random,
                                           boolean[]&nbsp;sampled)</PRE>
<DL>
<DD>Creates a new dataset of the same size using random sampling
 with replacement according to the given weight vector. The
 weights of the instances in the new dataset are set to one.
 The length of the weight vector has to be the same as the
 number of instances in the dataset, and all weights have to
 be positive.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>data</CODE> - the data to be sampled from<DD><CODE>random</CODE> - a random number generator<DD><CODE>sampled</CODE> - indicating which instance has been sampled
<DT><B>Returns:</B><DD>the new dataset
<DT><B>Throws:</B>
<DD><CODE>java.lang.IllegalArgumentException</CODE> - if the weights array is of the wrong
 length or contains negative weights.</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" title="class in weka.core">Instances</A>&nbsp;data)
                     throws java.lang.Exception</PRE>
<DL>
<DD>Bagging method.
<P>
<DD><DL>
<DT><B>Overrides:</B><DD><CODE><A HREF="../../../weka/classifiers/IteratedSingleClassifierEnhancer.html#buildClassifier(weka.core.Instances)">buildClassifier</A></CODE> in class <CODE><A HREF="../../../weka/classifiers/IteratedSingleClassifierEnhancer.html" title="class in weka.classifiers">IteratedSingleClassifierEnhancer</A></CODE></DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>data</CODE> - the training data to be used for generating the
 bagged 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="distributionForInstance(weka.core.Instance)"><!-- --></A><H3>
distributionForInstance</H3>
<PRE>
public double[] <B>distributionForInstance</B>(<A HREF="../../../weka/core/Instance.html" title="class in weka.core">Instance</A>&nbsp;instance)
                                 throws java.lang.Exception</PRE>
<DL>
<DD>Calculates the class membership probabilities for the given test
 instance.
<P>
<DD><DL>
<DT><B>Overrides:</B><DD><CODE><A HREF="../../../weka/classifiers/Classifier.html#distributionForInstance(weka.core.Instance)">distributionForInstance</A></CODE> in class <CODE><A HREF="../../../weka/classifiers/Classifier.html" title="class in weka.classifiers">Classifier</A></CODE></DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>instance</CODE> - the instance to be classified
<DT><B>Returns:</B><DD>preedicted class probability distribution
<DT><B>Throws:</B>
<DD><CODE>java.lang.Exception</CODE> - if distribution can't be computed successfully</DL>
</DD>
</DL>
<HR>

<A NAME="toString()"><!-- --></A><H3>
toString</H3>
<PRE>
public java.lang.String <B>toString</B>()</PRE>
<DL>
<DD>Returns description of the bagged classifier.
<P>
<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>description of the bagged classifier as a string</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.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>argv</CODE> - the options</DL>
</DD>
</DL>
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