bvdecompose.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

</DD>
<DD><DL>
<DT><B>Returns:</B><DD>number of instances in the training pool.</DL>
</DD>
</DL>
<HR>

<A NAME="setTrainPoolSize(int)"><!-- --></A><H3>
setTrainPoolSize</H3>
<PRE>
public void <B>setTrainPoolSize</B>(int&nbsp;numTrain)</PRE>
<DL>
<DD>Set the number of instances in the training pool.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>numTrain</CODE> - number of instances in the training pool.</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 classifiers being analysed<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>Gets the name of the classifier being analysed<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the classifier being analysed.</DL>
</DD>
</DL>
<HR>

<A NAME="setDebug(boolean)"><!-- --></A><H3>
setDebug</H3>
<PRE>
public void <B>setDebug</B>(boolean&nbsp;debug)</PRE>
<DL>
<DD>Sets 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>Gets 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="setSeed(int)"><!-- --></A><H3>
setSeed</H3>
<PRE>
public void <B>setSeed</B>(int&nbsp;seed)</PRE>
<DL>
<DD>Sets the random number seed<DD><DL>
</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="setTrainIterations(int)"><!-- --></A><H3>
setTrainIterations</H3>
<PRE>
public void <B>setTrainIterations</B>(int&nbsp;trainIterations)</PRE>
<DL>
<DD>Sets the maximum number of boost iterations<DD><DL>
</DL>
</DD>
</DL>
<HR>

<A NAME="getTrainIterations()"><!-- --></A><H3>
getTrainIterations</H3>
<PRE>
public int <B>getTrainIterations</B>()</PRE>
<DL>
<DD>Gets the maximum number of boost iterations<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the maximum number of boost iterations</DL>
</DD>
</DL>
<HR>

<A NAME="setDataFileName(java.lang.String)"><!-- --></A><H3>
setDataFileName</H3>
<PRE>
public void <B>setDataFileName</B>(java.lang.String&nbsp;dataFileName)</PRE>
<DL>
<DD>Sets the maximum number of boost iterations<DD><DL>
</DL>
</DD>
</DL>
<HR>

<A NAME="getDataFileName()"><!-- --></A><H3>
getDataFileName</H3>
<PRE>
public java.lang.String <B>getDataFileName</B>()</PRE>
<DL>
<DD>Get the name of the data file used for the decomposition<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the name of the data file</DL>
</DD>
</DL>
<HR>

<A NAME="getClassIndex()"><!-- --></A><H3>
getClassIndex</H3>
<PRE>
public int <B>getClassIndex</B>()</PRE>
<DL>
<DD>Get the index (starting from 1) of the attribute used as the class.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the index of the class attribute</DL>
</DD>
</DL>
<HR>

<A NAME="setClassIndex(int)"><!-- --></A><H3>
setClassIndex</H3>
<PRE>
public void <B>setClassIndex</B>(int&nbsp;classIndex)</PRE>
<DL>
<DD>Sets index of attribute to discretize on<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>index</CODE> - the index (starting from 1) of the class attribute</DL>
</DD>
</DL>
<HR>

<A NAME="getBias()"><!-- --></A><H3>
getBias</H3>
<PRE>
public double <B>getBias</B>()</PRE>
<DL>
<DD>Get the calculated bias squared<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the bias squared</DL>
</DD>
</DL>
<HR>

<A NAME="getVariance()"><!-- --></A><H3>
getVariance</H3>
<PRE>
public double <B>getVariance</B>()</PRE>
<DL>
<DD>Get the calculated variance<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the variance</DL>
</DD>
</DL>
<HR>

<A NAME="getSigma()"><!-- --></A><H3>
getSigma</H3>
<PRE>
public double <B>getSigma</B>()</PRE>
<DL>
<DD>Get the calculated sigma squared<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the sigma squared</DL>
</DD>
</DL>
<HR>

<A NAME="getError()"><!-- --></A><H3>
getError</H3>
<PRE>
public double <B>getError</B>()</PRE>
<DL>
<DD>Get the calculated error rate<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the error rate</DL>
</DD>
</DL>
<HR>

<A NAME="decompose()"><!-- --></A><H3>
decompose</H3>
<PRE>
public void <B>decompose</B>()
               throws java.lang.Exception</PRE>
<DL>
<DD>Carry out the bias-variance decomposition<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if the decomposition couldn't be carried out</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 bias-variance decomposition results.<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>the bias-variance decomposition results 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;args)</PRE>
<DL>
<DD>Test method for this class<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>args</CODE> - the command line arguments</DL>
</DD>
</DL>
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