lwr.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

protected double[] <B>m_Min</B></PRE>
<DL>
<DD>The minimum values for numeric attributes.</DL>
<HR>

<A NAME="m_Max"><!-- --></A><H3>
m_Max</H3>
<PRE>
protected double[] <B>m_Max</B></PRE>
<DL>
<DD>The maximum values for numeric attributes.</DL>
<HR>

<A NAME="m_Debug"><!-- --></A><H3>
m_Debug</H3>
<PRE>
protected boolean <B>m_Debug</B></PRE>
<DL>
<DD>True if debugging output should be printed</DL>
<HR>

<A NAME="m_kNN"><!-- --></A><H3>
m_kNN</H3>
<PRE>
protected int <B>m_kNN</B></PRE>
<DL>
<DD>The number of neighbours used to select the kernel bandwidth</DL>
<HR>

<A NAME="m_WeightKernel"><!-- --></A><H3>
m_WeightKernel</H3>
<PRE>
protected int <B>m_WeightKernel</B></PRE>
<DL>
<DD>The weighting kernel method currently selected</DL>
<HR>

<A NAME="m_UseAllK"><!-- --></A><H3>
m_UseAllK</H3>
<PRE>
protected boolean <B>m_UseAllK</B></PRE>
<DL>
<DD>True if m_kNN should be set to all instances</DL>
<HR>

<A NAME="LINEAR"><!-- --></A><H3>
LINEAR</H3>
<PRE>
protected static final int <B>LINEAR</B></PRE>
<DL>
</DL>
<HR>

<A NAME="INVERSE"><!-- --></A><H3>
INVERSE</H3>
<PRE>
protected static final int <B>INVERSE</B></PRE>
<DL>
</DL>
<HR>

<A NAME="GAUSS"><!-- --></A><H3>
GAUSS</H3>
<PRE>
protected static final int <B>GAUSS</B></PRE>
<DL>
</DL>

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<A NAME="LWR()"><!-- --></A><H3>
LWR</H3>
<PRE>
public <B>LWR</B>()</PRE>
<DL>
</DL>

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<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>
 Produce debugging output. <p>

 -K num <br>
 Set the number of neighbours used for setting kernel bandwidth.
 (default all) <p>

 -W num <br>
 Set the weighting kernel shape to use. 1 = Inverse, 2 = Gaussian.
 (default 0 = Linear) <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="setDebug(boolean)"><!-- --></A><H3>
setDebug</H3>
<PRE>
public void <B>setDebug</B>(boolean&nbsp;debug)</PRE>
<DL>
<DD>Sets whether debugging output should be produced<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>debug</CODE> - true if debugging output should be printed</DL>
</DD>
</DL>
<HR>

<A NAME="getDebug()"><!-- --></A><H3>
getDebug</H3>
<PRE>
public boolean <B>getDebug</B>()</PRE>
<DL>
<DD>SGts whether debugging output should be produced<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>true if debugging output should be printed</DL>
</DD>
</DL>
<HR>

<A NAME="setKNN(int)"><!-- --></A><H3>
setKNN</H3>
<PRE>
public void <B>setKNN</B>(int&nbsp;knn)</PRE>
<DL>
<DD>Sets the number of neighbours used for kernel bandwidth setting.
 The bandwidth is taken as the distance to the kth neighbour.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>knn</CODE> - the number of neighbours included inside the kernel
 bandwidth, or 0 to specify using all neighbors.</DL>
</DD>
</DL>
<HR>

<A NAME="getKNN()"><!-- --></A><H3>
getKNN</H3>
<PRE>
public int <B>getKNN</B>()</PRE>
<DL>
<DD>Gets the number of neighbours used for kernel bandwidth setting.
 The bandwidth is taken as the distance to the kth neighbour.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the number of neighbours included inside the kernel
 bandwidth, or 0 for all neighbours</DL>
</DD>
</DL>
<HR>

<A NAME="setWeightingKernel(int)"><!-- --></A><H3>
setWeightingKernel</H3>
<PRE>
public void <B>setWeightingKernel</B>(int&nbsp;kernel)</PRE>
<DL>
<DD>Sets the kernel weighting method to use. Must be one of LINEAR,
 INVERSE, or GAUSS, other values are ignored.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>kernel</CODE> - the new kernel method to use. Must be one of LINEAR,
 INVERSE, or GAUSS</DL>
</DD>
</DL>
<HR>

<A NAME="getWeightingKernel()"><!-- --></A><H3>
getWeightingKernel</H3>
<PRE>
public int <B>getWeightingKernel</B>()</PRE>
<DL>
<DD>Gets the kernel weighting method to use.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>the new kernel method to use. Will be one of LINEAR,
 INVERSE, or GAUSS</DL>
</DD>
</DL>
<HR>

<A NAME="getAttributeMin(int)"><!-- --></A><H3>
getAttributeMin</H3>
<PRE>
protected double <B>getAttributeMin</B>(int&nbsp;index)</PRE>
<DL>
<DD>Gets an attributes minimum observed value<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>index</CODE> - the index of the attribute<DT><B>Returns:</B><DD>the minimum observed value</DL>
</DD>
</DL>
<HR>

<A NAME="getAttributeMax(int)"><!-- --></A><H3>
getAttributeMax</H3>
<PRE>
protected double <B>getAttributeMax</B>(int&nbsp;index)</PRE>
<DL>
<DD>Gets an attributes maximum observed value<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>index</CODE> - the index of the attribute<DT><B>Returns:</B><DD>the maximum observed value</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="updateClassifier(weka.core.Instance)"><!-- --></A><H3>
updateClassifier</H3>
<PRE>
public void <B>updateClassifier</B>(<A HREF="../../weka/core/Instance.html">Instance</A>&nbsp;instance)
                      throws java.lang.Exception</PRE>
<DL>
<DD>Adds the supplied instance to the training set<DD><DL>
<DT><B>Specified by: </B><DD><CODE><A HREF="../../weka/classifiers/UpdateableClassifier.html#updateClassifier(weka.core.Instance)">updateClassifier</A></CODE> in interface <CODE><A HREF="../../weka/classifiers/UpdateableClassifier.html">UpdateableClassifier</A></CODE></DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>instance</CODE> - the instance to add<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if instance could not be incorporated
 successfully</DL>
</DD>
</DL>
<HR>

<A NAME="classifyInstance(weka.core.Instance)"><!-- --></A><H3>
classifyInstance</H3>
<PRE>
public double <B>classifyInstance</B>(<A HREF="../../weka/core/Instance.html">Instance</A>&nbsp;instance)
                        throws java.lang.Exception</PRE>
<DL>
<DD>Predicts the class value for the given test instance.<DD><DL>
<DT><B>Overrides:</B><DD><CODE><A HREF="../../weka/classifiers/Classifier.html#classifyInstance(weka.core.Instance)">classifyInstance</A></CODE> in class <CODE><A HREF="../../weka/classifiers/Classifier.html">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>the predicted class value<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if an error occurred during the prediction</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="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>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>argv</CODE> - the options</DL>
</DD>
</DL>
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