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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
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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Calculates the class membership probabilities for the given test instance.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>&nbsp;boolean</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/kstar/KStar.html#getEntropicAutoBlend()">getEntropicAutoBlend</A></B>()</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Get whether entropic blending being used</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>&nbsp;int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/kstar/KStar.html#getGlobalBlend()">getGlobalBlend</A></B>()</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Get the value of the global blend parameter</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>&nbsp;<A HREF="../../../weka/core/SelectedTag.html">SelectedTag</A></CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/kstar/KStar.html#getMissingMode()">getMissingMode</A></B>()</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Gets the method to use for handling missing values.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>&nbsp;java.lang.String[]</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/kstar/KStar.html#getOptions()">getOptions</A></B>()</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Gets the current settings of K*.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>&nbsp;java.util.Enumeration</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/kstar/KStar.html#listOptions()">listOptions</A></B>()</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Returns an enumeration describing the available options</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>static&nbsp;void</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/kstar/KStar.html#main(java.lang.String[])">main</A></B>(java.lang.String[]&nbsp;argv)</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Main method for testing this class.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>&nbsp;void</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/kstar/KStar.html#setEntropicAutoBlend(boolean)">setEntropicAutoBlend</A></B>(boolean&nbsp;e)</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Set whether entropic blending is to be used.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>&nbsp;void</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/kstar/KStar.html#setGlobalBlend(int)">setGlobalBlend</A></B>(int&nbsp;b)</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Set the global blend parameter</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>&nbsp;void</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/kstar/KStar.html#setMissingMode(weka.core.SelectedTag)">setMissingMode</A></B>(<A HREF="../../../weka/core/SelectedTag.html">SelectedTag</A>&nbsp;newMode)</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Sets the method to use for handling missing values.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>&nbsp;void</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/kstar/KStar.html#setOptions(java.lang.String[])">setOptions</A></B>(java.lang.String[]&nbsp;options)</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Parses a given list of options.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>&nbsp;java.lang.String</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/kstar/KStar.html#toString()">toString</A></B>()</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Returns a description of this classifier.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>&nbsp;void</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/kstar/KStar.html#updateClassifier(weka.core.Instance)">updateClassifier</A></B>(<A HREF="../../../weka/core/Instance.html">Instance</A>&nbsp;instance)</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Adds the supplied instance to the training set</TD></TR></TABLE>&nbsp;<A NAME="methods_inherited_from_class_weka.classifiers.DistributionClassifier"><!-- --></A><TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%"><TR BGCOLOR="#EEEEFF" CLASS="TableSubHeadingColor"><TD><B>Methods inherited from class weka.classifiers.<A HREF="../../../weka/classifiers/DistributionClassifier.html">DistributionClassifier</A></B></TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><CODE><A HREF="../../../weka/classifiers/DistributionClassifier.html#classifyInstance(weka.core.Instance)">classifyInstance</A></CODE></TD></TR></TABLE>&nbsp;<A NAME="methods_inherited_from_class_weka.classifiers.Classifier"><!-- --></A><TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%"><TR BGCOLOR="#EEEEFF" CLASS="TableSubHeadingColor"><TD><B>Methods inherited from class weka.classifiers.<A HREF="../../../weka/classifiers/Classifier.html">Classifier</A></B></TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><CODE><A HREF="../../../weka/classifiers/Classifier.html#forName(java.lang.String, java.lang.String[])">forName</A>, <A HREF="../../../weka/classifiers/Classifier.html#makeCopies(weka.classifiers.Classifier, int)">makeCopies</A></CODE></TD></TR></TABLE>&nbsp;<A NAME="methods_inherited_from_class_java.lang.Object"><!-- --></A><TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%"><TR BGCOLOR="#EEEEFF" CLASS="TableSubHeadingColor"><TD><B>Methods inherited from class java.lang.Object</B></TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><CODE>clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait</CODE></TD></TR></TABLE>&nbsp;<P><!-- ============ FIELD DETAIL =========== --><A NAME="field_detail"><!-- --></A><TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%"><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TD COLSPAN=1><FONT SIZE="+2"><B>Field Detail</B></FONT></TD></TR></TABLE><A NAME="m_Train"><!-- --></A><H3>m_Train</H3><PRE>protected <A HREF="../../../weka/core/Instances.html">Instances</A> <B>m_Train</B></PRE><DL><DD>The training instances used for classification.</DL><HR><A NAME="m_NumInstances"><!-- --></A><H3>m_NumInstances</H3><PRE>protected int <B>m_NumInstances</B></PRE><DL><DD>The number of instances in the dataset</DL><HR><A NAME="m_NumClasses"><!-- --></A><H3>m_NumClasses</H3><PRE>protected int <B>m_NumClasses</B></PRE><DL><DD>The number of class values</DL><HR><A NAME="m_NumAttributes"><!-- --></A><H3>m_NumAttributes</H3><PRE>protected int <B>m_NumAttributes</B></PRE><DL><DD>The number of attributes</DL><HR><A NAME="m_ClassType"><!-- --></A><H3>m_ClassType</H3><PRE>protected int <B>m_ClassType</B></PRE><DL><DD>The class attribute type</DL><HR><A NAME="m_RandClassCols"><!-- --></A><H3>m_RandClassCols</H3><PRE>protected int[][] <B>m_RandClassCols</B></PRE><DL><DD>Table of random class value colomns</DL><HR><A NAME="m_ComputeRandomCols"><!-- --></A><H3>m_ComputeRandomCols</H3><PRE>protected int <B>m_ComputeRandomCols</B></PRE><DL><DD>Flag turning on and off the computation of random class colomns</DL><HR><A NAME="m_InitFlag"><!-- --></A><H3>m_InitFlag</H3><PRE>protected int <B>m_InitFlag</B></PRE><DL><DD>Flag turning on and off the initialisation of config variables</DL><HR><A NAME="m_Cache"><!-- --></A><H3>m_Cache</H3><PRE>protected <A HREF="../../../weka/classifiers/kstar/KStarCache.html">KStarCache</A>[] <B>m_Cache</B></PRE><DL><DD>A custom data structure for caching distinct attribute values and their scale factor or stop parameter.</DL><HR><A NAME="m_MissingMode"><!-- --></A><H3>m_MissingMode</H3><PRE>protected int <B>m_MissingMode</B></PRE><DL><DD>missing value treatment</DL><HR><A NAME="m_BlendMethod"><!-- --></A><H3>m_BlendMethod</H3><PRE>protected int <B>m_BlendMethod</B></PRE><DL><DD>0 = use specified blend, 1 = entropic blend setting</DL><HR><A NAME="m_GlobalBlend"><!-- --></A><H3>m_GlobalBlend</H3><PRE>protected int <B>m_GlobalBlend</B></PRE><DL><DD>default sphere of influence blend setting</DL><HR><A NAME="TAGS_MISSING"><!-- --></A><H3>TAGS_MISSING</H3><PRE>public static final <A HREF="../../../weka/core/Tag.html">Tag</A>[] <B>TAGS_MISSING</B></PRE><DL><DD>Define possible missing value handling methods</DL><!-- ========= CONSTRUCTOR DETAIL ======== --><A NAME="constructor_detail"><!-- --></A><TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%"><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TD COLSPAN=1><FONT SIZE="+2"><B>Constructor Detail</B></FONT></TD></TR></TABLE><A NAME="KStar()"><!-- --></A><H3>KStar</H3><PRE>public <B>KStar</B>()</PRE><DL></DL>

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