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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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</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/AdditiveRegression.html#getOptions()">getOptions</A></B>()</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Gets the current settings of the Classifier.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>&nbsp;double</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/AdditiveRegression.html#getShrinkage()">getShrinkage</A></B>()</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Get the shrinkage rate.</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/AdditiveRegression.html#globalInfo()">globalInfo</A></B>()</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Returns a string describing this attribute evaluator</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/AdditiveRegression.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/AdditiveRegression.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;java.lang.String</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/AdditiveRegression.html#maxModelsTipText()">maxModelsTipText</A></B>()</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Returns the tip text for this property</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>&nbsp;double</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/AdditiveRegression.html#measureNumIterations()">measureNumIterations</A></B>()</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;return the number of iterations (base classifiers) completed</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/AdditiveRegression.html#setClassifier(weka.classifiers.Classifier)">setClassifier</A></B>(<A HREF="../../weka/classifiers/Classifier.html">Classifier</A>&nbsp;classifier)</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Sets the 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/AdditiveRegression.html#setDebug(boolean)">setDebug</A></B>(boolean&nbsp;d)</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Set whether debugging output is produced.</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/AdditiveRegression.html#setMaxModels(int)">setMaxModels</A></B>(int&nbsp;maxM)</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Set the maximum number of models to generate</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/AdditiveRegression.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;void</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/AdditiveRegression.html#setShrinkage(double)">setShrinkage</A></B>(double&nbsp;l)</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Set the shrinkage parameter</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/AdditiveRegression.html#shrinkageTipText()">shrinkageTipText</A></B>()</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Returns the tip text for this property</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/AdditiveRegression.html#toString()">toString</A></B>()</CODE><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Returns textual description of the classifier.</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_Classifier"><!-- --></A><H3>m_Classifier</H3><PRE>protected <A HREF="../../weka/classifiers/Classifier.html">Classifier</A> <B>m_Classifier</B></PRE><DL><DD>Base classifier.</DL><HR><A NAME="m_shrinkage"><!-- --></A><H3>m_shrinkage</H3><PRE>protected double <B>m_shrinkage</B></PRE><DL><DD>Shrinkage (Learning rate). Default = no shrinkage.</DL><HR><A NAME="m_maxModels"><!-- --></A><H3>m_maxModels</H3><PRE>protected int <B>m_maxModels</B></PRE><DL><DD>Maximum number of models to produce. -1 indicates keep going until the error threshold is met.</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="AdditiveRegression()"><!-- --></A><H3>AdditiveRegression</H3><PRE>public <B>AdditiveRegression</B>()</PRE><DL><DD>Default constructor specifying DecisionStump as the classifier</DL><HR><A NAME="AdditiveRegression(weka.classifiers.Classifier)"><!-- --></A><H3>AdditiveRegression</H3><PRE>public <B>AdditiveRegression</B>(<A HREF="../../weka/classifiers/Classifier.html">Classifier</A>&nbsp;classifier)</PRE><DL><DD>Constructor which takes base classifier as argument.<DD><DL><DT><B>Parameters:</B><DD><CODE>classifier</CODE> - the base classifier to use</DL></DD></DL><!-- ============ 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="globalInfo()"><!-- --></A><H3>globalInfo</H3><PRE>public java.lang.String <B>globalInfo</B>()</PRE><DL><DD>Returns a string describing this attribute evaluator<DD><DL></DL></DD><DD><DL><DT><B>Returns:</B><DD>a description of the evaluator suitable for displaying in the explorer/experimenter gui</DL></DD></DL><HR><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> -B classifierstring <br> Classifierstring should contain the full class name of a classifier followed by options to the classifier. (required).<p> -S shrinkage rate <br> Smaller values help prevent overfitting and have a smoothing effect  (but increase learning time). (default = 1.0, ie. no shrinkage). <p> -D <br> Debugging output. <p> -M max models <br> Set the maximum number of models to generate. Values <= 0 indicate  no maximum, ie keep going until the reduction in error threshold is  reached. (default = -1). <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="debugTipText()"><!-- --></A><H3>debugTipText</H3><PRE>public java.lang.String <B>debugTipText</B>()</PRE><DL><DD>Returns the tip text for this property<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="setDebug(boolean)"><!-- --></A><H3>setDebug</H3><PRE>public void <B>setDebug</B>(boolean&nbsp;d)</PRE><DL><DD>Set whether debugging output is produced.<DD><DL></DL></DD><DD><DL><DT><B>Parameters:</B><DD><CODE>d</CODE> - true if debugging output is to be produced</DL></DD>

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