📄 adtree.html
字号:
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0 Frameset//EN""http://www.w3.org/TR/REC-html40/frameset.dtd"><!--NewPage--><HTML><HEAD><!-- Generated by javadoc on Wed Sep 04 10:31:49 CDT 2002 --><TITLE>: Class ADTree</TITLE><LINK REL ="stylesheet" TYPE="text/css" HREF="../../../stylesheet.css" TITLE="Style"></HEAD><BODY BGCOLOR="white"><!-- ========== START OF NAVBAR ========== --><A NAME="navbar_top"><!-- --></A><TABLE BORDER="0" WIDTH="100%" CELLPADDING="1" CELLSPACING="0"><TR><TD COLSPAN=2 BGCOLOR="#EEEEFF" CLASS="NavBarCell1"><A NAME="navbar_top_firstrow"><!-- --></A><TABLE BORDER="0" CELLPADDING="0" CELLSPACING="3"> <TR ALIGN="center" VALIGN="top"> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="../../../overview-summary.html"><FONT CLASS="NavBarFont1"><B>Overview</B></FONT></A> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="package-summary.html"><FONT CLASS="NavBarFont1"><B>Package</B></FONT></A> </TD> <TD BGCOLOR="#FFFFFF" CLASS="NavBarCell1Rev"> <FONT CLASS="NavBarFont1Rev"><B>Class</B></FONT> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="package-tree.html"><FONT CLASS="NavBarFont1"><B>Tree</B></FONT></A> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="../../../deprecated-list.html"><FONT CLASS="NavBarFont1"><B>Deprecated</B></FONT></A> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="../../../index-all.html"><FONT CLASS="NavBarFont1"><B>Index</B></FONT></A> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="../../../help-doc.html"><FONT CLASS="NavBarFont1"><B>Help</B></FONT></A> </TD> </TR></TABLE></TD><TD ALIGN="right" VALIGN="top" ROWSPAN=3><EM></EM></TD></TR><TR><TD BGCOLOR="white" CLASS="NavBarCell2"><FONT SIZE="-2"> PREV CLASS <A HREF="../../../weka/classifiers/adtree/PredictionNode.html"><B>NEXT CLASS</B></A></FONT></TD><TD BGCOLOR="white" CLASS="NavBarCell2"><FONT SIZE="-2"> <A HREF="../../../index.html" TARGET="_top"><B>FRAMES</B></A> <A HREF="ADTree.html" TARGET="_top"><B>NO FRAMES</B></A></FONT></TD></TR><TR><TD VALIGN="top" CLASS="NavBarCell3"><FONT SIZE="-2"> SUMMARY: INNER | <A HREF="#field_summary">FIELD</A> | <A HREF="#constructor_summary">CONSTR</A> | <A HREF="#method_summary">METHOD</A></FONT></TD><TD VALIGN="top" CLASS="NavBarCell3"><FONT SIZE="-2">DETAIL: <A HREF="#field_detail">FIELD</A> | <A HREF="#constructor_detail">CONSTR</A> | <A HREF="#method_detail">METHOD</A></FONT></TD></TR></TABLE><!-- =========== END OF NAVBAR =========== --><HR><!-- ======== START OF CLASS DATA ======== --><H2><FONT SIZE="-1">weka.classifiers.adtree</FONT><BR>Class ADTree</H2><PRE>java.lang.Object | +--<A HREF="../../../weka/classifiers/Classifier.html">weka.classifiers.Classifier</A> | +--<A HREF="../../../weka/classifiers/DistributionClassifier.html">weka.classifiers.DistributionClassifier</A> | +--<B>weka.classifiers.adtree.ADTree</B></PRE><DL><DT><B>All Implemented Interfaces:</B> <DD><A HREF="../../../weka/core/AdditionalMeasureProducer.html">AdditionalMeasureProducer</A>, java.lang.Cloneable, <A HREF="../../../weka/core/Drawable.html">Drawable</A>, <A HREF="../../../weka/classifiers/IterativeClassifier.html">IterativeClassifier</A>, <A HREF="../../../weka/core/OptionHandler.html">OptionHandler</A>, java.io.Serializable, <A HREF="../../../weka/core/WeightedInstancesHandler.html">WeightedInstancesHandler</A></DD></DL><HR><DL><DT>public class <B>ADTree</B><DT>extends <A HREF="../../../weka/classifiers/DistributionClassifier.html">DistributionClassifier</A><DT>implements <A HREF="../../../weka/core/OptionHandler.html">OptionHandler</A>, <A HREF="../../../weka/core/Drawable.html">Drawable</A>, <A HREF="../../../weka/core/AdditionalMeasureProducer.html">AdditionalMeasureProducer</A>, <A HREF="../../../weka/core/WeightedInstancesHandler.html">WeightedInstancesHandler</A>, <A HREF="../../../weka/classifiers/IterativeClassifier.html">IterativeClassifier</A></DL><P>Class for generating an alternating decision tree. The basic algorithm is based on:<p> Freund, Y., Mason, L.: The alternating decision tree learning algorithm. Proceeding of the Sixteenth International Conference on Machine Learning, Bled, Slovenia, (1999) 124-133.</p> This version currently only supports two-class problems. The number of boosting iterations needs to be manually tuned to suit the dataset and the desired complexity/accuracy tradeoff. Induction of the trees has been optimized, and heuristic search methods have been introduced to speed learning.<p> Valid options are: <p> -B num <br> Set the number of boosting iterations (default 10) <p> -E num <br> Set the nodes to expand: -3(all), -2(weight), -1(z_pure), >=0 seed for random walk (default -3) <p> -D <br> Save the instance data with the model <p><P><DL><DT><B>See Also: </B><DD><A HREF="../../../serialized-form.html#weka.classifiers.adtree.ADTree">Serialized Form</A></DL><HR><P><!-- ======== INNER CLASS SUMMARY ======== --><!-- =========== FIELD SUMMARY =========== --><A NAME="field_summary"><!-- --></A><TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%"><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TD COLSPAN=2><FONT SIZE="+2"><B>Field Summary</B></FONT></TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_boostingIterations">m_boostingIterations</A></B></CODE><BR> Option - the number of boosting iterations o perform</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_examplesCounted">m_examplesCounted</A></B></CODE><BR> Statistics - the number of instances processed during search</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_lastAddedSplitNum">m_lastAddedSplitNum</A></B></CODE><BR> The number of the last splitter added to the tree</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected <A HREF="../../../weka/classifiers/adtree/ReferenceInstances.html">ReferenceInstances</A></CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_negTrainInstances">m_negTrainInstances</A></B></CODE><BR> The training instances with negative class - referencing the training dataset</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_nodesExpanded">m_nodesExpanded</A></B></CODE><BR> Statistics - the number of prediction nodes investigated during search</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected int[]</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_nominalAttIndices">m_nominalAttIndices</A></B></CODE><BR> An array containing the inidices to the nominal attributes in the data</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected int[]</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_numericAttIndices">m_numericAttIndices</A></B></CODE><BR> An array containing the inidices to the numeric attributes in the data</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected <A HREF="../../../weka/classifiers/adtree/ReferenceInstances.html">ReferenceInstances</A></CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_posTrainInstances">m_posTrainInstances</A></B></CODE><BR> The training instances with positive class - referencing the training dataset</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected java.util.Random</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_random">m_random</A></B></CODE><BR> The random number generator - used for the random search heuristic</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_randomSeed">m_randomSeed</A></B></CODE><BR> Option - the seed to use for a random search</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected <A HREF="../../../weka/classifiers/adtree/PredictionNode.html">PredictionNode</A></CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_root">m_root</A></B></CODE><BR> The root of the tree</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected boolean</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_saveInstanceData">m_saveInstanceData</A></B></CODE><BR> Option - whether the tree should remember the instance data</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected <A HREF="../../../weka/classifiers/adtree/PredictionNode.html">PredictionNode</A></CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_search_bestInsertionNode">m_search_bestInsertionNode</A></B></CODE><BR> The best node to insert under, as found so far by the latest search</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected <A HREF="../../../weka/core/Instances.html">Instances</A></CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_search_bestPathNegInstances">m_search_bestPathNegInstances</A></B></CODE><BR> The negative instances that apply to the best path found so far</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected <A HREF="../../../weka/core/Instances.html">Instances</A></CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_search_bestPathPosInstances">m_search_bestPathPosInstances</A></B></CODE><BR> The positive instances that apply to the best path found so far</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected <A HREF="../../../weka/classifiers/adtree/Splitter.html">Splitter</A></CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_search_bestSplitter">m_search_bestSplitter</A></B></CODE><BR> The best splitter to insert, as found so far by the latest search</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected double</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_search_smallestZ">m_search_smallestZ</A></B></CODE><BR> The smallest Z value found so far by the latest search</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_searchPath">m_searchPath</A></B></CODE><BR> Option - the search mode</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected <A HREF="../../../weka/core/Instances.html">Instances</A></CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_trainInstances">m_trainInstances</A></B></CODE><BR> The instances used to train the tree</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected double</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#m_trainTotalWeight">m_trainTotalWeight</A></B></CODE><BR> The total weight of the instances - used to speed Z calculations</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>static int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#SEARCHPATH_ALL">SEARCHPATH_ALL</A></B></CODE><BR> The search modes</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>static int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#SEARCHPATH_HEAVIEST">SEARCHPATH_HEAVIEST</A></B></CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>static int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#SEARCHPATH_RANDOM">SEARCHPATH_RANDOM</A></B></CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>static int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#SEARCHPATH_ZPURE">SEARCHPATH_ZPURE</A></B></CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>static <A HREF="../../../weka/core/Tag.html">Tag</A>[]</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/adtree/ADTree.html#TAGS_SEARCHPATH">TAGS_SEARCHPATH</A></B></CODE><BR> </TD></TR></TABLE> <!-- ======== CONSTRUCTOR SUMMARY ======== --><A NAME="constructor_summary"><!-- --></A><TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%"><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TD COLSPAN=2><FONT SIZE="+2"><B>Constructor Summary</B></FONT></TD></TR>⌨️ 快捷键说明
复制代码
Ctrl + C
搜索代码
Ctrl + F
全屏模式
F11
切换主题
Ctrl + Shift + D
显示快捷键
?
增大字号
Ctrl + =
减小字号
Ctrl + -