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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd"><!--NewPage--><HTML><HEAD><!-- Generated by javadoc (build 1.5.0_10) on Fri Jan 26 16:34:46 NZDT 2007 --><TITLE>BFTree</TITLE><META NAME="keywords" CONTENT="weka.classifiers.trees.BFTree class"><LINK REL ="stylesheet" TYPE="text/css" HREF="../../../stylesheet.css" TITLE="Style"><SCRIPT type="text/javascript">function windowTitle(){ parent.document.title="BFTree";}</SCRIPT><NOSCRIPT></NOSCRIPT></HEAD><BODY BGCOLOR="white" onload="windowTitle();"><!-- ========= START OF TOP NAVBAR ======= --><A NAME="navbar_top"><!-- --></A><A HREF="#skip-navbar_top" title="Skip navigation links"></A><TABLE BORDER="0" WIDTH="100%" CELLPADDING="1" CELLSPACING="0" SUMMARY=""><TR><TD COLSPAN=2 BGCOLOR="#EEEEFF" CLASS="NavBarCell1"><A NAME="navbar_top_firstrow"><!-- --></A><TABLE BORDER="0" CELLPADDING="0" CELLSPACING="3" SUMMARY=""> <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> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="http://www.cs.waikato.ac.nz/ml/weka/" target="_blank"><FONT CLASS="NavBarFont1"><B>Weka's home</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"> <A HREF="../../../weka/classifiers/trees/ADTree.html" title="class in weka.classifiers.trees"><B>PREV CLASS</B></A> <A HREF="../../../weka/classifiers/trees/DecisionStump.html" title="class in weka.classifiers.trees"><B>NEXT CLASS</B></A></FONT></TD><TD BGCOLOR="white" CLASS="NavBarCell2"><FONT SIZE="-2"> <A HREF="../../../index.html?weka/classifiers/trees/BFTree.html" target="_top"><B>FRAMES</B></A> <A HREF="BFTree.html" target="_top"><B>NO FRAMES</B></A> <SCRIPT type="text/javascript"> <!-- if(window==top) { document.writeln('<A HREF="../../../allclasses-noframe.html"><B>All Classes</B></A>'); } //--></SCRIPT><NOSCRIPT> <A HREF="../../../allclasses-noframe.html"><B>All Classes</B></A></NOSCRIPT></FONT></TD></TR><TR><TD VALIGN="top" CLASS="NavBarCell3"><FONT SIZE="-2"> SUMMARY: NESTED | <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><A NAME="skip-navbar_top"></A><!-- ========= END OF TOP NAVBAR ========= --><HR><!-- ======== START OF CLASS DATA ======== --><H2><FONT SIZE="-1">weka.classifiers.trees</FONT><BR>Class BFTree</H2><PRE>java.lang.Object <IMG SRC="../../../resources/inherit.gif" ALT="extended by "><A HREF="../../../weka/classifiers/Classifier.html" title="class in weka.classifiers">weka.classifiers.Classifier</A> <IMG SRC="../../../resources/inherit.gif" ALT="extended by "><A HREF="../../../weka/classifiers/RandomizableClassifier.html" title="class in weka.classifiers">weka.classifiers.RandomizableClassifier</A> <IMG SRC="../../../resources/inherit.gif" ALT="extended by "><B>weka.classifiers.trees.BFTree</B></PRE><DL><DT><B>All Implemented Interfaces:</B> <DD>java.io.Serializable, java.lang.Cloneable, <A HREF="../../../weka/core/AdditionalMeasureProducer.html" title="interface in weka.core">AdditionalMeasureProducer</A>, <A HREF="../../../weka/core/CapabilitiesHandler.html" title="interface in weka.core">CapabilitiesHandler</A>, <A HREF="../../../weka/core/OptionHandler.html" title="interface in weka.core">OptionHandler</A>, <A HREF="../../../weka/core/Randomizable.html" title="interface in weka.core">Randomizable</A>, <A HREF="../../../weka/core/TechnicalInformationHandler.html" title="interface in weka.core">TechnicalInformationHandler</A></DD></DL><HR><DL><DT><PRE>public class <B>BFTree</B><DT>extends <A HREF="../../../weka/classifiers/RandomizableClassifier.html" title="class in weka.classifiers">RandomizableClassifier</A><DT>implements <A HREF="../../../weka/core/AdditionalMeasureProducer.html" title="interface in weka.core">AdditionalMeasureProducer</A>, <A HREF="../../../weka/core/TechnicalInformationHandler.html" title="interface in weka.core">TechnicalInformationHandler</A></DL></PRE><P><!-- globalinfo-start --> Class for building a best-first decision tree classifier. This class uses binary split for both nominal and numeric attributes. For missing values, the method of 'fractional' instances is used.<br/> <br/> For more information, see:<br/> <br/> Haijian Shi (2007). Best-first decision tree learning. Hamilton, NZ.<br/> <br/> Jerome Friedman, Trevor Hastie, Robert Tibshirani (2000). Additive logistic regression : A statistical view of boosting. Annals of statistics. 28(2):337-407. <p/> <!-- globalinfo-end --> <!-- technical-bibtex-start --> BibTeX: <pre> @mastersthesis{Shi2007, address = {Hamilton, NZ}, author = {Haijian Shi}, note = {COMP594}, school = {University of Waikato}, title = {Best-first decision tree learning}, year = {2007} } @article{Friedman2000, author = {Jerome Friedman and Trevor Hastie and Robert Tibshirani}, journal = {Annals of statistics}, number = {2}, pages = {337-407}, title = {Additive logistic regression : A statistical view of boosting}, volume = {28}, year = {2000}, ISSN = {0090-5364} } </pre> <p/> <!-- technical-bibtex-end --> <!-- options-start --> Valid options are: <p/> <pre> -S <num> Random number seed. (default 1)</pre> <pre> -D If set, classifier is run in debug mode and may output additional info to the console</pre> <pre> -P <UNPRUNED|POSTPRUNED|PREPRUNED> The pruning strategy. (default: POSTPRUNED)</pre> <pre> -M <min no> The minimal number of instances at the terminal nodes. (default 2)</pre> <pre> -N <num folds> The number of folds used in the pruning. (default 5)</pre> <pre> -H Don't use heuristic search for nominal attributes in multi-class problem (default yes). </pre> <pre> -G Don't use Gini index for splitting (default yes), if not information is used.</pre> <pre> -R Don't use error rate in internal cross-validation (default yes), but root mean squared error.</pre> <pre> -A Use the 1 SE rule to make pruning decision. (default no).</pre> <pre> -C Percentage of training data size (0-1] (default 1).</pre> <!-- options-end --><P><P><DL><DT><B>Version:</B></DT> <DD>$Revision: 1.2 $</DD><DT><B>Author:</B></DT> <DD>Haijian Shi (hs69@cs.waikato.ac.nz)</DD><DT><B>See Also:</B><DD><A HREF="../../../serialized-form.html#weka.classifiers.trees.BFTree">Serialized Form</A></DL><HR><P><!-- =========== FIELD SUMMARY =========== --><A NAME="field_summary"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="2"><FONT SIZE="+2"><B>Field Summary</B></FONT></TH></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/trees/BFTree.html#PRUNING_POSTPRUNING">PRUNING_POSTPRUNING</A></B></CODE><BR> pruning strategy: post-pruning</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/trees/BFTree.html#PRUNING_PREPRUNING">PRUNING_PREPRUNING</A></B></CODE><BR> pruning strategy: pre-pruning</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/trees/BFTree.html#PRUNING_UNPRUNED">PRUNING_UNPRUNED</A></B></CODE><BR> pruning strategy: un-pruned</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" title="class in weka.core">Tag</A>[]</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/trees/BFTree.html#TAGS_PRUNING">TAGS_PRUNING</A></B></CODE><BR> pruning strategy</TD></TR></TABLE> <!-- ======== CONSTRUCTOR SUMMARY ======== --><A NAME="constructor_summary"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="2"><FONT SIZE="+2"><B>Constructor Summary</B></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><CODE><B><A HREF="../../../weka/classifiers/trees/BFTree.html#BFTree()">BFTree</A></B>()</CODE><BR> </TD></TR></TABLE> <!-- ========== METHOD SUMMARY =========== --><A NAME="method_summary"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="2"><FONT SIZE="+2"><B>Method Summary</B></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> void</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/trees/BFTree.html#buildClassifier(weka.core.Instances)">buildClassifier</A></B>(<A HREF="../../../weka/core/Instances.html" title="class in weka.core">Instances</A> data)</CODE><BR> Method for building a BestFirst decision tree classifier.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> double[]</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/trees/BFTree.html#distributionForInstance(weka.core.Instance)">distributionForInstance</A></B>(<A HREF="../../../weka/core/Instance.html" title="class in weka.core">Instance</A> instance)</CODE><BR> Computes class probabilities for instance using the decision tree.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> java.util.Enumeration</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/trees/BFTree.html#enumerateMeasures()">enumerateMeasures</A></B>()</CODE><BR> Return an enumeration of the measure names.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> <A HREF="../../../weka/core/Capabilities.html" title="class in weka.core">Capabilities</A></CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/trees/BFTree.html#getCapabilities()">getCapabilities</A></B>()</CODE><BR> Returns default capabilities of the classifier.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> boolean</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/trees/BFTree.html#getHeuristic()">getHeuristic</A></B>()</CODE><BR> Get if use heuristic search for nominal attributes in multi-class problems.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> double</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/trees/BFTree.html#getMeasure(java.lang.String)">getMeasure</A></B>(java.lang.String additionalMeasureName)</CODE><BR> Returns the value of the named measure</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/trees/BFTree.html#getMinNumObj()">getMinNumObj</A></B>()</CODE><BR> Get minimal number of instances at the terminal nodes.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/trees/BFTree.html#getNumFoldsPruning()">getNumFoldsPruning</A></B>()</CODE><BR> Set number of folds in internal cross-validation.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> java.lang.String[]</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/trees/BFTree.html#getOptions()">getOptions</A></B>()</CODE><BR> 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> <A HREF="../../../weka/core/SelectedTag.html" title="class in weka.core">SelectedTag</A></CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/trees/BFTree.html#getPruningStrategy()">getPruningStrategy</A></B>()</CODE><BR> Gets the pruning strategy.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> double</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/trees/BFTree.html#getSizePer()">getSizePer</A></B>()</CODE><BR> Get training set size.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> <A HREF="../../../weka/core/TechnicalInformation.html" title="class in weka.core">TechnicalInformation</A></CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/trees/BFTree.html#getTechnicalInformation()">getTechnicalInformation</A></B>()</CODE><BR> Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> boolean</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/trees/BFTree.html#getUseErrorRate()">getUseErrorRate</A></B>()</CODE><BR> Get if use error rate in internal cross-validation.</TD></TR>⌨️ 快捷键说明
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