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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_13) on Mon Jul 14 01:36:54 CEST 2008 --><TITLE>com.rapidminer.operator.learner.tree (RapidMiner Class Documentation)</TITLE><META NAME="keywords" CONTENT="com.rapidminer.operator.learner.tree package"><LINK REL ="stylesheet" TYPE="text/css" HREF="../../../../../stylesheet.css" TITLE="Style"><SCRIPT type="text/javascript">function windowTitle(){ parent.document.title="com.rapidminer.operator.learner.tree (RapidMiner Class Documentation)";}</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"><!-- 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Classes</B></A></NOSCRIPT></FONT></TD></TR></TABLE><A NAME="skip-navbar_top"></A><!-- ========= END OF TOP NAVBAR ========= --><HR><H2>Package com.rapidminer.operator.learner.tree</H2>Provides decision tree learners.<P><B>See:</B><BR> <A HREF="#package_description"><B>Description</B></A><P><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="2"><FONT SIZE="+2"><B>Interface Summary</B></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/tree/Criterion.html" title="interface in com.rapidminer.operator.learner.tree">Criterion</A></B></TD><TD>The criterion for a splitted example set.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/tree/LeafCreator.html" title="interface in com.rapidminer.operator.learner.tree">LeafCreator</A></B></TD><TD>This class can be used to transform an inner tree node into a leaf.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/tree/Pruner.html" title="interface in com.rapidminer.operator.learner.tree">Pruner</A></B></TD><TD>The pruner for trees.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/tree/SplitCondition.html" title="interface in com.rapidminer.operator.learner.tree">SplitCondition</A></B></TD><TD>A condition for a split in decision tree, rules etc.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/tree/SplitPreprocessing.html" title="interface in com.rapidminer.operator.learner.tree">SplitPreprocessing</A></B></TD><TD>Will be used before each split.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/tree/Terminator.html" title="interface in com.rapidminer.operator.learner.tree">Terminator</A></B></TD><TD>Implementations of this interface are used in order to determine if a splitting procedure should be stopped.</TD></TR></TABLE> <P><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="2"><FONT SIZE="+2"><B>Class Summary</B></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/tree/AbstractCriterion.html" title="class in com.rapidminer.operator.learner.tree">AbstractCriterion</A></B></TD><TD>This criterion class can be used for the incremental calculation of benefits.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/tree/AbstractSplitCondition.html" title="class in com.rapidminer.operator.learner.tree">AbstractSplitCondition</A></B></TD><TD>The abstract super class for all split conditions.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/tree/AbstractTreeLearner.html" title="class in com.rapidminer.operator.learner.tree">AbstractTreeLearner</A></B></TD><TD>This is the abstract super class for all decision tree learners.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/tree/AccuracyCriterion.html" title="class in com.rapidminer.operator.learner.tree">AccuracyCriterion</A></B></TD><TD>Calculates the accuracies for the given split if the children predict the majority classes.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/tree/Benefit.html" title="class in com.rapidminer.operator.learner.tree">Benefit</A></B></TD><TD>Encapsulates some information about the benefit of a split.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/tree/CHAIDLearner.html" title="class in com.rapidminer.operator.learner.tree">CHAIDLearner</A></B></TD><TD>The CHAID decision tree learner works like the <A HREF="../../../../../com/rapidminer/operator/learner/tree/DecisionTreeLearner.html" title="class in com.rapidminer.operator.learner.tree"><CODE>DecisionTreeLearner</CODE></A> with one exception: it used a chi squared based criterion instead of the information gain or gain ratio criteria.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/tree/DecisionStumpLearner.html" title="class in com.rapidminer.operator.learner.tree">DecisionStumpLearner</A></B></TD><TD>This operator learns decision stumps, i.e. a small decision tree with only one single split.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/tree/DecisionTreeLeafCreator.html" title="class in com.rapidminer.operator.learner.tree">DecisionTreeLeafCreator</A></B></TD><TD>This class can be used to transform an inner tree node into a leaf.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/tree/DecisionTreeLearner.html" title="class in com.rapidminer.operator.learner.tree">DecisionTreeLearner</A></B></TD><TD>This operator learns decision trees from both nominal and numerical data.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/tree/Edge.html" title="class in com.rapidminer.operator.learner.tree">Edge</A></B></TD><TD>The class edge holds the information about a split condition to a tree (child).</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/tree/EmptyTermination.html" title="class in com.rapidminer.operator.learner.tree">EmptyTermination</A></B></TD><TD>Splitting should be terminated if the example set is empty.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor">⌨️ 快捷键说明
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