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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 01:36:53 CEST 2008 --><TITLE>com.rapidminer.operator.features.weighting (RapidMiner Class Documentation)</TITLE><META NAME="keywords" CONTENT="com.rapidminer.operator.features.weighting package"><LINK REL ="stylesheet" TYPE="text/css" HREF="../../../../../stylesheet.css" TITLE="Style"><SCRIPT type="text/javascript">function windowTitle(){    parent.document.title="com.rapidminer.operator.features.weighting (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 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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></TABLE><A NAME="skip-navbar_top"></A><!-- ========= END OF TOP NAVBAR ========= --><HR><H2>Package com.rapidminer.operator.features.weighting</H2>Operators to weight features or determine feature relevance.<P><B>See:</B><BR>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<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>Class Summary</B></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/features/weighting/AbstractEntropyWeighting.html" title="class in com.rapidminer.operator.features.weighting">AbstractEntropyWeighting</A></B></TD><TD>This operator calculates the relevance of a feature by computing the  an entropy value of the class distribution, if the given example set would  have been splitted according to the feature.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/features/weighting/AbstractWeighting.html" title="class in com.rapidminer.operator.features.weighting">AbstractWeighting</A></B></TD><TD>This is an abstract superclass for RapidMiner weighting operators.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/features/weighting/AttributeWeightsCreator.html" title="class in com.rapidminer.operator.features.weighting">AttributeWeightsCreator</A></B></TD><TD>This operator creates a new attribute weights IOObject from a given example set.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/features/weighting/BackwardWeighting.html" title="class in com.rapidminer.operator.features.weighting">BackwardWeighting</A></B></TD><TD>Uses the backward selection idea for the weighting of features.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/features/weighting/ChiSquaredWeighting.html" title="class in com.rapidminer.operator.features.weighting">ChiSquaredWeighting</A></B></TD><TD>This operator calculates the relevance of a feature by computing  for each attribute of the input example set the value of the  chi-squared statistic with respect to the class attribute.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/features/weighting/ComponentWeights.html" title="class in com.rapidminer.operator.features.weighting">ComponentWeights</A></B></TD><TD>For models creating components like <code>PCA</code>, <code>GHA</code> and <code>FastICA</code> you can create the <code>AttributeWeights</code> from a component.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/features/weighting/CorpusBasedFeatureWeighting.html" title="class in com.rapidminer.operator.features.weighting">CorpusBasedFeatureWeighting</A></B></TD><TD>This operator uses a corpus of examples to characterize a single class by setting feature weights.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/features/weighting/EvolutionaryWeighting.html" title="class in com.rapidminer.operator.features.weighting">EvolutionaryWeighting</A></B></TD><TD>This operator performs the weighting of features with an evolutionary strategies approach.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/features/weighting/FeatureWeighting.html" title="class in com.rapidminer.operator.features.weighting">FeatureWeighting</A></B></TD><TD>This operator performs the weighting under the naive assumption that the features are independent from each other.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/features/weighting/ForwardWeighting.html" title="class in com.rapidminer.operator.features.weighting">ForwardWeighting</A></B></TD><TD>This operator performs the weighting under the naive assumption that the features are independent from each other.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/features/weighting/GenericWekaAttributeWeighting.html" title="class in com.rapidminer.operator.features.weighting">GenericWekaAttributeWeighting</A></B></TD><TD>Performs the AttributeEvaluator of Weka with the same name to determine a sort of attribute relevance.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/features/weighting/GiniWeighting.html" title="class in com.rapidminer.operator.features.weighting">GiniWeighting</A></B></TD><TD>This operator calculates the relevance of a feature by computing the  Gini index of the class distribution, if the given example set would 

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