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<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/ClassificationByRegression.html" title="class in com.rapidminer.operator.learner.meta">ClassificationByRegression</A></B></TD>
<TD>For a classified dataset (with possibly more than two classes) builds a
 classifier using a regression method which is specified by the inner
 operator.</TD>
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<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/ContingencyMatrix.html" title="class in com.rapidminer.operator.learner.meta">ContingencyMatrix</A></B></TD>
<TD>This class computes the contingency matrix of classifiers, supports weighted
 example sets and contains some convenience methods to query for some
 evaluation metrics that can directly be computed from this matrix.</TD>
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<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/CostBasedThresholdLearner.html" title="class in com.rapidminer.operator.learner.meta">CostBasedThresholdLearner</A></B></TD>
<TD>This operator uses a set of class weights and also allows a weight for the fact
 that an example is not classified at all (marked as unknown).</TD>
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<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/MetaCost.html" title="class in com.rapidminer.operator.learner.meta">MetaCost</A></B></TD>
<TD>This operator uses a given cost matrix to compute label predictions
 according to classification costs.</TD>
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<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/MetaCostModel.html" title="class in com.rapidminer.operator.learner.meta">MetaCostModel</A></B></TD>
<TD>This class is associated to the MetaCost operator and supports the 
 evaluation procedures of the MetaCost method.</TD>
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<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/MultiModel.html" title="class in com.rapidminer.operator.learner.meta">MultiModel</A></B></TD>
<TD>MultiModels are used for multi class learning tasks.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/MultiModelByRegression.html" title="class in com.rapidminer.operator.learner.meta">MultiModelByRegression</A></B></TD>
<TD>MultiModels are used for multi class learning tasks.</TD>
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<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/RelativeRegression.html" title="class in com.rapidminer.operator.learner.meta">RelativeRegression</A></B></TD>
<TD>This meta regression learner transforms the label on-the-fly relative
 to the value of the specified attribute.</TD>
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<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/RelativeRegressionModel.html" title="class in com.rapidminer.operator.learner.meta">RelativeRegressionModel</A></B></TD>
<TD>The model for the relative regression meta learner.</TD>
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<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/SDEnsemble.html" title="class in com.rapidminer.operator.learner.meta">SDEnsemble</A></B></TD>
<TD>A subgroup discovery model.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/SDReweightMeasures.html" title="class in com.rapidminer.operator.learner.meta">SDReweightMeasures</A></B></TD>
<TD>A set of weighted performance measures used for subgroup discovery.</TD>
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<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/SDRulesetInduction.html" title="class in com.rapidminer.operator.learner.meta">SDRulesetInduction</A></B></TD>
<TD>Subgroup discovery learner.</TD>
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<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/SimpleVoteModel.html" title="class in com.rapidminer.operator.learner.meta">SimpleVoteModel</A></B></TD>
<TD>A simple vote model.</TD>
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<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/Stacking.html" title="class in com.rapidminer.operator.learner.meta">Stacking</A></B></TD>
<TD>This class uses n+1 inner learners and generates n different models
 by using the last n learners.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/StackingModel.html" title="class in com.rapidminer.operator.learner.meta">StackingModel</A></B></TD>
<TD>This class is the model build by the <A HREF="../../../../../com/rapidminer/operator/learner/meta/Stacking.html" title="class in com.rapidminer.operator.learner.meta"><CODE>Stacking</CODE></A> operator.</TD>
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<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/ThresholdModel.html" title="class in com.rapidminer.operator.learner.meta">ThresholdModel</A></B></TD>
<TD>This model is created by the <A HREF="../../../../../com/rapidminer/operator/learner/meta/CostBasedThresholdLearner.html" title="class in com.rapidminer.operator.learner.meta"><CODE>CostBasedThresholdLearner</CODE></A>.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/TransformedRegression.html" title="class in com.rapidminer.operator.learner.meta">TransformedRegression</A></B></TD>
<TD>This meta learner applies a transformation on the label before the inner
 regression learner is applied.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/TransformedRegressionModel.html" title="class in com.rapidminer.operator.learner.meta">TransformedRegressionModel</A></B></TD>
<TD>Model for TransformedRegression.</TD>
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<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/Tree2RuleConverter.html" title="class in com.rapidminer.operator.learner.meta">Tree2RuleConverter</A></B></TD>
<TD>This meta learner uses an inner tree learner and creates a rule model
 from the learned decision tree.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/Vote.html" title="class in com.rapidminer.operator.learner.meta">Vote</A></B></TD>
<TD>This class uses n+1 inner learners and generates n different models
 by using the last n learners.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD WIDTH="15%"><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/WeightedPerformanceMeasures.html" title="class in com.rapidminer.operator.learner.meta">WeightedPerformanceMeasures</A></B></TD>
<TD>This private class cares about <i>weighted</i> performance measures as used
 by the <code>BayesianBoosting</code> algorithm and the similarly working
 <code>ModelBasedSampling</code> operator.</TD>
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&nbsp;

<P>
<A NAME="package_description"><!-- --></A><H2>
Package com.rapidminer.operator.learner.meta Description
</H2>

<P>
Meta learning schemes which uses other learning operators to increase the performance.
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