bayesianboosting.html

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 produce the same initial weighting during model application.</p>
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<DL>
<DT><B>Version:</B></DT>
  <DD>$Id: BayesianBoosting.java,v 1.56 2006/04/14 15:14:32 ingomierswa
          Exp $</DD>
<DT><B>Author:</B></DT>
  <DD>Martin Scholz</DD>
</DL>
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<!-- =========== FIELD SUMMARY =========== -->

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<B>Field Summary</B></FONT></TH>
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<CODE>protected &nbsp;int</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/BayesianBoosting.html#currentIteration">currentIteration</A></B></CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Field for visualizing performance.</TD>
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<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>static&nbsp;double</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/BayesianBoosting.html#MIN_ADVANTAGE">MIN_ADVANTAGE</A></B></CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Discard models with an advantage of less than the specified value.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>static&nbsp;java.lang.String</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/BayesianBoosting.html#PARAMETER_ALLOW_MARGINAL_SKEWS">PARAMETER_ALLOW_MARGINAL_SKEWS</A></B></CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Boolean parameter that switches between KBS (if set to false) and a
 boosting-like reweighting.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>static&nbsp;java.lang.String</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/BayesianBoosting.html#PARAMETER_ITERATIONS">PARAMETER_ITERATIONS</A></B></CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Name of the variable specifying the maximal number of iterations of the
 learner.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>static&nbsp;java.lang.String</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/BayesianBoosting.html#PARAMETER_RESCALE_LABEL_PRIORS">PARAMETER_RESCALE_LABEL_PRIORS</A></B></CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Boolean parameter to specify whether the label priors should be equally
 likely after first iteration.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>static&nbsp;java.lang.String</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/BayesianBoosting.html#PARAMETER_USE_SUBSET_FOR_TRAINING">PARAMETER_USE_SUBSET_FOR_TRAINING</A></B></CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Name of the flag indicating internal bootstrapping.</TD>
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<!-- ======== CONSTRUCTOR SUMMARY ======== -->

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<B>Constructor Summary</B></FONT></TH>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD><CODE><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/BayesianBoosting.html#BayesianBoosting(com.rapidminer.operator.OperatorDescription)">BayesianBoosting</A></B>(<A HREF="../../../../../com/rapidminer/operator/OperatorDescription.html" title="class in com.rapidminer.operator">OperatorDescription</A>&nbsp;description)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Constructor.</TD>
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<!-- ========== METHOD SUMMARY =========== -->

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<B>Method Summary</B></FONT></TH>
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<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>&nbsp;java.util.List&lt;<A HREF="../../../../../com/rapidminer/parameter/ParameterType.html" title="class in com.rapidminer.parameter">ParameterType</A>&gt;</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/BayesianBoosting.html#getParameterTypes()">getParameterTypes</A></B>()</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Adds the parameters &quot;number of iterations&quot; and &quot;model
 file&quot;.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>&nbsp;<A HREF="../../../../../com/rapidminer/operator/Model.html" title="interface in com.rapidminer.operator">Model</A></CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/BayesianBoosting.html#learn(com.rapidminer.example.ExampleSet)">learn</A></B>(<A HREF="../../../../../com/rapidminer/example/ExampleSet.html" title="interface in com.rapidminer.example">ExampleSet</A>&nbsp;exampleSet)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Constructs a <code>Model</code> repeatedly running a weak learner,
 reweighting the training example set accordingly, and combining the
 hypothesis using the available weighted performance values.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>protected &nbsp;double[]</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/BayesianBoosting.html#prepareWeights(com.rapidminer.example.ExampleSet)">prepareWeights</A></B>(<A HREF="../../../../../com/rapidminer/example/ExampleSet.html" title="interface in com.rapidminer.example">ExampleSet</A>&nbsp;exampleSet)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Creates a weight attribute if not yet done.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>protected &nbsp;double</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/BayesianBoosting.html#reweightExamples(com.rapidminer.operator.learner.meta.WeightedPerformanceMeasures, com.rapidminer.example.ExampleSet)">reweightExamples</A></B>(<A HREF="../../../../../com/rapidminer/operator/learner/meta/WeightedPerformanceMeasures.html" title="class in com.rapidminer.operator.learner.meta">WeightedPerformanceMeasures</A>&nbsp;wp,
                 <A HREF="../../../../../com/rapidminer/example/ExampleSet.html" title="interface in com.rapidminer.example">ExampleSet</A>&nbsp;exampleSet)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;This method reweights the example set with respect to the
 <code>WeightedPerformanceMeasures</code> object.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>&nbsp;boolean</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/BayesianBoosting.html#supportsCapability(com.rapidminer.operator.learner.LearnerCapability)">supportsCapability</A></B>(<A HREF="../../../../../com/rapidminer/operator/learner/LearnerCapability.html" title="class in com.rapidminer.operator.learner">LearnerCapability</A>&nbsp;lc)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Overrides the method of the super class.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>protected &nbsp;<A HREF="../../../../../com/rapidminer/operator/Model.html" title="interface in com.rapidminer.operator">Model</A></CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../com/rapidminer/operator/learner/meta/BayesianBoosting.html#trainBaseModel(com.rapidminer.example.ExampleSet)">trainBaseModel</A></B>(<A HREF="../../../../../com/rapidminer/example/ExampleSet.html" title="interface in com.rapidminer.example">ExampleSet</A>&nbsp;exampleSet)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Runs the &quot;embedded&quot; learner on the example set and retuns a
 model.</TD>
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&nbsp;<A NAME="methods_inherited_from_class_com.rapidminer.operator.learner.meta.AbstractMetaLearner"><!-- --></A>
<TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY="">
<TR BGCOLOR="#EEEEFF" CLASS="TableSubHeadingColor">
<TH ALIGN="left"><B>Methods inherited from class com.rapidminer.operator.learner.meta.<A HREF="../../../../../com/rapidminer/operator/learner/meta/AbstractMetaLearner.html" title="class in com.rapidminer.operator.learner.meta">AbstractMetaLearner</A></B></TH>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD><CODE><A HREF="../../../../../com/rapidminer/operator/learner/meta/AbstractMetaLearner.html#apply()">apply</A>, <A HREF="../../../../../com/rapidminer/operator/learner/meta/AbstractMetaLearner.html#applyInnerLearner(com.rapidminer.example.ExampleSet)">applyInnerLearner</A>, <A HREF="../../../../../com/rapidminer/operator/learner/meta/AbstractMetaLearner.html#getEstimatedPerformance()">getEstimatedPerformance</A>, <A HREF="../../../../../com/rapidminer/operator/learner/meta/AbstractMetaLearner.html#getInnerOperatorCondition()">getInnerOperatorCondition</A>, <A HREF="../../../../../com/rapidminer/operator/learner/meta/AbstractMetaLearner.html#getInputClasses()">getInputClasses</A>, <A HREF="../../../../../com/rapidminer/operator/learner/meta/AbstractMetaLearner.html#getInputDescription(java.lang.Class)">getInputDescription</A>, <A HREF="../../../../../com/rapidminer/operator/learner/meta/AbstractMetaLearner.html#getMaxNumberOfInnerOperators()">getMaxNumberOfInnerOperators</A>, <A HREF="../../../../../com/rapidminer/operator/learner/meta/AbstractMetaLearner.html#getMinNumberOfInnerOperators()">getMinNumberOfInnerOperators</A>, <A HREF="../../../../../com/rapidminer/operator/learner/meta/AbstractMetaLearner.html#getOutputClasses()">getOutputClasses</A>, <A HREF="../../../../../com/rapidminer/operator/learner/meta/AbstractMetaLearner.html#getWeights(com.rapidminer.example.ExampleSet)">getWeights</A>, <A HREF="../../../../../com/rapidminer/operator/learner/meta/AbstractMetaLearner.html#shouldCalculateWeights()">shouldCalculateWeights</A>, <A HREF="../../../../../com/rapidminer/operator/learner/meta/AbstractMetaLearner.html#shouldEstimatePerformance()">shouldEstimatePerformance</A></CODE></TD>
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&nbsp;<A NAME="methods_inherited_from_class_com.rapidminer.operator.OperatorChain"><!-- --></A>