org.knime.base.node.mine.decisiontree2.learner
Class SplitNominal

java.lang.Object
  extended by org.knime.base.node.mine.decisiontree2.learner.Split
      extended by org.knime.base.node.mine.decisiontree2.learner.SplitNominal
Direct Known Subclasses:
SplitNominalBinary, SplitNominalNormal

public abstract class SplitNominal
extends Split

Super class for all nominal split variants.

Author:
Christoph Sieb, University of Konstanz

Field Summary
 
Fields inherited from class org.knime.base.node.mine.decisiontree2.learner.Split
m_splitQualityMeasure
 
Constructor Summary
SplitNominal(InMemoryTable table, int attributeIndex, SplitQualityMeasure splitQualityMeasure)
          Constructs the best split for the given attribute list and the class distribution.
 
Method Summary
 DataCell[] getSplitValues()
          Returns the possible values of this splits attribute.
 
Methods inherited from class org.knime.base.node.mine.decisiontree2.learner.Split
canBeFurtherUsed, getAttributeIndex, getBestQualityMeasure, getNumberPartitions, getPartitionForRow, getPartitionWeights, getQualityMeasureName, getSplitAttributeName, getTable, isValidSplit, setBestQualityMeasure, toString
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
 

Constructor Detail

SplitNominal

public SplitNominal(InMemoryTable table,
                    int attributeIndex,
                    SplitQualityMeasure splitQualityMeasure)
Constructs the best split for the given attribute list and the class distribution. The results can be retrieved from getter methods. This is a nominal split.

Parameters:
table - the table for which to create the split
attributeIndex - the index specifying the attribute for which to calculate the split
splitQualityMeasure - the quality measure to determine the best split (e.g. gini or gain ratio)
Method Detail

getSplitValues

public DataCell[] getSplitValues()
Returns the possible values of this splits attribute. Those values are used for the split criteria.

Returns:
the possible values of this splits attribute


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