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Packages that use SplitQualityMeasure | |
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org.knime.base.node.mine.decisiontree2.learner |
Uses of SplitQualityMeasure in org.knime.base.node.mine.decisiontree2.learner |
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Subclasses of SplitQualityMeasure in org.knime.base.node.mine.decisiontree2.learner | |
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class |
SplitQualityGainRatio
Implements the gain ratio split quality measure. |
class |
SplitQualityGini
Implements the gini index split quality measure. |
Fields in org.knime.base.node.mine.decisiontree2.learner declared as SplitQualityMeasure | |
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protected SplitQualityMeasure |
Split.m_splitQualityMeasure
The quality measure to be used for the best split point calculation. |
Constructors in org.knime.base.node.mine.decisiontree2.learner with parameters of type SplitQualityMeasure | |
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Split(InMemoryTable table,
int attributeIndex,
SplitQualityMeasure splitQualityMeasure)
Constructs the best split for the given attribute list and the class distribution. |
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SplitContinuous(InMemoryTable table,
int attributeIndex,
SplitQualityMeasure splitQualityMeasure,
boolean averageSplitpoint,
double minObjectsCount)
Constructs the best split for the given numeric attribute list and the class distribution. |
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SplitFinder(InMemoryTable table,
SplitQualityMeasure splitQualityMeasure,
boolean averageSplitpoint,
double minObjectsCount,
boolean binaryNominalSplits,
int maxNumNominalsForCompleteComputation)
Finds the best split for the given data. |
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SplitNominal(InMemoryTable table,
int attributeIndex,
SplitQualityMeasure splitQualityMeasure)
Constructs the best split for the given attribute list and the class distribution. |
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SplitNominalBinary(InMemoryTable table,
int attributeIndex,
SplitQualityMeasure splitQualityMeasure,
double minObjectsCount,
int maxNumDifferentValues)
Constructs the best split for the given nominal attribute. |
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SplitNominalNormal(InMemoryTable table,
int attributeIndex,
SplitQualityMeasure splitQualityMeasure,
double minObjectsCount)
Constructs the best split for the given nominal attribute. |
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