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java.lang.Objectorg.knime.base.node.mine.decisiontree2.learner.SplitFinder
public class SplitFinder
Finds the best split for a given InMemoryTable
. The results can be
retrieved via getter methdods.
Constructor Summary | |
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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. |
Method Summary | |
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Split |
getSplit()
Returns the split evaluated as the best for the given data. |
int |
getSplitAttributeIndex()
Returns the attribute list that determines the split. |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public SplitFinder(InMemoryTable table, SplitQualityMeasure splitQualityMeasure, boolean averageSplitpoint, double minObjectsCount, boolean binaryNominalSplits, int maxNumNominalsForCompleteComputation)
table
- the data table for which to find the best split attribute
and for this the best splitsplitQualityMeasure
- the quality measure (e.g. gini or gain
ratio)averageSplitpoint
- if true, the split point is set as the average
of the partition borders, else the upper value of the lower
partition is usedminObjectsCount
- minimum number of examples for a partitionbinaryNominalSplits
- if true, nominal attributes are split
according to binary subsets, else each nominal value
represents one branchmaxNumNominalsForCompleteComputation
- the maximum number of nominal
values for which all subsets are calculated (results in the
optimal binary split); this parameter is only use if
binaryNominalSplits
is true
; if
the number of nominal values is higher, a heuristic is appliedMethod Detail |
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public Split getSplit()
public int getSplitAttributeIndex()
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