Java* API Reference for Intel® Data Analytics Acceleration Library 2018 Update 2

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Parameter Class Reference

Base class for parameters of the decision tree classification algorithm. More...

Detailed Description

Member Function Documentation

◆ getMaxTreeDepth()

long getMaxTreeDepth ( )

Returns the maximum tree depth. 0 means unlimited depth.

Returns
Maximum tree depth

◆ getMinObservationsInLeafNodes()

long getMinObservationsInLeafNodes ( )

Returns the minimum number of observations in the leaf node

Returns
Minimum number of observations in the leaf node

◆ getPruning()

PruningId getPruning ( )

Returns the pruning method for decision tree training algorithm

Returns
Pruning method for decision tree

◆ getSplitCriterion()

SplitCriterionId getSplitCriterion ( )

Returns the split criterion for decision tree classification

Returns
Split criterion for decision tree classification

◆ setMaxTreeDepth()

void setMaxTreeDepth ( long  value)

Sets the maximum tree depth, 0 means unlimited depth

Parameters
valueMaximum tree depth

◆ setMinObservationsInLeafNodes()

void setMinObservationsInLeafNodes ( long  value)

Sets the minimum number of observations in the leaf node

Parameters
valueMinimum number of observations in the leaf node

◆ setPruning()

void setPruning ( PruningId  value)

Sets the pruning method for decision tree training algorithm

Parameters
valuePruning method for decision tree

◆ setSplitCriterion()

void setSplitCriterion ( SplitCriterionId  value)

Sets the split criterion for decision tree classification

Parameters
valueSplit criterion for decision tree classification

The documentation for this class was generated from the following file:

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