org.tribuo.common.tree

Interface DecisionTreeTrainer<T extends Output<T>>

All Superinterfaces:

com.oracle.labs.mlrg.olcut.config.Configurable, com.oracle.labs.mlrg.olcut.provenance.Provenancable<TrainerProvenance>, SparseTrainer<T>, Trainer<T>, WeightedExamples

All Known Implementing Classes:

AbstractCARTTrainer, CARTClassificationTrainer, CARTJointRegressionTrainer, CARTRegressionTrainer

public interface DecisionTreeTrainer<T extends Output<T>>
extends SparseTrainer<T>, WeightedExamples

A tag interface for a Trainer so the random forests trainer can check if it's actually a tree.

Field Summary

Fields inherited from interface org.tribuo.Trainer

DEFAULT_SEED

Method Summary

Modifier and Type	Method and Description
float	getFractionFeaturesInSplit() Returns the feature subsampling rate.
float	getMinImpurityDecrease() Returns the minimum decrease in impurity necessary to split a node.
boolean	getUseRandomSplitPoints() Returns whether to choose split points for features at random.

Methods inherited from interface org.tribuo.SparseTrainer

train, train

Methods inherited from interface org.tribuo.Trainer

getInvocationCount

Methods inherited from interface com.oracle.labs.mlrg.olcut.config.Configurable

postConfig

Methods inherited from interface com.oracle.labs.mlrg.olcut.provenance.Provenancable

getProvenance

Method Detail

getFractionFeaturesInSplit

float getFractionFeaturesInSplit()

Returns the feature subsampling rate.

Returns:

The feature subsampling rate.

getUseRandomSplitPoints

boolean getUseRandomSplitPoints()

Returns whether to choose split points for features at random.

Returns:

Whether to choose split points for features at random.

getMinImpurityDecrease

float getMinImpurityDecrease()

Returns the minimum decrease in impurity necessary to split a node.

Returns:

The minimum decrease in impurity necessary to split a node.