Package 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, INCREMENT_INVOCATION_COUNT

Method Summary

Modifier and Type	Method	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 com.oracle.labs.mlrg.olcut.config.Configurable

postConfig

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

getProvenance

Methods inherited from interface org.tribuo.SparseTrainer

train, train, train

Methods inherited from interface org.tribuo.Trainer

getInvocationCount, setInvocationCount

Method Details

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.