org.apache.spark.ml.tree

Interface TreeEnsembleModel<M extends DecisionTreeModel>

Type Parameters:

M - Type of tree model in this ensemble

All Known Implementing Classes:

GBTClassificationModel, GBTRegressionModel, RandomForestClassificationModel, RandomForestRegressionModel

public interface TreeEnsembleModel<M extends DecisionTreeModel>

Abstraction for models which are ensembles of decision trees

Method Summary

Modifier and Type	Method and Description
Vector	javaTreeWeights() Weights used by the python wrappers.
Vector	predictLeaf(Vector features)
String	toDebugString() Full description of model
String	toString() Summary of the model
int	totalNumNodes() Total number of nodes, summed over all trees in the ensemble.
M[]	trees() Trees in this ensemble.
double[]	treeWeights() Weights for each tree, zippable with trees

Method Detail

trees

M[] trees()

Trees in this ensemble. Warning: These have null parent Estimators.

treeWeights

double[] treeWeights()

Weights for each tree, zippable with trees

javaTreeWeights

Vector javaTreeWeights()

Weights used by the python wrappers.

toString

String toString()

Summary of the model

Overrides:

toString in class Object

toDebugString

String toDebugString()

Full description of model

totalNumNodes

int totalNumNodes()

Total number of nodes, summed over all trees in the ensemble.

predictLeaf

Vector predictLeaf(Vector features)

Parameters:

features - (undocumented)

Returns:

The indices of the leaves corresponding to the feature vector. Leaves are indexed in pre-order from 0.