Package org.apache.spark.ml.tree

Interface RandomForestParams

All Superinterfaces:

DecisionTreeParams, HasCheckpointInterval, HasFeaturesCol, HasLabelCol, HasPredictionCol, HasSeed, HasWeightCol, Identifiable, Params, PredictorParams, Serializable, TreeEnsembleParams

All Known Subinterfaces:

RandomForestClassifierParams, RandomForestRegressorParams

All Known Implementing Classes:

RandomForestClassificationModel, RandomForestClassifier, RandomForestRegressionModel, RandomForestRegressor

public interface RandomForestParams
extends TreeEnsembleParams

Parameters for Random Forest algorithms.

Method Summary

Modifier and Type	Method	Description
BooleanParam	bootstrap()	Whether bootstrap samples are used when building trees.
boolean	getBootstrap()
int	getNumTrees()
IntParam	numTrees()	Number of trees to train (at least 1).

Methods inherited from interface org.apache.spark.ml.tree.DecisionTreeParams

cacheNodeIds, getCacheNodeIds, getLeafCol, getMaxBins, getMaxDepth, getMaxMemoryInMB, getMinInfoGain, getMinInstancesPerNode, getMinWeightFractionPerNode, getOldStrategy, leafCol, maxBins, maxDepth, maxMemoryInMB, minInfoGain, minInstancesPerNode, minWeightFractionPerNode, setLeafCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasCheckpointInterval

checkpointInterval, getCheckpointInterval

Methods inherited from interface org.apache.spark.ml.param.shared.HasFeaturesCol

featuresCol, getFeaturesCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasLabelCol

getLabelCol, labelCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasPredictionCol

getPredictionCol, predictionCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasSeed

getSeed, seed

Methods inherited from interface org.apache.spark.ml.param.shared.HasWeightCol

getWeightCol, weightCol

Methods inherited from interface org.apache.spark.ml.util.Identifiable

toString, uid

Methods inherited from interface org.apache.spark.ml.param.Params

clear, copy, copyValues, defaultCopy, defaultParamMap, estimateMatadataSize, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

Methods inherited from interface org.apache.spark.ml.PredictorParams

validateAndTransformSchema

Methods inherited from interface org.apache.spark.ml.tree.TreeEnsembleParams

featureSubsetStrategy, getFeatureSubsetStrategy, getOldStrategy, getSubsamplingRate, subsamplingRate

Method Details

bootstrap

BooleanParam bootstrap()

Whether bootstrap samples are used when building trees.

Returns:

(undocumented)

getBootstrap

boolean getBootstrap()

getNumTrees

int getNumTrees()

numTrees

IntParam numTrees()

Number of trees to train (at least 1). If 1, then no bootstrapping is used. If greater than 1, then bootstrapping is done. TODO: Change to always do bootstrapping (simpler). SPARK-7130 (default = 20)

Note: The reason that we cannot add this to both GBT and RF (i.e. in TreeEnsembleParams) is the param maxIter controls how many trees a GBT has. The semantics in the algorithms are a bit different.

Returns:

(undocumented)