org.apache.spark.ml.classification

Class RandomForestClassifier

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Estimator<M>

org.apache.spark.ml.Predictor<FeaturesType,E,M>

org.apache.spark.ml.classification.Classifier<FeaturesType,E,M>

org.apache.spark.ml.classification.ProbabilisticClassifier<Vector,RandomForestClassifier,RandomForestClassificationModel>

org.apache.spark.ml.classification.RandomForestClassifier

All Implemented Interfaces:

java.io.Serializable, Logging, ClassifierParams, ProbabilisticClassifierParams, Params, HasCheckpointInterval, HasFeaturesCol, HasLabelCol, HasPredictionCol, HasProbabilityCol, HasRawPredictionCol, HasSeed, HasThresholds, PredictorParams, DecisionTreeParams, RandomForestClassifierParams, RandomForestParams, TreeClassifierParams, TreeEnsembleParams, DefaultParamsWritable, Identifiable, MLWritable

public class RandomForestClassifier
extends ProbabilisticClassifier<Vector,RandomForestClassifier,RandomForestClassificationModel>
implements RandomForestClassifierParams, DefaultParamsWritable

Random Forest learning algorithm for classification. It supports both binary and multiclass labels, as well as both continuous and categorical features.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
RandomForestClassifier()
RandomForestClassifier(String uid)

Method Summary

Modifier and Type	Method and Description
RandomForestClassifier	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
static RandomForestClassifier	load(String path)
static MLReader<T>	read()
RandomForestClassifier	setCacheNodeIds(boolean value)
RandomForestClassifier	setCheckpointInterval(int value) Specifies how often to checkpoint the cached node IDs.
RandomForestClassifier	setFeatureSubsetStrategy(String value)
RandomForestClassifier	setImpurity(String value)
RandomForestClassifier	setMaxBins(int value)
RandomForestClassifier	setMaxDepth(int value)
RandomForestClassifier	setMaxMemoryInMB(int value)
RandomForestClassifier	setMinInfoGain(double value)
RandomForestClassifier	setMinInstancesPerNode(int value)
RandomForestClassifier	setNumTrees(int value)
RandomForestClassifier	setSeed(long value)
RandomForestClassifier	setSubsamplingRate(double value)
static String[]	supportedFeatureSubsetStrategies() Accessor for supported featureSubsetStrategy settings: auto, all, onethird, sqrt, log2
static String[]	supportedImpurities() Accessor for supported impurity settings: entropy, gini
String	uid() An immutable unique ID for the object and its derivatives.

Methods inherited from class org.apache.spark.ml.classification.ProbabilisticClassifier

setProbabilityCol, setThresholds

Methods inherited from class org.apache.spark.ml.classification.Classifier

setRawPredictionCol

Methods inherited from class org.apache.spark.ml.Predictor

fit, setFeaturesCol, setLabelCol, setPredictionCol, transformSchema

Methods inherited from class org.apache.spark.ml.Estimator

fit, fit, fit, fit

Methods inherited from class Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

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

getNumTrees, numTrees

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

featureSubsetStrategy, getFeatureSubsetStrategy, getOldStrategy, getSubsamplingRate, subsamplingRate

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

cacheNodeIds, getCacheNodeIds, getMaxBins, getMaxDepth, getMaxMemoryInMB, getMinInfoGain, getMinInstancesPerNode, getOldStrategy, maxBins, maxDepth, maxMemoryInMB, minInfoGain, minInstancesPerNode

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

validateAndTransformSchema

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

getLabelCol, labelCol

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

featuresCol, getFeaturesCol

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

getPredictionCol, predictionCol

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

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

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

toString

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

checkpointInterval, getCheckpointInterval

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

getSeed, seed

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

getImpurity, getOldImpurity, impurity

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

write

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

save

Methods inherited from interface org.apache.spark.ml.classification.ProbabilisticClassifierParams

validateAndTransformSchema

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

getRawPredictionCol, rawPredictionCol

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

getProbabilityCol, probabilityCol

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

getThresholds, thresholds

Methods inherited from interface org.apache.spark.internal.Logging

initializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

Constructor Detail

RandomForestClassifier

public RandomForestClassifier(String uid)

RandomForestClassifier

public RandomForestClassifier()

Method Detail

supportedImpurities

public static final String[] supportedImpurities()

Accessor for supported impurity settings: entropy, gini

supportedFeatureSubsetStrategies

public static final String[] supportedFeatureSubsetStrategies()

Accessor for supported featureSubsetStrategy settings: auto, all, onethird, sqrt, log2

load

public static RandomForestClassifier load(String path)

read

public static MLReader<T> read()

uid

public String uid()

Description copied from interface: Identifiable

An immutable unique ID for the object and its derivatives.

Specified by:

uid in interface Identifiable

Returns:

(undocumented)

setMaxDepth

public RandomForestClassifier setMaxDepth(int value)

Specified by:

setMaxDepth in interface DecisionTreeParams

Parameters:

value - (undocumented)

Returns:

(undocumented)

setMaxBins

public RandomForestClassifier setMaxBins(int value)

Specified by:

setMaxBins in interface DecisionTreeParams

Parameters:

value - (undocumented)

Returns:

(undocumented)

setMinInstancesPerNode

public RandomForestClassifier setMinInstancesPerNode(int value)

Specified by:

setMinInstancesPerNode in interface DecisionTreeParams

Parameters:

value - (undocumented)

Returns:

(undocumented)

setMinInfoGain

public RandomForestClassifier setMinInfoGain(double value)

Specified by:

setMinInfoGain in interface DecisionTreeParams

Parameters:

value - (undocumented)

Returns:

(undocumented)

setMaxMemoryInMB

public RandomForestClassifier setMaxMemoryInMB(int value)

Specified by:

setMaxMemoryInMB in interface DecisionTreeParams

Parameters:

value - (undocumented)

Returns:

(undocumented)

setCacheNodeIds

public RandomForestClassifier setCacheNodeIds(boolean value)

Specified by:

setCacheNodeIds in interface DecisionTreeParams

Parameters:

value - (undocumented)

Returns:

(undocumented)

setCheckpointInterval

public RandomForestClassifier setCheckpointInterval(int value)

Specifies how often to checkpoint the cached node IDs. E.g. 10 means that the cache will get checkpointed every 10 iterations. This is only used if cacheNodeIds is true and if the checkpoint directory is set in SparkContext. Must be at least 1. (default = 10)

Specified by:

setCheckpointInterval in interface DecisionTreeParams

Parameters:

value - (undocumented)

Returns:

(undocumented)

setImpurity

public RandomForestClassifier setImpurity(String value)

Specified by:

setImpurity in interface TreeClassifierParams

Parameters:

value - (undocumented)

Returns:

(undocumented)

setSubsamplingRate

public RandomForestClassifier setSubsamplingRate(double value)

Specified by:

setSubsamplingRate in interface TreeEnsembleParams

Parameters:

value - (undocumented)

Returns:

(undocumented)

setSeed

public RandomForestClassifier setSeed(long value)

Specified by:

setSeed in interface DecisionTreeParams

Parameters:

value - (undocumented)

Returns:

(undocumented)

setNumTrees

public RandomForestClassifier setNumTrees(int value)

Specified by:

setNumTrees in interface RandomForestParams

Parameters:

value - (undocumented)

Returns:

(undocumented)

setFeatureSubsetStrategy

public RandomForestClassifier setFeatureSubsetStrategy(String value)

Specified by:

setFeatureSubsetStrategy in interface TreeEnsembleParams

Parameters:

value - (undocumented)

Returns:

(undocumented)

copy

public RandomForestClassifier copy(ParamMap extra)

Description copied from interface: Params

Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. See defaultCopy().

Specified by:

copy in interface Params

Specified by:

copy in class Predictor<Vector,RandomForestClassifier,RandomForestClassificationModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)