org.apache.spark.ml.classification

Class RandomForestClassifier

Object

org.apache.spark.ml.PipelineStage

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

org.apache.spark.ml.Predictor<Vector,RandomForestClassifier,RandomForestClassificationModel>

org.apache.spark.ml.classification.RandomForestClassifier

All Implemented Interfaces:

java.io.Serializable, Logging, Params

public final class RandomForestClassifier
extends Predictor<Vector,RandomForestClassifier,RandomForestClassificationModel>

:: Experimental :: 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

Methods

Modifier and Type	Method and Description
RandomForestClassifier	setCacheNodeIds(boolean value)
RandomForestClassifier	setCheckpointInterval(int value)
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()
StructType	validateAndTransformSchema(StructType schema, boolean fitting, DataType featuresDataType) Validates and transforms the input schema with the provided param map.

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

copy, 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.param.Params

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

Methods inherited from interface org.apache.spark.Logging

initializeIfNecessary, initializeLogging, 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

uid

public String uid()

setMaxDepth

public RandomForestClassifier setMaxDepth(int value)

setMaxBins

public RandomForestClassifier setMaxBins(int value)

setMinInstancesPerNode

public RandomForestClassifier setMinInstancesPerNode(int value)

setMinInfoGain

public RandomForestClassifier setMinInfoGain(double value)

setMaxMemoryInMB

public RandomForestClassifier setMaxMemoryInMB(int value)

setCacheNodeIds

public RandomForestClassifier setCacheNodeIds(boolean value)

setCheckpointInterval

public RandomForestClassifier setCheckpointInterval(int value)

setImpurity

public RandomForestClassifier setImpurity(String value)

setSubsamplingRate

public RandomForestClassifier setSubsamplingRate(double value)

setSeed

public RandomForestClassifier setSeed(long value)

setNumTrees

public RandomForestClassifier setNumTrees(int value)

setFeatureSubsetStrategy

public RandomForestClassifier setFeatureSubsetStrategy(String value)

validateAndTransformSchema

public StructType validateAndTransformSchema(StructType schema,
                                    boolean fitting,
                                    DataType featuresDataType)

Validates and transforms the input schema with the provided param map.

Parameters:

schema - input schema

fitting - whether this is in fitting

featuresDataType - SQL DataType for FeaturesType. E.g., VectorUDT for vector features.

Returns:

output schema