OpRandomForestRegressorParams

Abstract Value Members

abstract def copy(extra: ParamMap): Params

Definition Classes

Params
abstract val uid: String

Definition Classes

Identifiable

Concrete Value Members

final def !=(arg0: Any): Boolean

Definition Classes

AnyRef → Any
final def ##(): Int

Definition Classes

AnyRef → Any
final def $[T](param: Param[T]): T

Attributes

protected

Definition Classes

Params
final def ==(arg0: Any): Boolean

Definition Classes

AnyRef → Any
final def asInstanceOf[T0]: T0

Definition Classes

Any
final val cacheNodeIds: BooleanParam

Definition Classes

DecisionTreeParams
final val checkpointInterval: IntParam

Definition Classes

HasCheckpointInterval
final def clear(param: Param[_]): OpRandomForestRegressorParams.this.type

Definition Classes

Params
def clone(): AnyRef

Attributes

protected[java.lang]

Definition Classes

AnyRef

Annotations

@throws( ... )
def copyValues[T <: Params](to: T, extra: ParamMap): T

Attributes

protected

Definition Classes

Params
final def defaultCopy[T <: Params](extra: ParamMap): T

Attributes

protected

Definition Classes

Params
final def eq(arg0: AnyRef): Boolean

Definition Classes

AnyRef
def equals(arg0: Any): Boolean

Definition Classes

AnyRef → Any
def explainParam(param: Param[_]): String

Definition Classes

Params
def explainParams(): String

Definition Classes

Params
final def extractParamMap(): ParamMap

Definition Classes

Params
final def extractParamMap(extra: ParamMap): ParamMap

Definition Classes

Params
final val featureSubsetStrategy: Param[String]

Definition Classes

TreeEnsembleParams
final val featuresCol: Param[String]

Definition Classes

HasFeaturesCol
def finalize(): Unit

Attributes

protected[java.lang]

Definition Classes

AnyRef

Annotations

@throws( classOf[java.lang.Throwable] )
final def get[T](param: Param[T]): Option[T]

Definition Classes

Params
final def getCacheNodeIds: Boolean

Definition Classes

DecisionTreeParams
final def getCheckpointInterval: Int

Definition Classes

HasCheckpointInterval
final def getClass(): Class[_]

Definition Classes

AnyRef → Any
final def getDefault[T](param: Param[T]): Option[T]

Definition Classes

Params
final def getFeatureSubsetStrategy: String

Definition Classes

TreeEnsembleParams
final def getFeaturesCol: String

Definition Classes

HasFeaturesCol
final def getImpurity: String

Definition Classes

TreeRegressorParams
final def getLabelCol: String

Definition Classes

HasLabelCol
final def getMaxBins: Int

Definition Classes

DecisionTreeParams
final def getMaxDepth: Int

Definition Classes

DecisionTreeParams
final def getMaxMemoryInMB: Int

Definition Classes

DecisionTreeParams
final def getMinInfoGain: Double

Definition Classes

DecisionTreeParams
final def getMinInstancesPerNode: Int

Definition Classes

DecisionTreeParams
final def getNumTrees: Int

Definition Classes

RandomForestParams
final def getOrDefault[T](param: Param[T]): T

Definition Classes

Params
def getParam(paramName: String): Param[Any]

Definition Classes

Params
final def getPredictionCol: String

Definition Classes

HasPredictionCol
final def getSeed: Long

Definition Classes

HasSeed
final def getSubsamplingRate: Double

Definition Classes

TreeEnsembleParams
final def hasDefault[T](param: Param[T]): Boolean

Definition Classes

Params
def hasParam(paramName: String): Boolean

Definition Classes

Params
def hashCode(): Int

Definition Classes

AnyRef → Any
final val impurity: Param[String]

Definition Classes

TreeRegressorParams
final def isDefined(param: Param[_]): Boolean

Definition Classes

Params
final def isInstanceOf[T0]: Boolean

Definition Classes

Any
final def isSet(param: Param[_]): Boolean

Definition Classes

Params
final val labelCol: Param[String]

Definition Classes

HasLabelCol
final val maxBins: IntParam

Definition Classes

DecisionTreeParams
final val maxDepth: IntParam

Definition Classes

DecisionTreeParams
final val maxMemoryInMB: IntParam

Definition Classes

DecisionTreeParams
final val minInfoGain: DoubleParam

Definition Classes

DecisionTreeParams
final val minInstancesPerNode: IntParam

Definition Classes

DecisionTreeParams
final def ne(arg0: AnyRef): Boolean

Definition Classes

AnyRef
final def notify(): Unit

Definition Classes

AnyRef
final def notifyAll(): Unit

Definition Classes

AnyRef
final val numTrees: IntParam

Definition Classes

RandomForestParams
lazy val params: Array[Param[_]]

Definition Classes

Params
final val predictionCol: Param[String]

Definition Classes

HasPredictionCol
final val seed: LongParam

Definition Classes

HasSeed
final def set(paramPair: ParamPair[_]): OpRandomForestRegressorParams.this.type

Attributes

protected

Definition Classes

Params
final def set(param: String, value: Any): OpRandomForestRegressorParams.this.type

Attributes

protected

Definition Classes

Params
final def set[T](param: Param[T], value: T): OpRandomForestRegressorParams.this.type

Definition Classes

Params
final def setDefault(paramPairs: ParamPair[_]*): OpRandomForestRegressorParams.this.type

Attributes

protected

Definition Classes

Params
final def setDefault[T](param: Param[T], value: T): OpRandomForestRegressorParams.this.type

Attributes

protected

Definition Classes

Params
final val subsamplingRate: DoubleParam

Definition Classes

TreeEnsembleParams
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes

AnyRef
def toString(): String

Definition Classes

Identifiable → AnyRef → Any
def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType

Attributes

protected

Definition Classes

PredictorParams
final def wait(): Unit

Definition Classes

AnyRef

Annotations

@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes

AnyRef

Annotations

@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes

AnyRef

Annotations

@throws( ... )

Deprecated Value Members

def setCacheNodeIds(value: Boolean): OpRandomForestRegressorParams.this.type

Definition Classes

DecisionTreeParams

Annotations

@deprecated

Deprecated

(Since version 2.1.0) This method is deprecated and will be removed in 3.0.0.
def setCheckpointInterval(value: Int): OpRandomForestRegressorParams.this.type

Definition Classes

DecisionTreeParams

Annotations

@deprecated

Deprecated

(Since version 2.1.0) This method is deprecated and will be removed in 3.0.0.
def setFeatureSubsetStrategy(value: String): OpRandomForestRegressorParams.this.type

Definition Classes

TreeEnsembleParams

Annotations

@deprecated

Deprecated

(Since version 2.1.0) This method is deprecated and will be removed in 3.0.0.
def setImpurity(value: String): OpRandomForestRegressorParams.this.type

Definition Classes

TreeRegressorParams

Annotations

@deprecated

Deprecated

(Since version 2.1.0) This method is deprecated and will be removed in 3.0.0.
def setMaxBins(value: Int): OpRandomForestRegressorParams.this.type

Definition Classes

DecisionTreeParams

Annotations

@deprecated

Deprecated

(Since version 2.1.0) This method is deprecated and will be removed in 3.0.0.
def setMaxDepth(value: Int): OpRandomForestRegressorParams.this.type

Definition Classes

DecisionTreeParams

Annotations

@deprecated

Deprecated

(Since version 2.1.0) This method is deprecated and will be removed in 3.0.0.
def setMaxMemoryInMB(value: Int): OpRandomForestRegressorParams.this.type

Definition Classes

DecisionTreeParams

Annotations

@deprecated

Deprecated

(Since version 2.1.0) This method is deprecated and will be removed in 3.0.0.
def setMinInfoGain(value: Double): OpRandomForestRegressorParams.this.type

Definition Classes

DecisionTreeParams

Annotations

@deprecated

Deprecated

(Since version 2.1.0) This method is deprecated and will be removed in 3.0.0.
def setMinInstancesPerNode(value: Int): OpRandomForestRegressorParams.this.type

Definition Classes

DecisionTreeParams

Annotations

@deprecated

Deprecated

(Since version 2.1.0) This method is deprecated and will be removed in 3.0.0.
def setNumTrees(value: Int): OpRandomForestRegressorParams.this.type

Definition Classes

RandomForestParams

Annotations

@deprecated

Deprecated

(Since version 2.1.0) This method is deprecated and will be removed in 3.0.0.
def setSeed(value: Long): OpRandomForestRegressorParams.this.type

Definition Classes

DecisionTreeParams

Annotations

@deprecated

Deprecated

(Since version 2.1.0) This method is deprecated and will be removed in 3.0.0.
def setSubsamplingRate(value: Double): OpRandomForestRegressorParams.this.type

Definition Classes

TreeEnsembleParams

Annotations

@deprecated

Deprecated

(Since version 2.1.0) This method is deprecated and will be removed in 3.0.0.

Related Doc: package regression

trait OpRandomForestRegressorParams extends RandomForestRegressorParams

Abstract Value Members

abstract def copy(extra: ParamMap): Params

abstract val uid: String

Concrete Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def $[T](param: Param[T]): T

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

final val cacheNodeIds: BooleanParam

final val checkpointInterval: IntParam

final def clear(param: Param[_]): OpRandomForestRegressorParams.this.type

def clone(): AnyRef

def copyValues[T <: Params](to: T, extra: ParamMap): T

final def defaultCopy[T <: Params](extra: ParamMap): T

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def explainParam(param: Param[_]): String

def explainParams(): String

final def extractParamMap(): ParamMap

final def extractParamMap(extra: ParamMap): ParamMap

final val featureSubsetStrategy: Param[String]

final val featuresCol: Param[String]

def finalize(): Unit

final def get[T](param: Param[T]): Option[T]

final def getCacheNodeIds: Boolean

final def getCheckpointInterval: Int

final def getClass(): Class[_]

final def getDefault[T](param: Param[T]): Option[T]

final def getFeatureSubsetStrategy: String

final def getFeaturesCol: String

final def getImpurity: String

final def getLabelCol: String

final def getMaxBins: Int

final def getMaxDepth: Int

final def getMaxMemoryInMB: Int

final def getMinInfoGain: Double

final def getMinInstancesPerNode: Int

final def getNumTrees: Int

final def getOrDefault[T](param: Param[T]): T

def getParam(paramName: String): Param[Any]

final def getPredictionCol: String

final def getSeed: Long

final def getSubsamplingRate: Double

final def hasDefault[T](param: Param[T]): Boolean

def hasParam(paramName: String): Boolean

def hashCode(): Int

final val impurity: Param[String]

final def isDefined(param: Param[_]): Boolean

final def isInstanceOf[T0]: Boolean

final def isSet(param: Param[_]): Boolean

final val labelCol: Param[String]

final val maxBins: IntParam

final val maxDepth: IntParam

final val maxMemoryInMB: IntParam

final val minInfoGain: DoubleParam

final val minInstancesPerNode: IntParam

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

final val numTrees: IntParam

lazy val params: Array[Param[_]]

final val predictionCol: Param[String]

final val seed: LongParam

final def set(paramPair: ParamPair[_]): OpRandomForestRegressorParams.this.type

final def set(param: String, value: Any): OpRandomForestRegressorParams.this.type

final def set[T](param: Param[T], value: T): OpRandomForestRegressorParams.this.type

final def setDefault(paramPairs: ParamPair[_]*): OpRandomForestRegressorParams.this.type

final def setDefault[T](param: Param[T], value: T): OpRandomForestRegressorParams.this.type

final val subsamplingRate: DoubleParam

final def synchronized[T0](arg0: ⇒ T0): T0

def toString(): String

def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

Deprecated Value Members