FilteredRawData

Contains RFF filtered data, features to drop, and results from RFF

cleanedData: RFF cleaned data
featuresToDrop: raw features dropped by RFF
mapKeysToDrop: keys in map features dropped by RFF
rawFeatureFilterResults: feature information calculated from the training data

Linear Supertypes

Serializable, Serializable, Product, Equals, AnyRef, Any

Instance Constructors

new FilteredRawData(cleanedData: DataFrame, featuresToDrop: Array[OPFeature], mapKeysToDrop: Map[String, Set[String]], rawFeatureFilterResults: RawFeatureFilterResults)

cleanedData

RFF cleaned data

featuresToDrop

raw features dropped by RFF

mapKeysToDrop

keys in map features dropped by RFF

rawFeatureFilterResults

feature information calculated from the training data

Value Members

final def !=(arg0: Any): Boolean

Definition Classes

AnyRef → Any
final def ##(): Int

Definition Classes

AnyRef → Any
final def ==(arg0: Any): Boolean

Definition Classes

AnyRef → Any
final def asInstanceOf[T0]: T0

Definition Classes

Any
val cleanedData: DataFrame

RFF cleaned data
def clone(): AnyRef

Attributes

protected[java.lang]

Definition Classes

AnyRef

Annotations

@throws( ... )
final def eq(arg0: AnyRef): Boolean

Definition Classes

AnyRef
val featuresToDrop: Array[OPFeature]

raw features dropped by RFF
def finalize(): Unit

Attributes

protected[java.lang]

Definition Classes

AnyRef

Annotations

@throws( classOf[java.lang.Throwable] )
final def getClass(): Class[_]

Definition Classes

AnyRef → Any
final def isInstanceOf[T0]: Boolean

Definition Classes

Any
val mapKeysToDrop: Map[String, Set[String]]

keys in map features dropped by RFF
final def ne(arg0: AnyRef): Boolean

Definition Classes

AnyRef
final def notify(): Unit

Definition Classes

AnyRef
final def notifyAll(): Unit

Definition Classes

AnyRef
val rawFeatureFilterResults: RawFeatureFilterResults

feature information calculated from the training data
def scoringFeatureDistributions: Seq[FeatureDistribution]

Feature distributions calculated from the scoring data
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes

AnyRef
def trainingFeatureDistributions: Seq[FeatureDistribution]

Feature distributions calculated from the training data
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( ... )

Related Doc: package filters

case class FilteredRawData(cleanedData: DataFrame, featuresToDrop: Array[OPFeature], mapKeysToDrop: Map[String, Set[String]], rawFeatureFilterResults: RawFeatureFilterResults) extends Product with Serializable

Instance Constructors

new FilteredRawData(cleanedData: DataFrame, featuresToDrop: Array[OPFeature], mapKeysToDrop: Map[String, Set[String]], rawFeatureFilterResults: RawFeatureFilterResults)

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

val cleanedData: DataFrame

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

val featuresToDrop: Array[OPFeature]

def finalize(): Unit

final def getClass(): Class[_]

final def isInstanceOf[T0]: Boolean

val mapKeysToDrop: Map[String, Set[String]]

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

val rawFeatureFilterResults: RawFeatureFilterResults

def scoringFeatureDistributions: Seq[FeatureDistribution]

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

def trainingFeatureDistributions: Seq[FeatureDistribution]

final def wait(): Unit

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

final def wait(arg0: Long): Unit

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from AnyRef

Inherited from Any

Ungrouped