RawFeatureFilterMetrics

Contains raw feature metrics computing in Raw Feature Filter

name: feature name
key: map key associated with distribution (when the feature is a map)
trainingFillRate: proportion of values that are null in the training distribution
trainingNullLabelAbsoluteCorr: correlation between null indicator and the label in the training distribution
scoringFillRate: proportion of values that are null in the scoring distribution
jsDivergence: Jensen-Shannon (JS) divergence between the training and scoring distributions
fillRateDiff: absolute difference in fill rates between the training and scoring distributions
fillRatioDiff: ratio of difference in fill rates between the training and scoring distributions

Linear Supertypes

Serializable, Serializable, Product, Equals, AnyRef, Any

Instance Constructors

new RawFeatureFilterMetrics(name: String, key: Option[String], trainingFillRate: Double, trainingNullLabelAbsoluteCorr: Option[Double], scoringFillRate: Option[Double], jsDivergence: Option[Double], fillRateDiff: Option[Double], fillRatioDiff: Option[Double])

name

feature name

key

map key associated with distribution (when the feature is a map)

trainingFillRate

proportion of values that are null in the training distribution

trainingNullLabelAbsoluteCorr

correlation between null indicator and the label in the training distribution

scoringFillRate

proportion of values that are null in the scoring distribution

jsDivergence

Jensen-Shannon (JS) divergence between the training and scoring distributions

fillRateDiff

absolute difference in fill rates between the training and scoring distributions

fillRatioDiff

ratio of difference in fill rates between the training and scoring distributions

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
def clone(): AnyRef

Attributes

protected[java.lang]

Definition Classes

AnyRef

Annotations

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

Definition Classes

AnyRef
val fillRateDiff: Option[Double]

absolute difference in fill rates between the training and scoring distributions
val fillRatioDiff: Option[Double]

ratio of difference in fill rates between the training and scoring distributions
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 jsDivergence: Option[Double]

Jensen-Shannon (JS) divergence between the training and scoring distributions
val key: Option[String]

map key associated with distribution (when the feature is a map)
val name: String

feature name
final def ne(arg0: AnyRef): Boolean

Definition Classes

AnyRef
final def notify(): Unit

Definition Classes

AnyRef
final def notifyAll(): Unit

Definition Classes

AnyRef
val scoringFillRate: Option[Double]

proportion of values that are null in the scoring distribution
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes

AnyRef
val trainingFillRate: Double

proportion of values that are null in the training distribution
val trainingNullLabelAbsoluteCorr: Option[Double]

correlation between null indicator and the label in the training distribution
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 RawFeatureFilterMetrics(name: String, key: Option[String], trainingFillRate: Double, trainingNullLabelAbsoluteCorr: Option[Double], scoringFillRate: Option[Double], jsDivergence: Option[Double], fillRateDiff: Option[Double], fillRatioDiff: Option[Double]) extends Product with Serializable

Instance Constructors

new RawFeatureFilterMetrics(name: String, key: Option[String], trainingFillRate: Double, trainingNullLabelAbsoluteCorr: Option[Double], scoringFillRate: Option[Double], jsDivergence: Option[Double], fillRateDiff: Option[Double], fillRatioDiff: Option[Double])

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

val fillRateDiff: Option[Double]

val fillRatioDiff: Option[Double]

def finalize(): Unit

final def getClass(): Class[_]

final def isInstanceOf[T0]: Boolean

val jsDivergence: Option[Double]

val key: Option[String]

val name: String

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

val scoringFillRate: Option[Double]

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

val trainingFillRate: Double

val trainingNullLabelAbsoluteCorr: Option[Double]

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