FeatureDistributionLike

abstract val count: Long

total count of feature seen

abstract val distribution: Array[Double]

binned counts of feature values (hashed for strings, evenly spaced bins for numerics)

abstract val key: Option[String]

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

abstract val name: String

name of the feature

abstract val nulls: Long

number of empties seen in feature

abstract val summaryInfo: Array[Double]

either min and max number of tokens for text data, or number of splits used for bins for numeric data

abstract val type: FeatureDistributionType

feature distribution type: training or scoring

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

def equals(arg0: Any): Boolean

def finalize(): Unit

final def getClass(): Class[_]

def hashCode(): Int

final def isInstanceOf[T0]: Boolean

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

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

def toString(): String

final def wait(): Unit

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

final def wait(arg0: Long): Unit