Class

com.salesforce.op.dsl.RichNumericFeature

RichBinaryFeature

Related Doc: package RichNumericFeature

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implicit class RichBinaryFeature extends AnyRef

Enrichment functions for Binary Feature

Linear Supertypes
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Instance Constructors

  1. new RichBinaryFeature(f: FeatureLike[Binary])

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    f

    FeatureLike

Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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  6. final def eq(arg0: AnyRef): Boolean

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  7. def equals(arg0: Any): Boolean

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  8. val f: FeatureLike[Binary]

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    FeatureLike

  9. def fillMissingWithMean(default: Double = 0.0): FeatureLike[RealNN]

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    Fill missing values with mean

    Fill missing values with mean

    default

    default value is the whole feature is filled with missing values

    returns

    transformed feature of type RealNN

  10. def finalize(): Unit

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  11. final def getClass(): Class[_]

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  12. def hashCode(): Int

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  13. final def isInstanceOf[T0]: Boolean

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  14. final def ne(arg0: AnyRef): Boolean

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  15. final def notify(): Unit

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  16. final def notifyAll(): Unit

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

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  18. def toString(): String

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  19. def vectorize(fillValue: Boolean, trackNulls: Boolean, others: Array[FeatureLike[Binary]] = Array.empty): FeatureLike[OPVector]

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    Apply binary vectorizer

    Apply binary vectorizer

    fillValue

    value to pull in place of nulls

    trackNulls

    keep tract of when nulls occurs by adding a second column to the vector with a null indicator

    others

    other features of same type

  20. final def wait(): Unit

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

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  22. final def wait(arg0: Long): Unit

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