Class

com.salesforce.op.filters

RawFeatureFilterMetrics

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case class RawFeatureFilterMetrics(name: String, trainingFillRate: Double, trainingNullLabelAbsoluteCorr: Option[Double], scoringFillRate: Option[Double], jsDivergence: Option[Double], fillRateDiff: Option[Double], fillRatioDiff: Option[Double]) extends Product with Serializable

Contains raw feature metrics computing in Raw Feature Filter

name

feature name

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

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Instance Constructors

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

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    name

    feature name

    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

  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. val fillRateDiff: Option[Double]

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    absolute difference in fill rates between the training and scoring distributions

  8. val fillRatioDiff: Option[Double]

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

  9. def finalize(): Unit

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

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  11. final def isInstanceOf[T0]: Boolean

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  12. val jsDivergence: Option[Double]

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

  13. val name: String

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    feature name

  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. val scoringFillRate: Option[Double]

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    proportion of values that are null in the scoring distribution

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

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  19. val trainingFillRate: Double

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    proportion of values that are null in the training distribution

  20. val trainingNullLabelAbsoluteCorr: Option[Double]

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    correlation between null indicator and the label in the training distribution

  21. final def wait(): Unit

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

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

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