Class

com.salesforce.op.stages.impl.preparators

CategoricalGroupStats

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case class CategoricalGroupStats(group: String, categoricalFeatures: Array[String], contingencyMatrix: Type, pointwiseMutualInfo: Type, cramersV: Double, mutualInfo: Double, maxRuleConfidences: Array[Double], supports: Array[Double]) extends MetadataLike with Product with Serializable

Container for categorical stats coming from a single group (and therefore a single contingency matrix)

group

Indicator group for this contingency matrix

categoricalFeatures

Array of categorical features belonging to this group

contingencyMatrix

Contingency matrix for this feature group

pointwiseMutualInfo

Matrix of PMI values in Map form (label -> PMI values)

cramersV

Cramer's V value for this feature group (how strongly correlated is it with the label)

mutualInfo

Mutual info value for this feature group

maxRuleConfidences

Array (one value per contingency matrix row) containing the largest association rule confidence for that row (over all the labels)

supports

Array (one value per contingency matrix row) containing the supports for each categorical choice (fraction of dats in which it is chosen)

Linear Supertypes
Serializable, Serializable, Product, Equals, MetadataLike, AnyRef, Any
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  1. CategoricalGroupStats
  2. Serializable
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  4. Product
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Instance Constructors

  1. new CategoricalGroupStats(group: String, categoricalFeatures: Array[String], contingencyMatrix: Type, pointwiseMutualInfo: Type, cramersV: Double, mutualInfo: Double, maxRuleConfidences: Array[Double], supports: Array[Double])

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    group

    Indicator group for this contingency matrix

    categoricalFeatures

    Array of categorical features belonging to this group

    contingencyMatrix

    Contingency matrix for this feature group

    pointwiseMutualInfo

    Matrix of PMI values in Map form (label -> PMI values)

    cramersV

    Cramer's V value for this feature group (how strongly correlated is it with the label)

    mutualInfo

    Mutual info value for this feature group

    maxRuleConfidences

    Array (one value per contingency matrix row) containing the largest association rule confidence for that row (over all the labels)

    supports

    Array (one value per contingency matrix row) containing the supports for each categorical choice (fraction of dats in which it is chosen)

Value Members

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

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    AnyRef → Any

  4. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  5. val categoricalFeatures: Array[String]

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    Array of categorical features belonging to this group

  6. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  7. val contingencyMatrix: Type

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    Contingency matrix for this feature group

  8. val cramersV: Double

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    Cramer's V value for this feature group (how strongly correlated is it with the label)

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

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    Definition Classes
    AnyRef

  10. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

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

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    Definition Classes
    AnyRef → Any

  12. val group: String

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    Indicator group for this contingency matrix

  13. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  14. val maxRuleConfidences: Array[Double]

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    Array (one value per contingency matrix row) containing the largest association rule confidence for that row (over all the labels)

  15. val mutualInfo: Double

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    Mutual info value for this feature group

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

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    Definition Classes
    AnyRef

  17. final def notify(): Unit

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    Definition Classes
    AnyRef

  18. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  19. val pointwiseMutualInfo: Type

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    Matrix of PMI values in Map form (label -> PMI values)

  20. val supports: Array[Double]

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    Array (one value per contingency matrix row) containing the supports for each categorical choice (fraction of dats in which it is chosen)

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

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    Definition Classes
    AnyRef

  22. def toMetadata(skipUnsupported: Boolean): Metadata

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    Converts to Metadata

    Converts to Metadata

    skipUnsupported

    skip unsupported values

    returns

    Metadata metadata

    Definition Classes
    CategoricalGroupStats → MetadataLike
    Exceptions thrown

    RuntimeException in case of unsupported value type

  23. def toMetadata(): Metadata

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    Converts to Metadata

    Converts to Metadata

    returns

    Metadata metadata

    Definition Classes
    MetadataLike
    Exceptions thrown

    RuntimeException in case of unsupported value type

  24. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
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    Annotations
    @throws( ... )

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from MetadataLike

Inherited from AnyRef

Inherited from Any

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