Class

com.microsoft.ml.spark.schema

CategoricalMap

Related Doc: package schema

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class CategoricalMap[T] extends Serializable

A wrapper around level maps: Map[T -> Int] and Map[Int -> T] that converts the data to/from Spark Metadata in both MLib and AzreML formats.

T

Input levels could be String, Double, Int, Long, Boolean

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Instance Constructors

  1. new CategoricalMap(levels: Array[T], isOrdinal: Boolean = false, hasNullLevel: Boolean = false)

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    levels

    The level values are assumed to be already sorted as needed

    isOrdinal

    A flag that indicates if the data are ordinal

Value Members

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

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    Definition Classes
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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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    Attributes
    protected[java.lang]
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    @throws( ... )
  6. val dataType: DataType

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    Spark DataType correspondint to type T

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

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  8. def equals(arg0: Any): Boolean

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  9. def finalize(): Unit

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    Attributes
    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  10. final def getClass(): Class[_]

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    Definition Classes
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  11. def getIndex(level: T): Int

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    Returns the index of the given level, can throw

  12. def getIndexOption(level: T): Option[Int]

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    Returns the index of a given level as Option; does not throw

  13. def getLevel(index: Int): T

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    Returns the level of the given index; can throw

  14. def getLevelOption(index: Int): Option[T]

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    Returns the level of the given index as Option; does not throw

  15. def hasLevel(level: T): Boolean

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    Checks if the given level exists

  16. val hasNullLevel: Boolean

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  17. def hashCode(): Int

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  18. final def isInstanceOf[T0]: Boolean

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  19. val isOrdinal: Boolean

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    A flag that indicates if the data are ordinal

  20. val levels: Array[T]

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    The level values are assumed to be already sorted as needed

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

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    Definition Classes
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  22. final def notify(): Unit

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  23. final def notifyAll(): Unit

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    AnyRef
  24. val numLevels: Int

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    Total number of levels

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

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    Definition Classes
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  26. def toMetadata(mmlStyle: Boolean): Metadata

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    Add categorical levels and in either MML or MLlib style metadata

    Add categorical levels and in either MML or MLlib style metadata

    mmlStyle

    MML (true) or MLlib metadata (false)

  27. def toMetadata(existingMetadata: Metadata, mmlStyle: Boolean): Metadata

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    Add categorical levels to existing Spark Metadata

    Add categorical levels to existing Spark Metadata

    existingMetadata

    [tag, categorical metadata] pair is added to existingMetadata, where tag is either MLlib or MML

    mmlStyle

    MML (true) or MLlib metadata (false)

  28. def toString(): String

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    Definition Classes
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  29. final def wait(): Unit

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    @throws( ... )
  30. final def wait(arg0: Long, arg1: Int): Unit

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

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Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Members