org.apache.spark.mllib.feature

ChiSqSelector

class ChiSqSelector extends Serializable

Creates a ChiSquared feature selector. The selector supports different selection methods: numTopFeatures, percentile, fpr.

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@Since( "1.3.0" )
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Instance Constructors

  1. new ChiSqSelector(numTopFeatures: Int)

    The is the same to call this() and setNumTopFeatures(numTopFeatures)

    The is the same to call this() and setNumTopFeatures(numTopFeatures)

    Annotations
    @Since( "1.3.0" )
  2. new ChiSqSelector()

    Annotations
    @Since( "2.1.0" )

Value Members

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

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  7. def clone(): AnyRef

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  10. def finalize(): Unit

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  11. def fit(data: RDD[LabeledPoint]): ChiSqSelectorModel

    Returns a ChiSquared feature selector.

    Returns a ChiSquared feature selector.

    data

    an RDD[LabeledPoint] containing the labeled dataset with categorical features. Real-valued features will be treated as categorical for each distinct value. Apply feature discretizer before using this function.

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    @Since( "1.3.0" )
  12. var fpr: Double

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

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  14. def hashCode(): Int

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  17. final def notify(): Unit

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  18. final def notifyAll(): Unit

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  19. var numTopFeatures: Int

  20. var percentile: Double

  21. var selectorType: String

  22. def setFpr(value: Double): ChiSqSelector.this.type

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    @Since( "2.1.0" )
  23. def setNumTopFeatures(value: Int): ChiSqSelector.this.type

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    @Since( "1.6.0" )
  24. def setPercentile(value: Double): ChiSqSelector.this.type

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    @Since( "2.1.0" )
  25. def setSelectorType(value: String): ChiSqSelector.this.type

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    @Since( "2.1.0" )
  26. final def synchronized[T0](arg0: ⇒ T0): T0

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  27. def toString(): String

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