org.apache.spark.mllib.tree.impurity

Impurity

trait Impurity extends Serializable

:: Experimental :: Trait for calculating information gain.

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@Experimental()
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Serializable, Serializable, AnyRef, Any
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Entropy, Gini, Variance
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Abstract Value Members

  1. abstract def calculate(count: Double, sum: Double, sumSquares: Double): Double

    :: DeveloperApi :: information calculation for regression

    :: DeveloperApi :: information calculation for regression

    count

    number of instances

    sum

    sum of labels

    sumSquares

    summation of squares of the labels

    returns

    information value

    Annotations
    @DeveloperApi()

  2. abstract def calculate(c0: Double, c1: Double): Double

    :: DeveloperApi :: information calculation for binary classification

    :: DeveloperApi :: information calculation for binary classification

    c0

    count of instances with label 0

    c1

    count of instances with label 1

    returns

    information value

    Annotations
    @DeveloperApi()

Concrete Value Members

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

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

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  3. final def ##(): Int

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  4. final def ==(arg0: AnyRef): Boolean

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

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  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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    @throws( ... )

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

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  9. def equals(arg0: Any): Boolean

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  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. final def wait(): Unit

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

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

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