org.apache.spark.mllib.feature

StandardScalerModel

class StandardScalerModel extends VectorTransformer

:: Experimental :: Represents a StandardScaler model that can transform vectors.

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@Experimental()
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VectorTransformer, Serializable, Serializable, AnyRef, Any
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  1. StandardScalerModel
  2. VectorTransformer
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Instance Constructors

  1. new StandardScalerModel(std: Vector)

  2. new StandardScalerModel(std: Vector, mean: Vector)

  3. new StandardScalerModel(std: Vector, mean: Vector, withStd: Boolean, withMean: Boolean)

    std

    column standard deviation values

    mean

    column mean values

    withStd

    whether to scale the data to have unit standard deviation

    withMean

    whether to center the data before scaling

Value Members

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

    Definition Classes
    AnyRef

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

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  3. final def ##(): Int

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    AnyRef → Any

  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

    Attributes
    protected[java.lang]
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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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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )

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

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  12. def hashCode(): Int

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  13. final def isInstanceOf[T0]: Boolean

    Definition Classes
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  14. val mean: Vector

    column mean values

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

    Definition Classes
    AnyRef

  16. final def notify(): Unit

    Definition Classes
    AnyRef

  17. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  18. def setWithMean(withMean: Boolean): StandardScalerModel.this.type

    Annotations
    @DeveloperApi()

  19. def setWithStd(withStd: Boolean): StandardScalerModel.this.type

    Annotations
    @DeveloperApi()

  20. val std: Vector

    column standard deviation values

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

    Definition Classes
    AnyRef

  22. def toString(): String

    Definition Classes
    AnyRef → Any

  23. def transform(vector: Vector): Vector

    Applies standardization transformation on a vector.

    Applies standardization transformation on a vector.

    vector

    Vector to be standardized.

    returns

    Standardized vector. If the std of a column is zero, it will return default 0.0 for the column with zero std.

    Definition Classes
    StandardScalerModel → VectorTransformer

  24. def transform(data: JavaRDD[Vector]): JavaRDD[Vector]

    Applies transformation on an JavaRDD[Vector].

    Applies transformation on an JavaRDD[Vector].

    data

    JavaRDD[Vector] to be transformed.

    returns

    transformed JavaRDD[Vector].

    Definition Classes
    VectorTransformer

  25. def transform(data: RDD[Vector]): RDD[Vector]

    Applies transformation on an RDD[Vector].

    Applies transformation on an RDD[Vector].

    data

    RDD[Vector] to be transformed.

    returns

    transformed RDD[Vector].

    Definition Classes
    VectorTransformer

  26. final def wait(): Unit

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    @throws( ... )

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

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    @throws( ... )

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

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  29. var withMean: Boolean

    whether to center the data before scaling

  30. var withStd: Boolean

    whether to scale the data to have unit standard deviation

Inherited from VectorTransformer

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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