Class

org.apache.spark.mllib.feature

StandardScalerModel

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class StandardScalerModel extends VectorTransformer

Represents a StandardScaler model that can transform vectors.

Annotations
@Since( "1.1.0" )
Source
StandardScaler.scala
Linear Supertypes
VectorTransformer, Serializable, Serializable, AnyRef, Any
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  1. StandardScalerModel
  2. VectorTransformer
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Instance Constructors

  1. new StandardScalerModel(std: Vector)

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    @Since( "1.3.0" )
  2. new StandardScalerModel(std: Vector, mean: Vector)

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    @Since( "1.3.0" )
  3. new StandardScalerModel(std: Vector, mean: Vector, withStd: Boolean, withMean: Boolean)

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    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

    Annotations
    @Since( "1.3.0" )

Value Members

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

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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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    protected[java.lang]
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    @throws( ... )
  6. final def eq(arg0: AnyRef): Boolean

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  7. def equals(arg0: Any): Boolean

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  8. def finalize(): Unit

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

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  10. def hashCode(): Int

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  11. final def isInstanceOf[T0]: Boolean

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  12. val mean: Vector

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    column mean values

    column mean values

    Annotations
    @Since( "1.1.0" )
  13. final def ne(arg0: AnyRef): Boolean

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    AnyRef
  14. final def notify(): Unit

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  15. final def notifyAll(): Unit

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

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    Annotations
    @Since( "1.3.0" ) @DeveloperApi()
  17. def setWithStd(withStd: Boolean): StandardScalerModel.this.type

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    Annotations
    @Since( "1.3.0" ) @DeveloperApi()
  18. val std: Vector

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    column standard deviation values

    column standard deviation values

    Annotations
    @Since( "1.3.0" )
  19. final def synchronized[T0](arg0: ⇒ T0): T0

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  20. def toString(): String

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  21. def transform(vector: Vector): Vector

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    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
    StandardScalerModelVectorTransformer
    Annotations
    @Since( "1.1.0" )
  22. def transform(data: JavaRDD[Vector]): JavaRDD[Vector]

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    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
    Annotations
    @Since( "1.1.0" )
  23. def transform(data: RDD[Vector]): RDD[Vector]

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    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
    Annotations
    @Since( "1.1.0" )
  24. final def wait(): Unit

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

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

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    @throws( ... )
  27. var withMean: Boolean

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    whether to center the data before scaling

    whether to center the data before scaling

    Annotations
    @Since( "1.3.0" )
  28. var withStd: Boolean

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    whether to scale the data to have unit standard deviation

    whether to scale the data to have unit standard deviation

    Annotations
    @Since( "1.3.0" )

Inherited from VectorTransformer

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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