org.apache.spark.mllib.feature

Normalizer

class Normalizer extends VectorTransformer

Normalizes samples individually to unit Lp norm

For any 1 <= p < Double.PositiveInfinity, normalizes samples using sum(abs(vector).p)(1/p) as norm.

For p = Double.PositiveInfinity, max(abs(vector)) will be used as norm for normalization.

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

  1. new Normalizer()

    Annotations
    @Since( "1.1.0" )

  2. new Normalizer(p: Double)

    p

    Normalization in Lp space, p = 2 by default.

    Annotations
    @Since( "1.1.0" )

Value Members

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

    Definition Classes
    AnyRef

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

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    Any

  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

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    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

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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

    Definition Classes
    AnyRef → Any

  19. def transform(vector: Vector): Vector

    Applies unit length normalization on a vector.

    Applies unit length normalization on a vector.

    vector

    vector to be normalized.

    returns

    normalized vector. If the norm of the input is zero, it will return the input vector.

    Definition Classes
    Normalizer → VectorTransformer
    Annotations
    @Since( "1.1.0" )

  20. 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
    Annotations
    @Since( "1.1.0" )

  21. 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
    Annotations
    @Since( "1.1.0" )

  22. final def wait(): Unit

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    @throws( ... )

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

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    @throws( ... )

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

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Inherited from VectorTransformer

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

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