Class

io.github.mandar2812.dynaml.utils

GaussianScaler

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case class GaussianScaler(mean: DenseVector[Double], sigma: DenseVector[Double]) extends ReversibleScaler[DenseVector[Double]] with Product with Serializable

Scales attributes of a vector pattern using the sample mean and variance of each dimension. This assumes that there is no covariance between the data dimensions.

mean

Sample mean of the data

sigma

Sample variance of each data dimension

Linear Supertypes
Product, Equals, ReversibleScaler[DenseVector[Double]], Encoder[DenseVector[Double], DenseVector[Double]], Scaler[DenseVector[Double]], DataPipe[DenseVector[Double], DenseVector[Double]], Serializable, Serializable, DataPipeConvertible[DenseVector[Double], DenseVector[Double]], AnyRef, Any
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Inherited
  1. GaussianScaler
  2. Product
  3. Equals
  4. ReversibleScaler
  5. Encoder
  6. Scaler
  7. DataPipe
  8. Serializable
  9. Serializable
  10. DataPipeConvertible
  11. AnyRef
  12. Any
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Visibility
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Instance Constructors

  1. new GaussianScaler(mean: DenseVector[Double], sigma: DenseVector[Double])

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    mean

    Sample mean of the data

    sigma

    Sample variance of each data dimension

Value Members

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

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

  3. def %>(that: Basis[DenseVector[Double]]): Basis[DenseVector[Double]]

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    Definition Classes
    DataPipe

  4. def *[T](that: ReversibleScaler[T]): ReversibleScaler[(DenseVector[Double], T)]

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    Definition Classes
    ReversibleScaler

  5. def *[T](that: Scaler[T]): Scaler[(DenseVector[Double], T)]

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    Definition Classes
    Scaler

  6. def *[OtherSource, OtherDestination](that: DataPipe[OtherSource, OtherDestination]): ParallelPipe[DenseVector[Double], DenseVector[Double], OtherSource, OtherDestination]

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    Definition Classes
    DataPipe

  7. def ++(other: GaussianScaler): GaussianScaler

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

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    Definition Classes
    AnyRef → Any

  9. def >(otherRevScaler: ReversibleScaler[DenseVector[Double]]): ReversibleScaler[DenseVector[Double]]

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    Definition Classes
    ReversibleScaler

  10. def >[Further](that: Encoder[DenseVector[Double], Further]): Encoder[DenseVector[Double], Further]

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    Definition Classes
    Encoder

  11. def >(otherScaler: Scaler[DenseVector[Double]]): Scaler[DenseVector[Double]]

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    Definition Classes
    Scaler

  12. def >[Further](that: DataPipeConvertible[DenseVector[Double], Further]): DataPipe[DenseVector[Double], Further]

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    Definition Classes
    DataPipe

  13. def >-<[OtherSource, OtherDestination](that: DataPipe[OtherSource, OtherDestination]): DataPipe2[DenseVector[Double], OtherSource, (DenseVector[Double], OtherDestination)]

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    Definition Classes
    DataPipe

  14. def apply(index: Int): UnivariateGaussianScaler

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  15. def apply(r: Range): GaussianScaler

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  16. def apply[T <: Traversable[DenseVector[Double]]](data: T): T

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    Definition Classes
    ReversibleScaler → Scaler → DataPipe

  17. def apply(data: DenseVector[Double]): DenseVector[Double]

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    Definition Classes
    DataPipe

  18. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  19. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef

  21. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

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

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    Definition Classes
    AnyRef → Any

  23. val i: Scaler[DenseVector[Double]]

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    Definition Classes
    GaussianScaler → ReversibleScaler → Encoder

  24. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  25. val mean: DenseVector[Double]

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    Sample mean of the data

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

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    Definition Classes
    AnyRef

  27. final def notify(): Unit

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    Definition Classes
    AnyRef

  28. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  29. def run(data: DenseVector[Double]): DenseVector[Double]

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    Definition Classes
    GaussianScaler → DataPipe

  30. val sigma: DenseVector[Double]

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    Sample variance of each data dimension

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

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    Definition Classes
    AnyRef

  32. def toPipe: (DenseVector[Double]) ⇒ DenseVector[Double]

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    Definition Classes
    DataPipe → DataPipeConvertible

  33. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Product

Inherited from Equals

Inherited from ReversibleScaler[DenseVector[Double]]

Inherited from Encoder[DenseVector[Double], DenseVector[Double]]

Inherited from Scaler[DenseVector[Double]]

Inherited from DataPipe[DenseVector[Double], DenseVector[Double]]

Inherited from Serializable

Inherited from Serializable

Inherited from DataPipeConvertible[DenseVector[Double], DenseVector[Double]]

Inherited from AnyRef

Inherited from Any

Ungrouped