case class L2Regularizer[T](l2: Double)(implicit evidence$4: ClassTag[T], ev: TensorNumeric[T]) extends L1L2Regularizer[T] with Product with Serializable

Apply L2 regularization

T

type parameters Float or Double

l2

l2 regularization rate

Annotations
@SerialVersionUID()
Linear Supertypes
Product, Equals, L1L2Regularizer[T], Regularizer[T], Serializable, Serializable, AnyRef, Any
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Inherited
  1. L2Regularizer
  2. Product
  3. Equals
  4. L1L2Regularizer
  5. Regularizer
  6. Serializable
  7. Serializable
  8. AnyRef
  9. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new L2Regularizer(l2: Double)(implicit arg0: ClassTag[T], ev: TensorNumeric[T])

    l2

    l2 regularization rate

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. def accRegularization(parameter: Tensor[T], gradParameter: Tensor[T], scale: Double): Unit

    The method need to be override by the concrete regularizer class It accumulates the gradient of the regularization of parameter to gradParameter

    The method need to be override by the concrete regularizer class It accumulates the gradient of the regularization of parameter to gradParameter

    parameter

    the parameter that is regularized

    gradParameter

    the gradient of the parameter

    scale

    the scale of gradParameters

    Definition Classes
    L1L2Regularizer → Regularizer
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )
  7. def disable(): Unit

    Disable the regularization feature

    Disable the regularization feature

    Definition Classes
    Regularizer
  8. def enable(): Unit

    Enable the regularization feature

    Enable the regularization feature

    Definition Classes
    Regularizer
  9. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  10. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  11. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  12. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  13. val l1: Double
    Definition Classes
    L1L2Regularizer
  14. val l2: Double
    Definition Classes
    L2Regularizer → L1L2Regularizer
  15. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  16. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  17. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  18. def preCheck(parameter: Tensor[T], gradParameter: Tensor[T]): Boolean

    Check the regularization is applied or not

    Check the regularization is applied or not

    parameter

    the parameter that is regularized

    gradParameter

    the gradient of the parameter

    returns

    a boolean, if true, accumulates the gradient of regularization, otherwise not.

    Attributes
    protected
    Definition Classes
    Regularizer
  19. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  20. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  21. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  22. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )

Inherited from Product

Inherited from Equals

Inherited from L1L2Regularizer[T]

Inherited from Regularizer[T]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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