com.intel.analytics.zoo.pipeline.api.keras.objectives

MeanAbsoluteError

class MeanAbsoluteError[T] extends TensorLossFunction[T]

A loss that measures the mean absolute value of the element-wise difference between the input and the target.

Linear Supertypes
TensorLossFunction[T], LossFunction[Tensor[T], Tensor[T], T], AbstractCriterion[Tensor[T], Tensor[T], T], Serializable, Serializable, AnyRef, Any
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Inherited
  1. MeanAbsoluteError
  2. TensorLossFunction
  3. LossFunction
  4. AbstractCriterion
  5. Serializable
  6. Serializable
  7. AnyRef
  8. Any
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Instance Constructors

  1. new MeanAbsoluteError(sizeAverage: Boolean = true)(implicit arg0: ClassTag[T], ev: TensorNumeric[T])

    sizeAverage

    Boolean. Whether losses are averaged over observations for each mini-batch. Default is true. If false, the losses are instead summed for each mini-batch.

Value Members

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

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  6. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  7. def backward(input: Tensor[T], target: Tensor[T]): Tensor[T]

    Definition Classes
    AbstractCriterion

  8. def canEqual(other: Any): Boolean

    Definition Classes
    AbstractCriterion

  9. def clone(): AnyRef

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

  10. def cloneCriterion(): AbstractCriterion[Tensor[T], Tensor[T], T]

    Definition Classes
    AbstractCriterion

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

    Definition Classes
    AnyRef

  12. def equals(other: Any): Boolean

    Definition Classes
    AbstractCriterion → AnyRef → Any

  13. def finalize(): Unit

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

  14. def forward(input: Tensor[T], target: Tensor[T]): T

    Definition Classes
    AbstractCriterion

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

    Definition Classes
    AnyRef → Any

  16. var gradInput: Tensor[T]

    Definition Classes
    AbstractCriterion

  17. def hashCode(): Int

    Definition Classes
    AbstractCriterion → AnyRef → Any

  18. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  19. val loss: AbstractCriterion[Tensor[T], Tensor[T], T]

    Definition Classes
    MeanAbsoluteError → LossFunction

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

    Definition Classes
    AnyRef

  21. final def notify(): Unit

    Definition Classes
    AnyRef

  22. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  23. var output: T

    Definition Classes
    AbstractCriterion

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

    Definition Classes
    AnyRef

  25. def toString(): String

    Definition Classes
    AnyRef → Any

  26. def updateGradInput(input: Tensor[T], target: Tensor[T]): Tensor[T]

    Definition Classes
    LossFunction → AbstractCriterion

  27. def updateOutput(input: Tensor[T], target: Tensor[T]): T

    Definition Classes
    LossFunction → AbstractCriterion

  28. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from TensorLossFunction[T]

Inherited from LossFunction[Tensor[T], Tensor[T], T]

Inherited from AbstractCriterion[Tensor[T], Tensor[T], T]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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