Object

com.github.nearbydelta.deepspark.data

Rectifier

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object Rectifier extends Activation

Activation Function: Rectifier

Example: 

  1. val fx = Rectifier(0.0)
          val diff = Rectifier.derivative(fx)
Note

rectifier(x) = x if x > 0, otherwise 0 We assumed the input of activation is a row vector.

Linear Supertypes
Activation, Differentiable, (DataVec) ⇒ DataVec, Serializable, Serializable, AnyRef, Any
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Inherited
  1. Rectifier
  2. Activation
  3. Differentiable
  4. Function1
  5. Serializable
  6. Serializable
  7. AnyRef
  8. Any
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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. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  4. def andThen[A](g: (DataVec) ⇒ A): (DataVec) ⇒ A

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    Definition Classes
    Function1
    Annotations
    @unspecialized()

  5. def apply(x: DataVec): DataVec

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    Compute mapping for x

    Compute mapping for x

    x

    the input matrix. Before application, input should be summed already.

    returns

    value of f(x)

    Definition Classes
    Rectifier → Function1

  6. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  7. def clone(): AnyRef

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

  8. def compose[A](g: (A) ⇒ DataVec): (A) ⇒ DataVec

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    Definition Classes
    Function1
    Annotations
    @unspecialized()

  9. def derivative(fx: DataVec): Matrix

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    Differentiate function at output value fx.

    Differentiate function at output value fx.

    fx

    Differentiation point vector, by output value.

    returns

    Differentiation value of this function, generally squared matrix with same dimension.

    Definition Classes
    Rectifier → Differentiable

  10. def diffAtY(y: DataVec): Matrix

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    Differentiate function at output value y.

    Differentiate function at output value y.

    y

    Differentiation point vector, by output value.

    returns

    Differentiation value of this function, generally squared matrix with same dimension.

    Definition Classes
    Differentiable

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

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    Definition Classes
    AnyRef

  12. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  13. def finalize(): Unit

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

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

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    Definition Classes
    AnyRef → Any

  15. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

  16. def initialize(fanIn: Int, fanOut: Int): (Double, Double)

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    Initialization range of weight

    Initialization range of weight

    fanIn

    the number of fan-in i.e. the number of neurons in previous layer

    fanOut

    the number of fan-out i.e. the number of neurons in next layer

    returns

    the initialized range of weight

    Definition Classes
    Activation

  17. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

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

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    Definition Classes
    AnyRef

  19. final def notify(): Unit

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    Definition Classes
    AnyRef

  20. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

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

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    Definition Classes
    AnyRef

  22. def toString(): String

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    Definition Classes
    Function1 → AnyRef → Any

  23. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Activation

Inherited from Differentiable

Inherited from (DataVec) ⇒ DataVec

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped