Class

com.github.cloudml.zen.ml.neuralNetwork

EquilibratedUpdater

Related Doc: package neuralNetwork

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class EquilibratedUpdater extends Updater

Equilibrated Gradient Descent the paper: RMSProp and equilibrated adaptive learning rates for non-convex optimization

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@Experimental()
Linear Supertypes
Updater, Serializable, Serializable, AnyRef, Any
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  1. EquilibratedUpdater
  2. Updater
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Instance Constructors

  1. new EquilibratedUpdater(epsilon: Double, momentum: Double)

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Value Members

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

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    AnyRef → Any

  2. final def ##(): Int

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    AnyRef → Any

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

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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    protected[java.lang]
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    @throws( ... )

  6. def compute(weightsOld: Vector, gradient: Vector, stepSize: Double, iter: Int, regParam: Double): (Vector, Double)

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    Definition Classes
    EquilibratedUpdater → Updater

  7. val epsilon: Double

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

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    AnyRef

  9. def equals(arg0: Any): Boolean

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  10. def finalize(): Unit

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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. def l2(weightsOld: Vector, gradient: Vector, stepSize: Double, iter: Int, regParam: Double): Double

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    Attributes
    protected

  15. val momentum: Double

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

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  17. final def notify(): Unit

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  18. final def notifyAll(): Unit

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

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  20. def toString(): String

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  21. final def wait(): Unit

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    @throws( ... )

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

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    @throws( ... )

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

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Inherited from Updater

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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