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io.github.mandar2812.dynaml.models.neuralnets

TransferFunctions

Related Doc: package neuralnets

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object TransferFunctions

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

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  2. final def ##(): Int

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

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  4. val Dlin: (Double) ⇒ Double

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    First derivative of the linear function

  5. val Dlogsig: (Double) ⇒ Double

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    First derivative of the sigmoid function

  6. val DrecLin: (Double) ⇒ Double

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    First derivative of the rectified linear function

  7. val Dselu: (Double, Double) ⇒ (Double) ⇒ Double

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  8. val Dtansig: (Double) ⇒ Double

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    First derivative of the hyperbolic tangent function

  9. val LIN: String

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  10. val RECLIN: String

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  11. val SIGMOID: String

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  12. val TANH: String

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  13. final def asInstanceOf[T0]: T0

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  14. def clone(): AnyRef

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

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  16. def equals(arg0: Any): Boolean

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  17. def finalize(): Unit

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  18. def getActivation(s: String): (Double) ⇒ Double

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    Function which returns the appropriate activation for a given string

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

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  20. def getDiffActivation(s: String): (Double) ⇒ Double

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    Function which returns the appropriate derivative activation for a given string

  21. def hashCode(): Int

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  22. final def isInstanceOf[T0]: Boolean

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  23. val lin: (Double) ⇒ Double

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    Linear/Identity Function

  24. val logsig: (Double) ⇒ Double

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    Sigmoid/Logistic function

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

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  26. final def notify(): Unit

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  27. final def notifyAll(): Unit

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  28. val recLin: (Double) ⇒ Double

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    Rectified linear Function

  29. val selu: (Double, Double) ⇒ (Double) ⇒ Double

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

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  31. val tansig: (Double) ⇒ Double

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    Hyperbolic tangent function

  32. def toString(): String

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  33. final def wait(): Unit

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

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

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