nak.nnet

NNObjective

class NNObjective[Output] extends BatchDiffFunction[DenseVector[Double]]

Linear Supertypes
BatchDiffFunction[DenseVector[Double]], (DenseVector[Double], IndexedSeq[Int]) ⇒ Double, DiffFunction[DenseVector[Double]], StochasticDiffFunction[DenseVector[Double]], (DenseVector[Double]) ⇒ Double, AnyRef, Any
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Inherited
  1. NNObjective
  2. BatchDiffFunction
  3. Function2
  4. DiffFunction
  5. StochasticDiffFunction
  6. Function1
  7. AnyRef
  8. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new NNObjective(data: IndexedSeq[(DenseVector[Double], Output)], errorFun: (DenseVector[Double], Output) ⇒ (Double, DenseVector[Double]), layers: Array[Int])

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. def andThen[A](g: (Double) ⇒ A): (DenseVector[Double]) ⇒ A

    Definition Classes
    Function1
    Annotations
    @unspecialized()

  7. def apply(x: DenseVector[Double], batch: IndexedSeq[Int]): Double

    Definition Classes
    BatchDiffFunction → Function2

  8. final def apply(x: DenseVector[Double]): Double

    Definition Classes
    StochasticDiffFunction → Function1

  9. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  10. def calculate(x: DenseVector[Double], batch: IndexedSeq[Int]): (Double, DenseVector[Double])

    Definition Classes
    NNObjective → BatchDiffFunction

  11. def calculate(x: DenseVector[Double]): (Double, DenseVector[Double])

    Definition Classes
    BatchDiffFunction → StochasticDiffFunction

  12. def clone(): AnyRef

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

  13. def compose[A](g: (A) ⇒ DenseVector[Double]): (A) ⇒ Double

    Definition Classes
    Function1
    Annotations
    @unspecialized()

  14. def curried: (DenseVector[Double]) ⇒ (IndexedSeq[Int]) ⇒ Double

    Definition Classes
    Function2
    Annotations
    @unspecialized()

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

    Definition Classes
    AnyRef

  16. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  17. def extract(x: DenseVector[Double]): NeuralNetwork

  18. def finalize(): Unit

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

  19. def fullRange: IndexedSeq[Int]

    The full size of the data

    The full size of the data

    Definition Classes
    NNObjective → BatchDiffFunction

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

    Definition Classes
    AnyRef → Any

  21. def gradientAt(x: DenseVector[Double]): DenseVector[Double]

    Definition Classes
    BatchDiffFunction → StochasticDiffFunction

  22. def gradientAt(x: DenseVector[Double], batch: IndexedSeq[Int]): DenseVector[Double]

    Definition Classes
    BatchDiffFunction

  23. def groupItems(groupSize: Int): BatchDiffFunction[DenseVector[Double]]

    Definition Classes
    BatchDiffFunction

  24. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  25. def initialWeightVector: DenseVector[Double]

  26. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

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

    Definition Classes
    AnyRef

  28. final def notify(): Unit

    Definition Classes
    AnyRef

  29. final def notifyAll(): Unit

    Definition Classes
    AnyRef

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

    Definition Classes
    AnyRef

  31. def throughLens[U](implicit l: Isomorphism[DenseVector[Double], U]): DiffFunction[U]

    Definition Classes
    StochasticDiffFunction

  32. def toString(): String

    Definition Classes
    Function2 → AnyRef → Any

  33. def tupled: ((DenseVector[Double], IndexedSeq[Int])) ⇒ Double

    Definition Classes
    Function2
    Annotations
    @unspecialized()

  34. def valueAt(x: DenseVector[Double]): Double

    Definition Classes
    BatchDiffFunction → StochasticDiffFunction

  35. def valueAt(x: DenseVector[Double], batch: IndexedSeq[Int]): Double

    Definition Classes
    BatchDiffFunction

  36. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  39. def withRandomBatches(size: Int): StochasticDiffFunction[DenseVector[Double]]

    Definition Classes
    BatchDiffFunction

  40. def withScanningBatches(size: Int): StochasticDiffFunction[DenseVector[Double]]

    Definition Classes
    BatchDiffFunction

Inherited from BatchDiffFunction[DenseVector[Double]]

Inherited from (DenseVector[Double], IndexedSeq[Int]) ⇒ Double

Inherited from DiffFunction[DenseVector[Double]]

Inherited from StochasticDiffFunction[DenseVector[Double]]

Inherited from (DenseVector[Double]) ⇒ Double

Inherited from AnyRef

Inherited from Any

Ungrouped