breeze.optimize

SecondOrderFunction

trait SecondOrderFunction[T, H] extends DiffFunction[T]

Represents a function for which we can easily compute the Hessian.

For conjugate gradient methods, you can play tricks with the hessian, returning an object that only supports multiplication.

Linear Supertypes
DiffFunction[T], StochasticDiffFunction[T], (T) ⇒ Double, AnyRef, Any
Known Subclasses
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Inherited
  1. SecondOrderFunction
  2. DiffFunction
  3. StochasticDiffFunction
  4. Function1
  5. AnyRef
  6. Any
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Abstract Value Members

  1. abstract def calculate2(x: T): (Double, T, H)

    Calculates the value, the gradient, and the Hessian at a point

Concrete 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): (T) ⇒ A

    Definition Classes
    Function1
    Annotations
    @unspecialized()
  7. final def apply(x: T): Double

    Definition Classes
    StochasticDiffFunction → Function1
  8. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  9. def calculate(x: T): (Double, T)

    Calculates both the value and the gradient at a point

    Calculates both the value and the gradient at a point

    Definition Classes
    SecondOrderFunctionStochasticDiffFunction
  10. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  11. def compose[A](g: (A) ⇒ T): (A) ⇒ Double

    Definition Classes
    Function1
    Annotations
    @unspecialized()
  12. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  13. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  14. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  15. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  16. def gradientAt(x: T): T

    calculates the gradient at a point

    calculates the gradient at a point

    Definition Classes
    StochasticDiffFunction
  17. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  18. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  19. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  20. final def notify(): Unit

    Definition Classes
    AnyRef
  21. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  22. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  23. def throughLens[U](implicit l: Isomorphism[T, U]): DiffFunction[U]

    Lenses provide a way of mapping between two types, which we typically use to convert something to a DenseVector or other Tensor for optimization purposes.

    Lenses provide a way of mapping between two types, which we typically use to convert something to a DenseVector or other Tensor for optimization purposes.

    Definition Classes
    StochasticDiffFunction
  24. def toString(): String

    Definition Classes
    Function1 → AnyRef → Any
  25. def valueAt(x: T): Double

    calculates the value at a point

    calculates the value at a point

    Definition Classes
    StochasticDiffFunction
  26. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  27. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  28. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from DiffFunction[T]

Inherited from StochasticDiffFunction[T]

Inherited from (T) ⇒ Double

Inherited from AnyRef

Inherited from Any

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