Class/Object

io.github.mandar2812.dynaml.kernels

CovarianceFunction

Related Docs: object CovarianceFunction | package kernels

Permalink

abstract class CovarianceFunction[T, V, M] extends Kernel[T, V] with Serializable

A (symmeteric positive definite) covariance function. Covariance functions are central to Gaussian/Student T Process Models as well as SVMs.

T

The index set over which K(.,.) is defined K: T × T -> V

V

The value outputted by the kernel

M

The type of the kernel matrix object.

Linear Supertypes
Kernel[T, V], Serializable, Serializable, AnyRef, Any
Known Subclasses
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. CovarianceFunction
  2. Kernel
  3. Serializable
  4. Serializable
  5. AnyRef
  6. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new CovarianceFunction()

    Permalink

Abstract Value Members

  1. abstract def buildCrossKernelMatrix[S <: Seq[T]](dataset1: S, dataset2: S): M

    Permalink
  2. abstract def buildKernelMatrix[S <: Seq[T]](mappedData: S, length: Int): KernelMatrix[M]

    Permalink
  3. abstract def evaluateAt(config: Map[String, Double])(x: T, y: T): V

    Permalink
  4. abstract def gradientAt(config: Map[String, Double])(x: T, y: T): Map[String, V]

    Permalink
  5. abstract val hyper_parameters: List[String]

    Permalink

Concrete Value Members

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

    Permalink
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

    Permalink
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0

    Permalink
    Definition Classes
    Any
  5. def block(h: String*): Unit

    Permalink
  6. def block_all_hyper_parameters: Unit

    Permalink
  7. var blocked_hyper_parameters: List[String]

    Permalink
  8. def clone(): AnyRef

    Permalink
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  9. def effective_hyper_parameters: List[String]

    Permalink
  10. def effective_state: Map[String, Double]

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

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

    Permalink
    Definition Classes
    AnyRef → Any
  13. def evaluate(x: T, y: T): V

    Permalink
    Definition Classes
    CovarianceFunctionKernel
  14. def finalize(): Unit

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

    Permalink
    Definition Classes
    AnyRef → Any
  16. def gradient(x: T, y: T): Map[String, V]

    Permalink
  17. def hashCode(): Int

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

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

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

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

    Permalink
    Definition Classes
    AnyRef
  22. def setHyperParameters(h: Map[String, Double]): CovarianceFunction.this.type

    Permalink
  23. var state: Map[String, Double]

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

    Permalink
    Definition Classes
    AnyRef
  25. def toString(): String

    Permalink
    Definition Classes
    AnyRef → Any
  26. final def wait(): Unit

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

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

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Kernel[T, V]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped