Class

io.github.mandar2812.dynaml.kernels

FeatureMapCovariance

Related Doc: package kernels

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class FeatureMapCovariance[T, U] extends CovarianceFunction[T, Double, DenseMatrix[Double]] with LocalSVMKernel[T]

Self Type
FeatureMapCovariance[T, U]
Linear Supertypes
LocalSVMKernel[T], LocalScalarKernel[T], CovarianceFunction[T, Double, DenseMatrix[Double]], Kernel[T, Double], Serializable, Serializable, AnyRef, Any
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Inherited
  1. FeatureMapCovariance
  2. LocalSVMKernel
  3. LocalScalarKernel
  4. CovarianceFunction
  5. Kernel
  6. Serializable
  7. Serializable
  8. AnyRef
  9. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new FeatureMapCovariance(p: DataPipe[T, U])(implicit e: InnerProductSpace[U, Double])

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    p

    Feature map to be applied on input.

Value Members

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

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

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    Definition Classes
    AnyRef → Any
  3. def *(c: Double): LocalScalarKernel[T]

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    Returns the kernel multiplied by a positive constant: k_new = k*c

    Returns the kernel multiplied by a positive constant: k_new = k*c

    Definition Classes
    LocalScalarKernel
  4. def *[T <: LocalScalarKernel[T]](otherKernel: T)(implicit ev: ClassTag[T]): CompositeCovariance[T]

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    Create composite kernel k = k1 * k2

    Create composite kernel k = k1 * k2

    otherKernel

    The kernel to multiply to the current one.

    returns

    The kernel k defined above.

    Definition Classes
    LocalScalarKernel
  5. def +[T <: LocalScalarKernel[T]](otherKernel: T)(implicit ev: ClassTag[T]): CompositeCovariance[T]

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    Create composite kernel k = k1 + k2

    Create composite kernel k = k1 + k2

    param otherKernel The kernel to add to the current one. return The kernel k defined above.

    Definition Classes
    LocalScalarKernel
  6. def :*[T1](otherKernel: LocalScalarKernel[T1]): KroneckerProductKernel[T, T1]

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    Construct the kronecker product kernel

    Construct the kronecker product kernel

    Definition Classes
    LocalScalarKernel
  7. def :+[T1](otherKernel: LocalScalarKernel[T1]): CompositeCovariance[(T, T1)]

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    Definition Classes
    LocalScalarKernel
  8. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  9. def >[V](other: FeatureMapCovariance[U, V])(implicit e1: InnerProductSpace[V, Double]): FeatureMapCovariance[T, V]

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    Construct a multi-layer feature map kernel

  10. def >(other: LocalScalarKernel[U]): CompositeCovariance[T]

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    Construct a multi-layer kernel

  11. def >[K <: GenericRBFKernel[T]](otherKernel: K): CompositeCovariance[T]

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    Construct a 2 layer kernel K = k1 > rbf

    Construct a 2 layer kernel K = k1 > rbf

    Definition Classes
    LocalScalarKernel
  12. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  13. def asPipe: DataPipe[Map[String, Double], LocalScalarKernel[T]]

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    Get a pipeline which when given a particular configuration of hyper-parameters returns this kernel function set with that configuration.

    Get a pipeline which when given a particular configuration of hyper-parameters returns this kernel function set with that configuration.

    Definition Classes
    LocalScalarKernel
  14. def block(h: String*): Unit

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    Definition Classes
    CovarianceFunction
  15. def block_all_hyper_parameters: Unit

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    Definition Classes
    CovarianceFunction
  16. var blocked_hyper_parameters: List[String]

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    Definition Classes
    CovarianceFunction
  17. def buildBlockedCrossKernelMatrix[S <: Seq[T]](dataset1: S, dataset2: S): PartitionedMatrix

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    Definition Classes
    LocalScalarKernel
  18. def buildBlockedKernelMatrix[S <: Seq[T]](mappedData: S, length: Long): PartitionedPSDMatrix

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    Definition Classes
    LocalScalarKernel
  19. def buildCrossKernelMatrix[S <: Seq[T]](dataset1: S, dataset2: S): DenseMatrix[Double]

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    Definition Classes
    LocalScalarKernelCovarianceFunction
  20. def buildKernelMatrix[S <: Seq[T]](mappedData: S, length: Int): KernelMatrix[DenseMatrix[Double]]

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    Definition Classes
    LocalScalarKernelCovarianceFunction
  21. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  22. var colBlocking: Int

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    Definition Classes
    LocalScalarKernel
  23. def effective_hyper_parameters: List[String]

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    Definition Classes
    CovarianceFunction
  24. def effective_state: Map[String, Double]

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    Definition Classes
    CovarianceFunction
  25. final def eq(arg0: AnyRef): Boolean

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

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    Definition Classes
    AnyRef → Any
  27. def evaluate(x: T, y: T): Double

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    Definition Classes
    CovarianceFunctionKernel
  28. def evaluateAt(config: Map[String, Double])(x: T, y: T): Double

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  29. def finalize(): Unit

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

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    Definition Classes
    AnyRef → Any
  31. def gradient(x: T, y: T): Map[String, Double]

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    Definition Classes
    CovarianceFunction
  32. def gradientAt(config: Map[String, Double])(x: T, y: T): Map[String, Double]

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    Definition Classes
    LocalSVMKernelCovarianceFunction
  33. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  34. val hyper_parameters: List[String]

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  35. final def isInstanceOf[T0]: Boolean

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

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

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

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    Definition Classes
    AnyRef
  39. val phi: DataPipe[T, U]

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  40. var rowBlocking: Int

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    Definition Classes
    LocalScalarKernel
  41. def setBlockSizes(s: (Int, Int)): Unit

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    Definition Classes
    LocalScalarKernel
  42. def setHyperParameters(h: Map[String, Double]): FeatureMapCovariance.this.type

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    Definition Classes
    CovarianceFunction
  43. var state: Map[String, Double]

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    Definition Classes
    CovarianceFunction
  44. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  45. def toString(): String

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

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

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from LocalSVMKernel[T]

Inherited from LocalScalarKernel[T]

Inherited from CovarianceFunction[T, Double, DenseMatrix[Double]]

Inherited from Kernel[T, Double]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped