Class

io.github.mandar2812.dynaml.modelpipe

GPMixturePipe

Related Doc: package modelpipe

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class GPMixturePipe[T, I] extends MixturePipe[T, I, Double, PartitionedVector, PartitionedPSDMatrix, BlockedMultiVariateGaussian, MultGaussianPRV, AbstractGPRegressionModel[T, I]]

Linear Supertypes
MixturePipe[T, I, Double, PartitionedVector, PartitionedPSDMatrix, BlockedMultiVariateGaussian, MultGaussianPRV, AbstractGPRegressionModel[T, I]], DataPipe2[Seq[AbstractGPRegressionModel[T, I]], DenseVector[Double], GenContinuousMixtureModel[T, I, Double, PartitionedVector, PartitionedPSDMatrix, BlockedMultiVariateGaussian, MultGaussianPRV, AbstractGPRegressionModel[T, I]]], Serializable, Serializable, DataPipeConvertible[(Seq[AbstractGPRegressionModel[T, I]], DenseVector[Double]), GenContinuousMixtureModel[T, I, Double, PartitionedVector, PartitionedPSDMatrix, BlockedMultiVariateGaussian, MultGaussianPRV, AbstractGPRegressionModel[T, I]]], AnyRef, Any
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Inherited
  1. GPMixturePipe
  2. MixturePipe
  3. DataPipe2
  4. Serializable
  5. Serializable
  6. DataPipeConvertible
  7. AnyRef
  8. Any
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Visibility
  1. Public
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Instance Constructors

  1. new GPMixturePipe()(implicit arg0: ClassTag[I])

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

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    Definition Classes
    AnyRef → Any

  4. def >[Result2](otherPipe: DataPipe[GenContinuousMixtureModel[T, I, Double, PartitionedVector, PartitionedPSDMatrix, BlockedMultiVariateGaussian, MultGaussianPRV, AbstractGPRegressionModel[T, I]], Result2]): DataPipe2[Seq[AbstractGPRegressionModel[T, I]], DenseVector[Double], Result2]

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    Definition Classes
    DataPipe2

  5. def apply(data1: Seq[AbstractGPRegressionModel[T, I]], data2: DenseVector[Double]): GenContinuousMixtureModel[T, I, Double, PartitionedVector, PartitionedPSDMatrix, BlockedMultiVariateGaussian, MultGaussianPRV, AbstractGPRegressionModel[T, I]]

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    Definition Classes
    DataPipe2

  6. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  7. def clone(): AnyRef

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

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

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    Definition Classes
    AnyRef

  9. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  10. def finalize(): Unit

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

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

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  12. def hashCode(): Int

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    AnyRef → Any

  13. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

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

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    Definition Classes
    AnyRef

  15. final def notify(): Unit

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    Definition Classes
    AnyRef

  16. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  17. def run(models: Seq[AbstractGPRegressionModel[T, I]], weights: DenseVector[Double]): GaussianProcessMixture[T, I]

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    Definition Classes
    GPMixturePipe → DataPipe2

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

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    Definition Classes
    AnyRef

  19. def toPipe: ((Seq[AbstractGPRegressionModel[T, I]], DenseVector[Double])) ⇒ GenContinuousMixtureModel[T, I, Double, PartitionedVector, PartitionedPSDMatrix, BlockedMultiVariateGaussian, MultGaussianPRV, AbstractGPRegressionModel[T, I]]

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    Definition Classes
    DataPipe2 → DataPipeConvertible

  20. def toString(): String

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    Definition Classes
    AnyRef → Any

  21. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from MixturePipe[T, I, Double, PartitionedVector, PartitionedPSDMatrix, BlockedMultiVariateGaussian, MultGaussianPRV, AbstractGPRegressionModel[T, I]]

Inherited from DataPipe2[Seq[AbstractGPRegressionModel[T, I]], DenseVector[Double], GenContinuousMixtureModel[T, I, Double, PartitionedVector, PartitionedPSDMatrix, BlockedMultiVariateGaussian, MultGaussianPRV, AbstractGPRegressionModel[T, I]]]

Inherited from Serializable

Inherited from Serializable

Inherited from DataPipeConvertible[(Seq[AbstractGPRegressionModel[T, I]], DenseVector[Double]), GenContinuousMixtureModel[T, I, Double, PartitionedVector, PartitionedPSDMatrix, BlockedMultiVariateGaussian, MultGaussianPRV, AbstractGPRegressionModel[T, I]]]

Inherited from AnyRef

Inherited from Any

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