Class

io.github.mandar2812.dynaml.optimization

GPMixtureMachine

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class GPMixtureMachine[T, I] extends MixtureMachine[T, I, Double, PartitionedVector, PartitionedPSDMatrix, BlockedMultiVariateGaussian, MultGaussianPRV, AbstractGPRegressionModel[T, I]]

Constructs a gaussian process mixture model from a single AbstractGPRegressionModel instance.

T

The type of the GP training data

I

The index set/input domain of the GP model.

Linear Supertypes
MixtureMachine[T, I, Double, PartitionedVector, PartitionedPSDMatrix, BlockedMultiVariateGaussian, MultGaussianPRV, AbstractGPRegressionModel[T, I]], AbstractCSA[AbstractGPRegressionModel[T, I], GenContinuousMixtureModel[T, I, Double, PartitionedVector, PartitionedPSDMatrix, BlockedMultiVariateGaussian, MultGaussianPRV, AbstractGPRegressionModel[T, I]]], AbstractGridSearch[AbstractGPRegressionModel[T, I], GenContinuousMixtureModel[T, I, Double, PartitionedVector, PartitionedPSDMatrix, BlockedMultiVariateGaussian, MultGaussianPRV, AbstractGPRegressionModel[T, I]]], ModelTuner[AbstractGPRegressionModel[T, I], GenContinuousMixtureModel[T, I, Double, PartitionedVector, PartitionedPSDMatrix, BlockedMultiVariateGaussian, MultGaussianPRV, AbstractGPRegressionModel[T, I]]], AnyRef, Any
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Inherited
  1. GPMixtureMachine
  2. MixtureMachine
  3. AbstractCSA
  4. AbstractGridSearch
  5. ModelTuner
  6. AnyRef
  7. Any
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Visibility
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Instance Constructors

  1. new GPMixtureMachine(model: AbstractGPRegressionModel[T, I])(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. var MAX_ITERATIONS: Int

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    Attributes
    protected
    Definition Classes
    AbstractCSA

  5. def _policy: String

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    Definition Classes
    MixtureMachine

  6. def acceptanceTemperature(initialTemp: Double)(k: Int): Double

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    Definition Classes
    AbstractCSA

  7. var alpha: Double

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    Definition Classes
    AbstractCSA

  8. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  9. var baselinePolicy: String

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    Attributes
    protected
    Definition Classes
    MixtureMachine

  10. def blockedHypParams: List[String]

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  11. def blockedState: Map[String, Double]

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  12. def calculateEnergyLandscape(initialConfig: Map[String, Double], options: Map[String, String]): Seq[(Double, Map[String, Double])]

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    Attributes
    protected
    Definition Classes
    MixtureMachine

  13. def clone(): AnyRef

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

  14. val confToModel: DataPipe[Map[String, Double], AbstractGPRegressionModel[T, I]]

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    Definition Classes
    GPMixtureMachine → MixtureMachine

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

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    Definition Classes
    AnyRef

  16. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  17. def finalize(): Unit

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

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

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    Definition Classes
    AnyRef → Any

  19. def getEnergyLandscape(initialConfig: Map[String, Double], options: Map[String, String] = Map(), prior: Map[String, ContinuousRVWithDistr[Double, ContinuousDistr[Double]]] = Map()): List[(Double, Map[String, Double])]

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    Definition Classes
    ModelTuner

  20. def getGrid(initialConfig: Map[String, Double]): Seq[Map[String, Double]]

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    Definition Classes
    ModelTuner

  21. var gridsize: Int

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    Attributes
    protected
    Definition Classes
    ModelTuner

  22. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

  23. var iTemp: Double

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    Definition Classes
    AbstractCSA

  24. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  25. val kernelPipe: DataPipe[Map[String, Double], LocalScalarKernel[I]]

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  26. var logarithmicScale: Boolean

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    Attributes
    protected
    Definition Classes
    ModelTuner

  27. val logger: Logger

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    Attributes
    protected
    Definition Classes
    AbstractGridSearch → ModelTuner

  28. var meanFieldPrior: Map[String, ContinuousRVWithDistr[Double, ContinuousDistr[Double]]]

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    Attributes
    protected
    Definition Classes
    ModelTuner

  29. val mixturePipe: GPMixturePipe[T, I]

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    Definition Classes
    GPMixtureMachine → MixtureMachine

  30. def modelProbabilities: DataPipe[Seq[(Double, Map[String, Double])], Seq[(Double, Map[String, Double])]]

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    Attributes
    protected
    Definition Classes
    MixtureMachine

  31. val mutate: (Map[String, Double], Double) ⇒ Map[String, Double]

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    Attributes
    protected
    Definition Classes
    AbstractCSA

  32. def mutationTemperature(initialTemp: Double)(k: Int): Double

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    Definition Classes
    AbstractCSA

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

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    Definition Classes
    AnyRef

  34. val noisePipe: DataPipe[Map[String, Double], LocalScalarKernel[I]]

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  35. final def notify(): Unit

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    Definition Classes
    AnyRef

  36. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  37. var num_samples: Int

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    Attributes
    protected
    Definition Classes
    ModelTuner

  38. def optimize(initialConfig: Map[String, Double], options: Map[String, String]): (GenContinuousMixtureModel[T, I, Double, PartitionedVector, PartitionedPSDMatrix, BlockedMultiVariateGaussian, MultGaussianPRV, AbstractGPRegressionModel[T, I]], Map[String, Double])

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    Definition Classes
    MixtureMachine → ModelTuner

  39. def performCSA(initialConfig: Map[String, Double], options: Map[String, String] = Map()): List[(Double, Map[String, Double])]

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    Attributes
    protected
    Definition Classes
    AbstractCSA

  40. var policy: String

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    Attributes
    protected
    Definition Classes
    MixtureMachine

  41. def setBaseLinePolicy(p: String): GPMixtureMachine.this.type

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    Definition Classes
    MixtureMachine

  42. def setGridSize(s: Int): GPMixtureMachine.this.type

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    Definition Classes
    AbstractCSA → AbstractGridSearch → ModelTuner

  43. def setLogScale(t: Boolean): GPMixtureMachine.this.type

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    Definition Classes
    AbstractCSA → AbstractGridSearch → ModelTuner

  44. def setMaxIterations(m: Int): GPMixtureMachine.this.type

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    Definition Classes
    AbstractCSA

  45. def setNumSamples(n: Int): GPMixtureMachine.this.type

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    Definition Classes
    ModelTuner

  46. def setPolicy(p: String): GPMixtureMachine.this.type

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    Definition Classes
    MixtureMachine

  47. def setPrior(p: Map[String, ContinuousRVWithDistr[Double, ContinuousDistr[Double]]]): GPMixtureMachine.this.type

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    Definition Classes
    ModelTuner

  48. def setStepSize(s: Double): GPMixtureMachine.this.type

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    Definition Classes
    AbstractCSA → AbstractGridSearch → ModelTuner

  49. def setVariant(v: String): GPMixtureMachine.this.type

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    Definition Classes
    AbstractCSA

  50. var step: Double

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    Attributes
    protected
    Definition Classes
    ModelTuner

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

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    Definition Classes
    AnyRef

  52. val system: AbstractGPRegressionModel[T, I]

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    Definition Classes
    AbstractGridSearch → ModelTuner

  53. def toString(): String

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    Definition Classes
    AnyRef → Any

  54. implicit val transform: DataPipe[T, Seq[(I, Double)]]

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  55. var variant: String

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    Attributes
    protected
    Definition Classes
    AbstractCSA

  56. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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

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

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

Inherited from AnyRef

Inherited from Any

Ungrouped