Class

org.clustering4ever.clustering.rla

RLAModelMixed

Related Doc: package rla

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final case class RLAModelMixed[D <: MixedDistance](metric: D, epsilon: Double, centers: HashMap[Int, MixedVector]) extends RLAModelAncestor[MixedVector, D] with CenterModelMixedLocal[D] with KnnModelModelMixed[D] with Product with Serializable

Linear Supertypes
Product, Equals, KnnModelModelMixed[D], CenterModelMixedLocal[D], CenterModelMixed[D], RLAModelAncestor[MixedVector, D], MetricArgs[MixedVector, D], AlgorithmsArguments, CenterModelLocalCz[MixedVector, D], CenterModelCz[MixedVector, D], CenterModelLocal[MixedVector, D], CenterModel[MixedVector, D], KnnModelModelLocalCz[MixedVector, D], KnnModelModelCz[MixedVector, D], KnnModelModelLocal[MixedVector, D], KnnModelModel[MixedVector, D], MetricModel[MixedVector, D], ClusteringModelLocal[MixedVector], ClusteringModel, ClusteringSharedTypes, Serializable, Serializable, AnyRef, Any
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Inherited
  1. RLAModelMixed
  2. Product
  3. Equals
  4. KnnModelModelMixed
  5. CenterModelMixedLocal
  6. CenterModelMixed
  7. RLAModelAncestor
  8. MetricArgs
  9. AlgorithmsArguments
  10. CenterModelLocalCz
  11. CenterModelCz
  12. CenterModelLocal
  13. CenterModel
  14. KnnModelModelLocalCz
  15. KnnModelModelCz
  16. KnnModelModelLocal
  17. KnnModelModel
  18. MetricModel
  19. ClusteringModelLocal
  20. ClusteringModel
  21. ClusteringSharedTypes
  22. Serializable
  23. Serializable
  24. AnyRef
  25. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new RLAModelMixed(metric: D, epsilon: Double, centers: HashMap[Int, MixedVector])

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Type Members

  1. final type ClusterID = Int

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    Definition Classes
    ClusteringSharedTypes

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. final val algorithmID: extensibleAlgorithmNature.RLAMixed.type

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    Definition Classes
    RLAModelMixed → ClusteringModel

  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  6. final def centerPredict[GS[X] <: GenSeq[X]](data: GS[(Array[Int], Array[Double])])(implicit d1: DummyImplicit, d2: DummyImplicit): GS[(ClusterID, (Array[Int], Array[Double]))]

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    Definition Classes
    CenterModelMixedLocal

  7. final def centerPredict(v: (Array[Int], Array[Double])): ClusterID

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    Definition Classes
    CenterModelMixed

  8. final def centerPredict[O, Cz[B, C <: GVector[C]] <: Clusterizable[B, C, Cz], GS[X] <: GenSeq[X]](data: GS[Cz[O, MixedVector]])(implicit d: DummyImplicit): GS[Cz[O, MixedVector]]

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    Definition Classes
    CenterModelLocalCz

  9. final def centerPredict[O, Cz[B, C <: GVector[C]] <: Clusterizable[B, C, Cz]](cz: Cz[O, MixedVector]): ClusterID

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    Definition Classes
    CenterModelCz

  10. final def centerPredict[GS[X] <: GenSeq[X]](data: GS[MixedVector]): GS[(ClusterID, MixedVector)]

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    Definition Classes
    CenterModelLocal

  11. final def centerPredict(v: MixedVector): ClusterID

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    Definition Classes
    CenterModel

  12. final val centers: HashMap[Int, MixedVector]

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    Definition Classes
    RLAModelMixed → CenterModel

  13. def clone(): AnyRef

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

  14. final val epsilon: Double

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    Definition Classes
    RLAModelMixed → RLAModelAncestor

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

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    Definition Classes
    AnyRef

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

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    Definition Classes
    AnyRef → Any
    Annotations
    @HotSpotIntrinsicCandidate()

  17. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  18. final def knnPredict(v: (Array[Int], Array[Double]), k: Int, trainDS: Seq[(ClusterID, (Array[Int], Array[Double]))]): ClusterID

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    Definition Classes
    KnnModelModelMixed

  19. final def knnPredict[O, Cz[B, C <: GVector[C]] <: Clusterizable[B, C, Cz], GS[X] <: GenSeq[X]](data: GS[Cz[O, MixedVector]], k: Int, trainDS: Seq[Cz[O, MixedVector]], clusteringNumber: Int): GS[Cz[O, MixedVector]]

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    Definition Classes
    KnnModelModelLocalCz

  20. final def knnPredict[O, Cz[B, C <: GVector[C]] <: Clusterizable[B, C, Cz]](cz: Cz[O, MixedVector], k: Int, trainDS: Seq[Cz[O, MixedVector]], clusteringNumber: Int): ClusterID

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    Definition Classes
    KnnModelModelCz

  21. final def knnPredict[GS[X] <: GenSeq[X]](data: GS[MixedVector], k: Int, trainDS: Seq[(ClusterID, MixedVector)]): GS[(ClusterID, MixedVector)]

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    Definition Classes
    KnnModelModelLocal

  22. final def knnPredict(v: MixedVector, k: Int, trainDS: Seq[(ClusterID, MixedVector)]): ClusterID

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    Definition Classes
    KnnModelModel

  23. final def knnPredictWithNN(v: (Array[Int], Array[Double]), k: Int, trainDS: Seq[(ClusterID, (Array[Int], Array[Double]))]): (ClusterID, Seq[(ClusterID, (Array[Int], Array[Double]))])

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    Definition Classes
    KnnModelModelMixed

  24. final def knnPredictWithNN[O, Cz[B, C <: GVector[C]] <: Clusterizable[B, C, Cz]](cz: Cz[O, MixedVector], k: Int, trainDS: Seq[Cz[O, MixedVector]], clusteringNumber: Int): (ClusterID, Seq[Cz[O, MixedVector]])

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    Definition Classes
    KnnModelModelCz

  25. final def knnPredictWithNN(v: MixedVector, k: Int, trainDS: Seq[(ClusterID, MixedVector)]): (ClusterID, Seq[(ClusterID, MixedVector)])

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    Definition Classes
    KnnModelModel

  26. final val metric: D

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    Definition Classes
    RLAModelMixed → MetricArgs → MetricModel

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

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    Definition Classes
    AnyRef

  28. final def notify(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @HotSpotIntrinsicCandidate()

  29. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @HotSpotIntrinsicCandidate()

  30. final def obtainClustering[O, Cz[B, C <: GVector[C]] <: Clusterizable[B, C, Cz], GS[X] <: GenSeq[X]](data: GS[Cz[O, MixedVector]]): GS[Cz[O, MixedVector]]

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    Attributes
    protected[org.clustering4ever.clustering]
    Definition Classes
    RLAModelAncestor → ClusteringModelLocal

  31. final def obtainClusteringIDs[O, Cz[Y, Z <: GVector[Z]] <: Clusterizable[Y, Z, Cz], GS[X] <: GenSeq[X]](data: GS[Cz[O, MixedVector]]): GS[ClusterID]

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    Attributes
    protected[org.clustering4ever.clustering]
    Definition Classes
    ClusteringModelLocal

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

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    Definition Classes
    AnyRef

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  35. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Deprecated Value Members

  1. def finalize(): Unit

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

    (Since version ) see corresponding Javadoc for more information.

Inherited from Product

Inherited from Equals

Inherited from KnnModelModelMixed[D]

Inherited from CenterModelMixedLocal[D]

Inherited from CenterModelMixed[D]

Inherited from RLAModelAncestor[MixedVector, D]

Inherited from MetricArgs[MixedVector, D]

Inherited from AlgorithmsArguments

Inherited from CenterModelLocalCz[MixedVector, D]

Inherited from CenterModelCz[MixedVector, D]

Inherited from CenterModelLocal[MixedVector, D]

Inherited from CenterModel[MixedVector, D]

Inherited from KnnModelModelLocalCz[MixedVector, D]

Inherited from KnnModelModelCz[MixedVector, D]

Inherited from KnnModelModelLocal[MixedVector, D]

Inherited from KnnModelModel[MixedVector, D]

Inherited from MetricModel[MixedVector, D]

Inherited from ClusteringModelLocal[MixedVector]

Inherited from ClusteringModel

Inherited from ClusteringSharedTypes

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped