Class

org.clustering4ever.clustering.rla

RLAModel

Related Doc: package rla

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case class RLAModel[V <: GVector[V], D[X <: GVector[X]] <: Distance[X]](metric: D[V], epsilon: Double, centers: HashMap[Int, V]) extends RLAModelAncestor[V, D[V]] with KnnModelModel[V, D[V]] with Product with Serializable

Linear Supertypes
Product, Equals, RLAModelAncestor[V, D[V]], CenterModelLocalCz[V, D[V]], CenterModelCz[V, D[V]], CenterModelLocal[V, D[V]], CenterModel[V, D[V]], KnnModelModelLocalCz[V, D[V]], KnnModelModelCz[V, D[V]], KnnModelModelLocal[V, D[V]], KnnModelModel[V, D[V]], MetricModel[V, D[V]], ClusteringModelLocal[V], ClusteringModel, ClusteringSharedTypes, Serializable, Serializable, AnyRef, Any
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Inherited
  1. RLAModel
  2. Product
  3. Equals
  4. RLAModelAncestor
  5. CenterModelLocalCz
  6. CenterModelCz
  7. CenterModelLocal
  8. CenterModel
  9. KnnModelModelLocalCz
  10. KnnModelModelCz
  11. KnnModelModelLocal
  12. KnnModelModel
  13. MetricModel
  14. ClusteringModelLocal
  15. ClusteringModel
  16. ClusteringSharedTypes
  17. Serializable
  18. Serializable
  19. AnyRef
  20. Any
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Visibility
  1. Public
  2. All

Instance Constructors

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

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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.RLA.type

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    Definition Classes
    RLAModel → ClusteringModel

  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

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

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    Definition Classes
    CenterModelLocalCz

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

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    Definition Classes
    CenterModelCz

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

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    Definition Classes
    CenterModelLocal

  9. final def centerPredict(v: V): ClusterID

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    Definition Classes
    CenterModel

  10. val centers: HashMap[Int, V]

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    Definition Classes
    RLAModel → CenterModel

  11. def clone(): AnyRef

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

  12. val epsilon: Double

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    Definition Classes
    RLAModel → RLAModelAncestor

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

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    Definition Classes
    AnyRef

  14. def finalize(): Unit

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

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

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    Definition Classes
    AnyRef → Any

  16. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

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

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    Definition Classes
    KnnModelModelLocalCz

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

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    Definition Classes
    KnnModelModelCz

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

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    Definition Classes
    KnnModelModelLocal

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

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    Definition Classes
    KnnModelModel

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

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    Definition Classes
    KnnModelModelCz

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

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    Definition Classes
    KnnModelModel

  23. val metric: D[V]

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    Definition Classes
    RLAModel → MetricModel

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

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    Definition Classes
    AnyRef

  25. final def notify(): Unit

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    Definition Classes
    AnyRef

  26. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

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

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

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

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

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

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    Definition Classes
    AnyRef

  30. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Product

Inherited from Equals

Inherited from RLAModelAncestor[V, D[V]]

Inherited from CenterModelLocalCz[V, D[V]]

Inherited from CenterModelCz[V, D[V]]

Inherited from CenterModelLocal[V, D[V]]

Inherited from CenterModel[V, D[V]]

Inherited from KnnModelModelLocalCz[V, D[V]]

Inherited from KnnModelModelCz[V, D[V]]

Inherited from KnnModelModelLocal[V, D[V]]

Inherited from KnnModelModel[V, D[V]]

Inherited from MetricModel[V, D[V]]

Inherited from ClusteringModelLocal[V]

Inherited from ClusteringModel

Inherited from ClusteringSharedTypes

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped