Class

org.clustering4ever.clustering.kcenters.scala

KModesModel

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final case class KModesModel[V <: Seq[Int], D[X <: Seq[Int]] <: BinaryDistance[X]](k: Int, metric: D[V], epsilon: Double, maxIterations: Int, centers: HashMap[Int, BinaryVector[V]] = ...) extends ClusteringModelLocalBinary[V] with KCentersModelAncestor[BinaryVector[V], D[V]] with CenterModelLocalBinary[V, D[V]] with KnnModelModelBinary[V, D[V]] with Product with Serializable

KModes model

Linear Supertypes
Product, Equals, KnnModelModelBinary[V, D[V]], KnnModelSimpleV[Int, V, BinaryVector[V], D[V]], KnnModelModel[BinaryVector[V], D[V]], CenterModelLocalBinary[V, D[V]], CenterModelSimpleVLocal[Int, V, BinaryVector[V], D[V]], CenterModelSimpleV[Int, V, BinaryVector[V], D[V]], KCentersModelAncestor[BinaryVector[V], D[V]], CenterModelLocalCz[BinaryVector[V], D[V]], CenterModelCz[BinaryVector[V], D[V]], CenterModelLocal[BinaryVector[V], D[V]], KCentersModelCommons[BinaryVector[V], D[V]], CenterModel[BinaryVector[V], D[V]], MetricModel[BinaryVector[V], D[V]], ClusteringModelLocalBinary[V], ClusteringModelLocal[BinaryVector[V]], ClusteringModel, ClusteringSharedTypes, Serializable, Serializable, AnyRef, Any
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Inherited
  1. KModesModel
  2. Product
  3. Equals
  4. KnnModelModelBinary
  5. KnnModelSimpleV
  6. KnnModelModel
  7. CenterModelLocalBinary
  8. CenterModelSimpleVLocal
  9. CenterModelSimpleV
  10. KCentersModelAncestor
  11. CenterModelLocalCz
  12. CenterModelCz
  13. CenterModelLocal
  14. KCentersModelCommons
  15. CenterModel
  16. MetricModel
  17. ClusteringModelLocalBinary
  18. ClusteringModelLocal
  19. ClusteringModel
  20. ClusteringSharedTypes
  21. Serializable
  22. Serializable
  23. AnyRef
  24. Any
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Visibility
  1. Public
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Instance Constructors

  1. new KModesModel(k: Int, metric: D[V], epsilon: Double, maxIterations: Int, centers: HashMap[Int, BinaryVector[V]] = ...)

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Type Members

  1. 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.KModes.type

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    Definition Classes
    KModesModel → ClusteringModel

  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

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

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    Definition Classes
    CenterModelSimpleVLocal

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

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    Definition Classes
    CenterModelSimpleV

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

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    Definition Classes
    CenterModelLocalCz

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

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    Definition Classes
    CenterModelCz

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

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    Definition Classes
    CenterModelLocal

  11. def centerPredict(v: BinaryVector[V]): ClusterID

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    Definition Classes
    CenterModel

  12. final val centers: HashMap[Int, BinaryVector[V]]

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    Definition Classes
    KModesModel → CenterModel

  13. def clone(): AnyRef

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

  14. final val epsilon: Double

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    The stopping threshold for iterations

    The stopping threshold for iterations

    Definition Classes
    KModesModel → KCentersModelCommons

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

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    Definition Classes
    AnyRef

  16. def finalize(): Unit

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

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

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    Definition Classes
    AnyRef → Any

  18. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  19. final val k: Int

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    The number of initial seeked clusters, the real number of cluster can be smaller, cf centers.size

    The number of initial seeked clusters, the real number of cluster can be smaller, cf centers.size

    Definition Classes
    KModesModel → KCentersModelCommons

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

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    Definition Classes
    KnnModelSimpleV

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

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    Definition Classes
    KnnModelModel

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

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    Definition Classes
    KnnModelModel

  23. final val maxIterations: Int

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    The maximum number of authorized iterations

    The maximum number of authorized iterations

    Definition Classes
    KModesModel → KCentersModelCommons

  24. final val metric: D[V]

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    Definition Classes
    KModesModel → MetricModel

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

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    Definition Classes
    AnyRef

  26. final def notify(): Unit

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    Definition Classes
    AnyRef

  27. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

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

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

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

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

  30. final def prototypesDistancePerPoint[O, Cz[Y, Z <: GVector[Z]] <: Clusterizable[Y, Z, Cz], GS[X] <: GenSeq[X]](data: GS[Cz[O, BinaryVector[V]]]): GS[(Cz[O, BinaryVector[V]], HashMap[ClusterID, Double])]

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    Compute the distance between every points and all centers

    Compute the distance between every points and all centers

    Definition Classes
    KCentersModelAncestor

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

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    Definition Classes
    AnyRef

  32. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  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( ... )

Inherited from Product

Inherited from Equals

Inherited from KnnModelModelBinary[V, D[V]]

Inherited from KnnModelSimpleV[Int, V, BinaryVector[V], D[V]]

Inherited from KnnModelModel[BinaryVector[V], D[V]]

Inherited from CenterModelLocalBinary[V, D[V]]

Inherited from CenterModelSimpleVLocal[Int, V, BinaryVector[V], D[V]]

Inherited from CenterModelSimpleV[Int, V, BinaryVector[V], D[V]]

Inherited from KCentersModelAncestor[BinaryVector[V], D[V]]

Inherited from CenterModelLocalCz[BinaryVector[V], D[V]]

Inherited from CenterModelCz[BinaryVector[V], D[V]]

Inherited from CenterModelLocal[BinaryVector[V], D[V]]

Inherited from KCentersModelCommons[BinaryVector[V], D[V]]

Inherited from CenterModel[BinaryVector[V], D[V]]

Inherited from MetricModel[BinaryVector[V], D[V]]

Inherited from ClusteringModelLocalBinary[V]

Inherited from ClusteringModelLocal[BinaryVector[V]]

Inherited from ClusteringModel

Inherited from ClusteringSharedTypes

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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