KCenters

Instance Constructors

new KCenters(k: Int, metric: D[V], epsilon: Double, maxIterations: Int, customCenters: HashMap[Int, V] = immutable.HashMap.empty[Int, V])

Type Members

final type ClusterID = Int

Definition Classes
ClusteringSharedTypes

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final val algorithmID: extensibleAlgorithmNature.KCenters.type

Definition Classes
KCenters → ClusteringAlgorithm
final def areCentersNotMovingEnough(updatedCenters: ArrayBuffer[(Int, V)], previousCenters: ArrayBuffer[(Int, V)], epsilon: Double, metric: D[V]): Boolean

Check if centers move enough
Check if centers move enough
returns
true if every centers move less than epsilon

Attributes
protected[org.clustering4ever.clustering.kcenters]
Definition Classes
KCommons
final def asInstanceOf[T0]: T0

Definition Classes
Any
final def castModel(model: ClusteringModelLocal[V]): Option[KCentersModel[V, D]]

Definition Classes
ClusteringAlgorithmLocal
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
final val customCenters: HashMap[Int, V]

A custom centers initialiazation, empty HashMap by default which result usage of K++ initialization
A custom centers initialiazation, empty HashMap by default which result usage of K++ initialization

Definition Classes
KCenters → KCommons
final val epsilon: Double

The stopping criteria, ie the distance under which centers are mooving from their previous position
The stopping criteria, ie the distance under which centers are mooving from their previous position

Definition Classes
KCenters → KCommons
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
final val k: Int

The number of cluster seeked
The number of cluster seeked

Definition Classes
KCenters → KCommons
final val maxIterations: Int

The maximum number of iterations
The maximum number of iterations

Definition Classes
KCenters → KCommons
final val metric: D[V]

The employed metric on the GVector descendant
The employed metric on the GVector descendant

Definition Classes
KCenters → KCommons
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
final def obtainCenters[O, Cz[B, C <: GVector[C]] <: Clusterizable[B, C, Cz], GS[X] <: GenSeq[X]](data: GS[Cz[O, V]]): HashMap[Int, V]

Run the K-Centers
Run the K-Centers

Attributes
protected[org.clustering4ever.clustering.kcenters]
Definition Classes
KCentersAncestor
final def obtainNearestCenterID(v: V, centers: ArrayBuffer[(Int, V)], metric: D[V]): ClusterID

Attributes
protected[org.clustering4ever.clustering.kcenters]
Definition Classes
KCommons
final def run[O, Cz[B, C <: GVector[C]] <: Clusterizable[B, C, Cz], GS[X] <: GenSeq[X]](data: GS[Cz[O, V]]): KCentersModel[V, D]

Definition Classes
KCenters → ClusteringAlgorithmLocal
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )

Related Doc: package scala

final case class KCenters[V <: GVector[V], D[X <: GVector[X]] <: Distance[X]](k: Int, metric: D[V], epsilon: Double, maxIterations: Int, customCenters: HashMap[Int, V] = immutable.HashMap.empty[Int, V]) extends KCentersAncestor[V, D[V], KCentersModel[V, D]] with Product with Serializable

Instance Constructors

new KCenters(k: Int, metric: D[V], epsilon: Double, maxIterations: Int, customCenters: HashMap[Int, V] = immutable.HashMap.empty[Int, V])

Type Members

final type ClusterID = Int

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final val algorithmID: extensibleAlgorithmNature.KCenters.type

final def areCentersNotMovingEnough(updatedCenters: ArrayBuffer[(Int, V)], previousCenters: ArrayBuffer[(Int, V)], epsilon: Double, metric: D[V]): Boolean

final def asInstanceOf[T0]: T0

final def castModel(model: ClusteringModelLocal[V]): Option[KCentersModel[V, D]]

def clone(): AnyRef

final val customCenters: HashMap[Int, V]

final val epsilon: Double

final def eq(arg0: AnyRef): Boolean

def finalize(): Unit

final def getClass(): Class[_]

final def isInstanceOf[T0]: Boolean

final val k: Int

final val maxIterations: Int

final val metric: D[V]

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

final def obtainCenters[O, Cz[B, C <: GVector[C]] <: Clusterizable[B, C, Cz], GS[X] <: GenSeq[X]](data: GS[Cz[O, V]]): HashMap[Int, V]

final def obtainNearestCenterID(v: V, centers: ArrayBuffer[(Int, V)], metric: D[V]): ClusterID

final def run[O, Cz[B, C <: GVector[C]] <: Clusterizable[B, C, Cz], GS[X] <: GenSeq[X]](data: GS[Cz[O, V]]): KCentersModel[V, D]

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

final def wait(): Unit

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

final def wait(arg0: Long): Unit

Inherited from Product

Inherited from Equals

Inherited from KCentersAncestor[V, D[V], KCentersModel[V, D]]

Inherited from ClusteringAlgorithmLocal[V, KCentersModel[V, D]]

Inherited from ClusteringAlgorithm

Inherited from KCommons[V, D[V]]

Inherited from ClusteringSharedTypes

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped