LocalClusteringChainingBinary

This classe intend to run many algorithms parallely on a local system for medium size datasets, it works for one version of an algorithm with various parameters

O: the raw object from which vectorizations came from
V: the nature of the working vector
Cz: a clusterizable descendant, EasyClusterizable is the basic advise instance
CM: the clustering model type corresponding to the nature of the given algorithm type
Vecto: the current vectorization which gives the current Vector nature
GS: the nature of the collection containing Cz[O, V]
Algorithms: the clustering algorith type
data: the dataset ideally sorted by Cz's IDs, if not it's done automatically
isDatasetSortedByID: a neccessary security due to specific algorithm where model is the entire dataset and then require to be aligned with input data
vectorizations: vectorizations employed on the algorithms list
algorithms: the sequence of algorithms which will be executed at the instantiation of the class

Linear Supertypes

Product, Equals, ChainingOneAlgorithm[O, BinaryVector[V], Cz, GS, Vecto[O, V], CM, Algorithms[V, CM]], ClusteringSharedTypes, Serializable, Serializable, AnyRef, Any

Instance Constructors

new LocalClusteringChainingBinary(data: GS[Cz[O, BinaryVector[V]]], isDatasetSortedByID: Boolean, vectorizations: Seq[Vecto[O, V]], algorithms: Seq[Algorithms[V, CM]], modelsKeeper: ModelsKeeper = new ModelsKeeper)

data
the dataset ideally sorted by Cz's IDs, if not it's done automatically
isDatasetSortedByID
a neccessary security due to specific algorithm where model is the entire dataset and then require to be aligned with input data
vectorizations
vectorizations employed on the algorithms list
algorithms
the sequence of algorithms which will be executed at the instantiation of the class

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 algorithmNature: ClusteringAlgorithmNature

Definition Classes
ChainingOneAlgorithm
final val algorithms: Seq[Algorithms[V, CM]]

the sequence of algorithms which will be executed at the instantiation of the class
the sequence of algorithms which will be executed at the instantiation of the class

Definition Classes
LocalClusteringChainingBinary → ChainingOneAlgorithm
final val algorithmsIndices: Seq[Seq[Int]]

Indices of launched algorithm, ie (previousClusteringNumber until previousClusteringNumber + algorithms.size)
Indices of launched algorithm, ie (previousClusteringNumber until previousClusteringNumber + algorithms.size)

Definition Classes
ChainingOneAlgorithm
final def asInstanceOf[T0]: T0

Definition Classes
Any
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
final val clusteringIDsResults: ParSeq[GS[ClusterID]]

ParSeq of Collection of ClusterID, each ParSeq elem correspond to the given algorithms order
ParSeq of Collection of ClusterID, each ParSeq elem correspond to the given algorithms order

Definition Classes
ChainingOneAlgorithm
final val data: GS[Cz[O, BinaryVector[V]]]

the dataset ideally sorted by Cz's IDs, if not it's done automatically
the dataset ideally sorted by Cz's IDs, if not it's done automatically

Definition Classes
LocalClusteringChainingBinary → ChainingOneAlgorithm
final val dataSortedByID: GS[Cz[O, BinaryVector[V]]]

Definition Classes
ChainingOneAlgorithm
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 getAllModels: Seq[CM]

get all models resulting from given clustering algorithm
get all models resulting from given clustering algorithm

Definition Classes
ChainingOneAlgorithm
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
final def getEveryMIPerClustering(groundTruth: GenSeq[Int]): GenSeq[(Double, Double, Double)]

Definition Classes
ChainingOneAlgorithm
final def getModel(i: Int): Option[CM]

get one model from those resulting from given clustering algorithm
get one model from those resulting from given clustering algorithm

Definition Classes
ChainingOneAlgorithm
final def getModelsFromVecto(vecto: Vecto[O, V]): Seq[CM]

get all models resulting from given clustering algorithm for a particular vectorization
get all models resulting from given clustering algorithm for a particular vectorization

Definition Classes
ChainingOneAlgorithm
final val isDatasetSortedByID: Boolean

a neccessary security due to specific algorithm where model is the entire dataset and then require to be aligned with input data
a neccessary security due to specific algorithm where model is the entire dataset and then require to be aligned with input data

Definition Classes
LocalClusteringChainingBinary → ChainingOneAlgorithm
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
final val modelMapping: ModelsMapping[Int, CM]

Model Mapping required to access to specific model in ModelsKeeper HMAP
Model Mapping required to access to specific model in ModelsKeeper HMAP

Definition Classes
ChainingOneAlgorithm
final val modelsKeeper: ModelsKeeper

Definition Classes
LocalClusteringChainingBinary → ChainingOneAlgorithm
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 obtainSortedClusterizedData: GS[Cz[O, BinaryVector[V]]]

The Dataset vectorization is the original one
The Dataset vectorization is the original one
returns
the linked dataset between clusterizable and their associate clusteringIDs sorted by clusterizable ID

Definition Classes
ChainingOneAlgorithm
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
final val vectorizations: Seq[Vecto[O, V]]

vectorizations employed on the algorithms list
vectorizations employed on the algorithms list

Definition Classes
LocalClusteringChainingBinary → ChainingOneAlgorithm
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 chaining

Instance Constructors

new LocalClusteringChainingBinary(data: GS[Cz[O, BinaryVector[V]]], isDatasetSortedByID: Boolean, vectorizations: Seq[Vecto[O, V]], algorithms: Seq[Algorithms[V, CM]], modelsKeeper: ModelsKeeper = new ModelsKeeper)

Type Members

final type ClusterID = Int

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final val algorithmNature: ClusteringAlgorithmNature

final val algorithms: Seq[Algorithms[V, CM]]

final val algorithmsIndices: Seq[Seq[Int]]

final def asInstanceOf[T0]: T0

def clone(): AnyRef

final val clusteringIDsResults: ParSeq[GS[ClusterID]]

final val data: GS[Cz[O, BinaryVector[V]]]

final val dataSortedByID: GS[Cz[O, BinaryVector[V]]]

final def eq(arg0: AnyRef): Boolean

def finalize(): Unit

final def getAllModels: Seq[CM]

final def getClass(): Class[_]

final def getEveryMIPerClustering(groundTruth: GenSeq[Int]): GenSeq[(Double, Double, Double)]

final def getModel(i: Int): Option[CM]

final def getModelsFromVecto(vecto: Vecto[O, V]): Seq[CM]

final val isDatasetSortedByID: Boolean

final def isInstanceOf[T0]: Boolean

final val modelMapping: ModelsMapping[Int, CM]

final val modelsKeeper: ModelsKeeper

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

final def obtainSortedClusterizedData: GS[Cz[O, BinaryVector[V]]]

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

final val vectorizations: Seq[Vecto[O, V]]

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 ChainingOneAlgorithm[O, BinaryVector[V], Cz, GS, Vecto[O, V], CM, Algorithms[V, CM]]

Inherited from ClusteringSharedTypes

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped