Uses of Interface
org.apache.commons.math4.legacy.ml.clustering.Clusterable

Packages that use Clusterable

Package	Description
org.apache.commons.math4.legacy.ml.clustering	Clustering algorithms.
org.apache.commons.math4.legacy.ml.clustering.evaluation	Cluster evaluation methods.

Uses of Clusterable in org.apache.commons.math4.legacy.ml.clustering

Classes in org.apache.commons.math4.legacy.ml.clustering with type parameters of type Clusterable

Modifier and Type	Class	Description
class	CentroidCluster<T extends Clusterable>	A Cluster used by centroid-based clustering algorithms.
class	Cluster<T extends Clusterable>	Cluster holding a set of Clusterable points.
class	Clusterer<T extends Clusterable>	Base class for clustering algorithms.
class	DBSCANClusterer<T extends Clusterable>	DBSCAN (density-based spatial clustering of applications with noise) algorithm.
class	ElkanKMeansPlusPlusClusterer<T extends Clusterable>	Implementation of k-means++ algorithm.
class	FuzzyKMeansClusterer<T extends Clusterable>	Fuzzy K-Means clustering algorithm.
class	KMeansPlusPlusClusterer<T extends Clusterable>	Clustering algorithm based on David Arthur and Sergei Vassilvitski k-means++ algorithm.
class	MiniBatchKMeansClusterer<T extends Clusterable>	Clustering algorithm based on KMeans.
class	MultiKMeansPlusPlusClusterer<T extends Clusterable>	A wrapper around a k-means++ clustering algorithm which performs multiple trials and returns the best solution.

Classes in org.apache.commons.math4.legacy.ml.clustering that implement Clusterable

Modifier and Type	Class	Description
class	DoublePoint	A simple implementation of Clusterable for points with double coordinates.

Methods in org.apache.commons.math4.legacy.ml.clustering with type parameters of type Clusterable

Modifier and Type	Method	Description
static <T extends Clusterable> ClusterRanking	ClusterEvaluator.ranking(ClusterEvaluator eval)	Converts to a ranking function (as required by clustering implementations).

Methods in org.apache.commons.math4.legacy.ml.clustering that return Clusterable

Modifier and Type	Method	Description
Clusterable	Cluster.centroid()	Computes the centroid of the cluster.

Methods in org.apache.commons.math4.legacy.ml.clustering with parameters of type Clusterable

Modifier and Type	Method	Description
protected double	Clusterer.distance(Clusterable p1, Clusterable p2)	Calculates the distance between two Clusterable instances with the configured DistanceMeasure.

Method parameters in org.apache.commons.math4.legacy.ml.clustering with type arguments of type Clusterable

Modifier and Type	Method	Description
double	ClusterRanking.compute(List<? extends Cluster<? extends Clusterable>> clusters)	Computes the rank (higher is better).
double	ClusterEvaluator.score(List<? extends Cluster<? extends Clusterable>> cList)

Constructors in org.apache.commons.math4.legacy.ml.clustering with parameters of type Clusterable

Constructor	Description
CentroidCluster(Clusterable center)	Build a cluster centered at a specified point.

Uses of Clusterable in org.apache.commons.math4.legacy.ml.clustering.evaluation

Method parameters in org.apache.commons.math4.legacy.ml.clustering.evaluation with type arguments of type Clusterable

Modifier and Type	Method	Description
double	CalinskiHarabasz.score(List<? extends Cluster<? extends Clusterable>> clusters)
double	SumOfClusterVariances.score(List<? extends Cluster<? extends Clusterable>> clusters)