Uses of Interface
org.hipparchus.clustering.Clusterable

Packages that use Clusterable

Package	Description
org.hipparchus.clustering	Clustering algorithms.
org.hipparchus.clustering.evaluation	Cluster evaluation methods.

Uses of Clusterable in org.hipparchus.clustering

Classes in org.hipparchus.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	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	MultiKMeansPlusPlusClusterer<T extends Clusterable>	A wrapper around a k-means++ clustering algorithm which performs multiple trials and returns the best solution.

Classes in org.hipparchus.clustering that implement Clusterable

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

Methods in org.hipparchus.clustering that return Clusterable

Modifier and Type	Method	Description
Clusterable	CentroidCluster.getCenter()	Get the point chosen to be the center of this cluster.

Methods in org.hipparchus.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.

Constructors in org.hipparchus.clustering with parameters of type Clusterable

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

Uses of Clusterable in org.hipparchus.clustering.evaluation

Classes in org.hipparchus.clustering.evaluation with type parameters of type Clusterable

Modifier and Type	Class	Description
class	ClusterEvaluator<T extends Clusterable>	Base class for cluster evaluation methods.
class	SumOfClusterVariances<T extends Clusterable>	Computes the sum of intra-cluster distance variances according to the formula: \] score = \sum\limits_{i=1}^n \sigma_i^2 \] where n is the number of clusters and \( \sigma_i^2 \) is the variance of intra-cluster distances of cluster \( c_i \).

Methods in org.hipparchus.clustering.evaluation that return Clusterable

Modifier and Type	Method	Description
protected Clusterable	ClusterEvaluator.centroidOf(Cluster<T> cluster)	Computes the centroid for a cluster.

Methods in org.hipparchus.clustering.evaluation with parameters of type Clusterable

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