Uses of Interface org.hipparchus.clustering.distance.DistanceMeasure (Hipparchus 3.0 API)

Packages that use DistanceMeasure
Package	Description
org.hipparchus.clustering	Clustering algorithms.
org.hipparchus.clustering.distance	Common distance measures.
org.hipparchus.clustering.evaluation	Cluster evaluation methods.

Uses of DistanceMeasure in org.hipparchus.clustering

Methods in org.hipparchus.clustering that return DistanceMeasure
Modifier and Type	Method	Description
`DistanceMeasure`	Clusterer.`getDistanceMeasure()`	Returns the `DistanceMeasure` instance used by this clusterer.

Constructors in org.hipparchus.clustering with parameters of type DistanceMeasure
Constructor	Description
`Clusterer(DistanceMeasure measure)`	Build a new clusterer with the given `DistanceMeasure`.
`DBSCANClusterer(double eps, int minPts, DistanceMeasure measure)`	Creates a new instance of a DBSCANClusterer.
`FuzzyKMeansClusterer(int k, double fuzziness, int maxIterations, DistanceMeasure measure)`	Creates a new instance of a FuzzyKMeansClusterer.
`FuzzyKMeansClusterer(int k, double fuzziness, int maxIterations, DistanceMeasure measure, double epsilon, RandomGenerator random)`	Creates a new instance of a FuzzyKMeansClusterer.
`KMeansPlusPlusClusterer(int k, int maxIterations, DistanceMeasure measure)`	Build a clusterer.
`KMeansPlusPlusClusterer(int k, int maxIterations, DistanceMeasure measure, RandomGenerator random)`	Build a clusterer.
`KMeansPlusPlusClusterer(int k, int maxIterations, DistanceMeasure measure, RandomGenerator random, KMeansPlusPlusClusterer.EmptyClusterStrategy emptyStrategy)`	Build a clusterer.

Uses of DistanceMeasure in org.hipparchus.clustering.distance

Classes in org.hipparchus.clustering.distance that implement DistanceMeasure
Modifier and Type	Class	Description
`class`	`CanberraDistance`	Calculates the Canberra distance between two points.
`class`	`ChebyshevDistance`	Calculates the L_∞ (max of abs) distance between two points.
`class`	`EarthMoversDistance`	Calculates the Earh Mover's distance (also known as Wasserstein metric) between two distributions.
`class`	`EuclideanDistance`	Calculates the L₂ (Euclidean) distance between two points.
`class`	`ManhattanDistance`	Calculates the L₁ (sum of abs) distance between two points.

Uses of DistanceMeasure in org.hipparchus.clustering.evaluation

Constructors in org.hipparchus.clustering.evaluation with parameters of type DistanceMeasure
Constructor	Description
`ClusterEvaluator(DistanceMeasure measure)`	Creates a new cluster evaluator with the given distance measure.
`SumOfClusterVariances(DistanceMeasure measure)`	Simple constructor.