Uses of Interface
org.apache.commons.math4.legacy.ml.distance.DistanceMeasure

Packages that use DistanceMeasure

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

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

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

Modifier and Type	Method	Description
DistanceMeasure	Clusterer.getDistanceMeasure()	Returns the DistanceMeasure instance used by this clusterer.

Constructors in org.apache.commons.math4.legacy.ml.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.
ElkanKMeansPlusPlusClusterer(int k, int maxIterations, DistanceMeasure measure, org.apache.commons.rng.UniformRandomProvider random)
ElkanKMeansPlusPlusClusterer(int k, int maxIterations, DistanceMeasure measure, org.apache.commons.rng.UniformRandomProvider random, KMeansPlusPlusClusterer.EmptyClusterStrategy emptyStrategy)
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, org.apache.commons.rng.UniformRandomProvider 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, org.apache.commons.rng.UniformRandomProvider random)	Build a clusterer.
KMeansPlusPlusClusterer(int k, int maxIterations, DistanceMeasure measure, org.apache.commons.rng.UniformRandomProvider random, KMeansPlusPlusClusterer.EmptyClusterStrategy emptyStrategy)	Build a clusterer.
MiniBatchKMeansClusterer(int k, int maxIterations, int batchSize, int initIterations, int initBatchSize, int maxNoImprovementTimes, DistanceMeasure measure, org.apache.commons.rng.UniformRandomProvider random, KMeansPlusPlusClusterer.EmptyClusterStrategy emptyStrategy)	Build a clusterer.

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

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

Constructor	Description
SumOfClusterVariances(DistanceMeasure measure)

Uses of DistanceMeasure in org.apache.commons.math4.legacy.ml.distance

Classes in org.apache.commons.math4.legacy.ml.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.