Uses of Interface
org.hipparchus.clustering.distance.DistanceMeasure
Package
Description
Clustering algorithms.
Common distance measures.
Cluster evaluation methods.
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Uses of DistanceMeasure in org.hipparchus.clustering
Modifier and TypeMethodDescriptionClusterer.getDistanceMeasure()
Returns theDistanceMeasure
instance used by this clusterer.ModifierConstructorDescriptionprotected
Clusterer
(DistanceMeasure measure) Build a new clusterer with the givenDistanceMeasure
.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
Modifier and TypeClassDescriptionclass
Calculates the Canberra distance between two points.class
Calculates the L∞ (max of abs) distance between two points.class
Calculates the Earh Mover's distance (also known as Wasserstein metric) between two distributions.class
Calculates the L2 (Euclidean) distance between two points.class
Calculates the L1 (sum of abs) distance between two points. -
Uses of DistanceMeasure in org.hipparchus.clustering.evaluation
ModifierConstructorDescriptionClusterEvaluator
(DistanceMeasure measure) Creates a new cluster evaluator with the given distance measure.SumOfClusterVariances
(DistanceMeasure measure) Simple constructor.