Uses of Interface
org.apache.commons.math4.legacy.ml.distance.DistanceMeasure
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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. -
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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 DistanceMeasureClusterer. getDistanceMeasure()Returns theDistanceMeasureinstance 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 givenDistanceMeasure.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 classCanberraDistanceCalculates the Canberra distance between two points.classChebyshevDistanceCalculates the L∞ (max of abs) distance between two points.classEarthMoversDistanceCalculates the Earh Mover's distance (also known as Wasserstein metric) between two distributions.classEuclideanDistanceCalculates the L2 (Euclidean) distance between two points.classManhattanDistanceCalculates the L1 (sum of abs) distance between two points.
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