Package elki.clustering.uncertain
Clustering algorithms for uncertain data.

Class Summary Class Description CenterOfMassMetaClustering<C extends Clustering<?>> Centerofmass meta clustering reduces uncertain objects to their center of mass, then runs a vectororiented clustering algorithm on this data set.CenterOfMassMetaClustering.Par<C extends Clustering<?>> Parameterization class.CKMeans Run kmeans on the centers of each uncertain object.CKMeans.Par Parameterization class, based on kmeans.FDBSCAN FDBSCAN is an adaption of DBSCAN for fuzzy (uncertain) objects.FDBSCAN.Par Parameterizer class.FDBSCANNeighborPredicate Densitybased Clustering of Applications with Noise and Fuzzy objects (FDBSCAN) is an Algorithm to find sets in a fuzzy database that are densityconnected with minimum probability.FDBSCANNeighborPredicate.Instance Instance of the neighbor predicate.FDBSCANNeighborPredicate.Par Parameterizer class.RepresentativeUncertainClustering Representative clustering of uncertain data.RepresentativeUncertainClustering.Par Parameterization class.RepresentativeUncertainClustering.RepresentativenessEvaluation Representativeness evaluation result.UKMeans Uncertain KMeans clustering, using the average deviation from the center.UKMeans.Par Parameterization class.