Uses of Package
de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain

Packages that use de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain

Package	Description
de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain	Clustering algorithms for uncertain data.

Classes in de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain used by de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain

Class and Description
CenterOfMassMetaClustering Center-of-mass meta clustering reduces uncertain objects to their center of mass, then runs a vector-oriented clustering algorithm on this data set.
CKMeans Run k-means on the centers of each uncertain object.
FDBSCAN FDBSCAN is an adaption of DBSCAN for fuzzy (uncertain) objects.
FDBSCANNeighborPredicate Density-based Clustering of Applications with Noise and Fuzzy objects (FDBSCAN) is an Algorithm to find sets in a fuzzy database that are density-connected with minimum probability.
FDBSCANNeighborPredicate.Instance Instance of the neighbor predicate.
RepresentativeUncertainClustering Representative clustering of uncertain data.
UKMeans Uncertain K-Means clustering, using the average deviation from the center.