title: A multi-clustering fusion scheme for data partitioning.
abstract: A multi-clustering fusion method is presented based on combining several runs of a clustering algorithm resulting in a common partition. More specifically, the results of several independent runs of the same clustering algorithm are appropriately combined to obtain a distinct partition of the data which is not affected by initialization and overcomes the instabilities of clustering methods. Subsequently, a fusion procedure is applied to the clusters generated during the previous phase to determine the optimal number of clusters in the data set according to some predefined criteria.
authors.affiliation: National Technical University of Athens, School of Electrical and Computer Engineering, Zographou 157 80, Athens, Greece. dfros@cslab.ntua.gr
authors.forename: Dimitrios S
authors.initials: DS
authors.lastname: Frossyniotis
authors.forename: Christos
authors.initials: C
authors.lastname: Pateritsas
authors.forename: Andreas
authors.initials: A
authors.lastname: Stafylopatis
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003628:Database Management Systems