Clustering of vaguely defined objects

Libor Zak

Address. Department of Mathematics, Technical University of Brno, Technicka 2, 616 69 Brno, Czech Republic


This paper is concerned with the clustering of objects whose properties cannot be
described by exact data. These can only be described by fuzzy sets or by linguistic
values of previously defined linguistic variables. To cluster these objects we use a
generalization of classic clustering methods in which instead of similarity (dissimilarity)
of objects, used fuzzy similarity (fuzzy dissimilarity) to define the clustering of fuzzy objects.

AMSclassification. 91C20, 26E50.

Keywords. Fuzzy sets, extension principle, clustering methods, fuzzy clustering.