Title :
New results in fuzzy clustering based on the concept of indistinguishability relation
Author :
De Mantaras, R. Lopez ; Valverde, L.
Author_Institution :
Polytech. Univ. of Barcelona, Spain
Abstract :
The issue of validity in clustering is considered and a definition of fuzzy r-cluster that extends E. Ruspini´s definition (1982) is proposed. This definition is based on an indistinguishability relation based on the concept of t-norm. The fuzzy r-cluster´s metrical properties are studied through the dual concept of t-conorm that leads to G-pseudometrics. From the concept of G-pseudometric, fuzzy r-clusters and fuzzy cluster coverages are defined. The authors propose a measure of cluster validity based on the concept of fuzzy coverage. The basic idea of the approach presented is that the smaller the difference between the degrees of membership and the degrees of indistinguishability, the better the clustering.<>
Keywords :
fuzzy set theory; pattern recognition; G-pseudometrics concept; dual concept; fuzzy clustering; fuzzy set theory; indistinguishability relation; pattern recognition; Clustering algorithms; Contracts; Fuzzy sets; Graph theory; Length measurement; Partitioning algorithms; Prototypes;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on