ECM: An evidential version of the fuzzy c-means algorithm

Authors:
Marie-Hélène Masson;T. Denux
Affiliations:
UMR CNRS 6599 Heudiasyc, Université de Technologie de Compiègne BP 20529, F-60205 Compiègne, Cedex, France;UMR CNRS 6599 Heudiasyc, Université de Technologie de Compiègne BP 20529, F-60205 Compiègne, Cedex, France
Venue:
Pattern Recognition
Year:
2008

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Abstract

A new clustering method for object data, called ECM (evidential c-means) is introduced, in the theoretical framework of belief functions. It is based on the concept of credal partition, extending those of hard, fuzzy, and possibilistic ones. To derive such a structure, a suitable objective function is minimized using an FCM-like algorithm. A validity index allowing the determination of the proper number of clusters is also proposed. Experiments with synthetic and real data sets show that the proposed algorithm can be considered as a promising tool in the field of exploratory statistics.