A Family of Cluster Validity Indexes Based on a l-Order Fuzzy OR Operator

Authors:
Hoel Capitaine;Carl Frélicot
Affiliations:
MIA Laboratory, University of La Rochelle, La Rochelle, France 17042 Cedex;MIA Laboratory, University of La Rochelle, La Rochelle, France 17042 Cedex
Venue:
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Year:
2008

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Abstract

Clustering is one of the most important task in pattern recognition. For most of partitional clustering algorithms, a partition that represents as much as possible the structure of the data is generated. In this paper, we adress the problem of finding the optimal number of clusters from data. This can be done by introducing an index which evaluates the validity of the generated fuzzy c -partition. We propose to use a criterion based on the fuzzy combination of membership values which quantifies the l -order overlap and the intercluster separation of a given pattern.