Multiobjective fuzzy clustering approach based on tissue-like membrane systems

Abstract

Fuzzy clustering problem is usually posed as an optimization problem. However, the existing researchhas shown that clustering technique that optimizes a single cluster validity index may not provide satisfactory results on different kinds of data sets. This paper proposes a multiobjective clustering frameworkfor fuzzy clustering, in which a tissue-like membrane system with a special cell structure is designed tointegrate a non-dominated sorting technique and a modified differential evolution mechanism. Based onthe multiobjective clustering framework, a fuzzy clustering approach is realized to optimize three cluster validity indices that can capture different characteristics. The proposed approach is evaluated on sixartificial and ten real-life data sets and is compared with several multiobjective and singleobjective techniques. The comparison results demonstrate the effectiveness and advantage of the proposed approachon clustering the data sets with different characteristics.