ECOGA Efficient Data Mining Approach for Fuzzy Association Rules

Data mining is concerned with developing algorithms and computational tools and techniques to help people extract patterns from data. In this paper an efficient data mining approach, which is based on fuzzy set theory and clonal selection algorithm, is proposed. The main motivation is to benefit from the global search performed by this kind of algorithms. Experimental results show the number of fuzzy association rules obtained with the proposed method is larger than those obtained by applying other methods.