Multi-objective genetic algorithm based method for mining optimized fuzzy association rules - Kaya, M; Alhajj, R (Springer-Verlag Berlin, 2004)
This paper introduces optimized fuzzy association rules mining. We propose a multi-objective Genetic Algorithm (GA) based approach for mining fuzzy association rules containing instantiated and uninstantiated attributes. According to our method, fuzzy association rules can contain an arbitrary number of uninstantiated attributes. The method uses three objectives for the rule mining process: support, confidence and number of fuzzy sets. Experimental results conducted on a real data set demonstrate the effectiveness and applicability of the proposed approach.
5th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2004) -- AUG 25-27, 2004 -- Execter, ENGLAND