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Facilitating fuzzy association rules mining by using multi-objective genetic algorithms for automated clustering

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2 Author(s)
Kaya, M. ; Dept. of Comput. Eng., Firat Univ., Elazig, Turkey ; Alhajj, R.

We propose an automated clustering method based on multiobjective genetic algorithms (GA); the aim of this method is to automatically cluster values of a given quantitative attribute to obtain large number of large itemsets in low duration (time). We compare the proposed multi-objective GA-based approach with CURE-based approach. In addition to the autonomous specification of fuzzy sets, experimental results showed that the proposed automated clustering exhibits good performance over CURE-based approach in terms of runtime as well as the number of large itemsets and interesting association rules.

Published in:

Data Mining, 2003. ICDM 2003. Third IEEE International Conference on

Date of Conference:

19-22 Nov. 2003