In this paper, we adopt a more sophisticated multi-objective approach, SPEA2, to find appropriate sets of membership functions for fuzzy data mining. Two objective functions are used to find the Pareto front. The first one is to minimize the suitability of membership functions and the second one is to maximize the total number of large 1-itemsets. An experimental comparison with the previous approach is also made to show the effectiveness of the proposed approach in finding the Pareto-front membership functions.
['Chun-Hao Chen', 'Tzung-Pei Hong', 'Vincent S. Tseng']
A SPEA2-based genetic-fuzzy mining algorithm