DocumentCode
2308183
Title
A SPEA2-based genetic-fuzzy mining algorithm
Author
Chen, Chun-Hao ; Hong, Tzung-Pei ; Tseng, Vincent S.
Author_Institution
Dept. of Comput. Sci. & Inf. Eng., Tamkang Univ., Taipei, Taiwan
fYear
2010
fDate
18-23 July 2010
Firstpage
1
Lastpage
5
Abstract
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.
Keywords
Pareto optimisation; data mining; fuzzy set theory; genetic algorithms; Pareto-front membership functions; SPEA2-based genetic-fuzzy mining algorithm; fuzzy data mining; Association rules; Biological cells; Computer science; Evolutionary computation; Optimization; Pragmatics;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems (FUZZ), 2010 IEEE International Conference on
Conference_Location
Barcelona
ISSN
1098-7584
Print_ISBN
978-1-4244-6919-2
Type
conf
DOI
10.1109/FUZZY.2010.5584376
Filename
5584376
Link To Document