A GA-based approach for mining membership functions and concept-drift patterns

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题名:	A GA-based approach for mining membership functions and concept-drift patterns
作者:	Chen, C. H.;Li, Y.;Hong, T. P.;Li, Y. K.;Lu, E. H. C.
关键词:	concept drift;data mining;fuzzy association rules;genetic algorithms;membership functions
日期:	2015-05-25
上传时间:	2016-04-27 11:11:30 (UTC+8)
出版者:	IEEE
摘要:	Since customers' behaviors may change over time in real applications, algorithms that can be utilized to mine these drift patterns are needed. In this paper, we propose a GA-based approach for mining fuzzy concept-drift patterns. It consists of two phases. The first phase mines membership functions and the second one finds fuzzy concept-drift patterns. In the first phase, appropriate membership functions for items are derived by GA with a designed fitness function. Then, the derived membership functions are utilized to mine fuzzy concept-drift patterns in the second phase. Experiments on simulated datasets are also made to show the effectiveness of the proposed approach.
關聯:	Evolutionary Computation (CEC), 2015 IEEE, pp.2961-2965
DOI:	10.1109/CEC.2015.7257257
显示于类别:	[資訊工程學系暨研究所] 會議論文

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