關鍵字查詢 | 類別:會議論文 | | 關鍵字:A GA-based approach for mining membership functions and concept-drift patterns

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序號 學年期 教師動態
1 103/2 資工系 陳俊豪 教授 會議論文 發佈 A GA-based approach for mining membership functions and concept-drift patterns , [103-2] :A GA-based approach for mining membership functions and concept-drift patterns會議論文A GA-based approach for mining membership functions and concept-drift patternsC. H. Chen; Y. Li; T. P. Hong; Y. K. Li; E. H. C. Luconcept drift;data mining;fuzzy association rules;genetic algorithms;membership functionsEvolutionary Computation (CEC), 2015 IEEE, pp.2961-2965Since 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 effe
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