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- W1596272016 abstract "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." @default.
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- W1596272016 date "2015-05-01" @default.
- W1596272016 modified "2023-09-24" @default.
- W1596272016 title "A GA-based approach for mining membership functions and concept-drift patterns" @default.
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- W1596272016 doi "https://doi.org/10.1109/cec.2015.7257257" @default.
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