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Genetic-fuzzy mining (GFM) was proposed to train fuzzy membership functions, thus enhancing the final solution quality. However, it is quite time-consuming because of frequent database scans for fitness evaluation. In this paper, we propose a parallel algorithm with MapReduce architecture to further speed up the genetic-fuzzy mining process. In the proposed approach, the master processor randomly...
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