Evolutionary design of a fuzzy classifier from data

  title={Evolutionary design of a fuzzy classifier from data},
  author={Xiaoguang Chang and John H. Lilly},
  journal={IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)},
Genetic algorithms show powerful capabilities for automatically designing fuzzy systems from data, but many proposed methods must be subjected to some minimal structure assumptions, such as rule base size. In this paper, we also address the design of fuzzy systems from data. A new evolutionary approach is proposed for deriving a compact fuzzy classification system directly from data without any a priori knowledge or assumptions on the distribution of the data. At the beginning of the algorithm… CONTINUE READING
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