COR Methodology: A Simple Way to Obtain Linguistic Fuzzy Models with Good Interpretability and Accuracy
نویسندگان
چکیده
The chapter introduces a simple learning methodology, the cooperative rules (COR) one, that improves the accuracy of linguistic fuzzy models preserving the highest interpretability. Its operation mode involves a combinatorial search of fuzzy rules performed over a set of previously generated candidate ones. The accuracy is achieved by developing a smart search space reduction and by inducing the generation of a linguistic fuzzy rule set with good cooperation. COR also ensures a good interpretability by keeping the membership functions and the model structure unaltered, as well as generating a compact rule base.
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