Extracting fuzzy classi cation rules with gene expression programming
نویسنده
چکیده
In essence, data mining consists of extracting knowledge from data. This paper proposes an evolutionary system for discovering fuzzy classi cation rules. Fuzzy logic is useful for data mining especially in the case for performing classi cation task. Three methods were used to extract fuzzy classi cation rules using Evolutionary Algorithms: (1) genetic selection small number of large number of fuzzy candidate rules, (2) genetic reduction of genetic space, selection fuzzy rules from large the candidate rules, (3) genetic learning of fuzzy classi cation rules. In this paper, we propose a new gene expression programming (GEP) algorithm for discovering logical fuzzy classi cation rules, the proposed method has been tested and the results are comparable with other techniques include Genetic Programming (GP).
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