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Erschienen in:
2010 | OriginalPaper | Buchkapitel
The Evolution of Fuzzy Classifier for Data Mining with Applications
verfasst von : Václav Snášel, Pavel Krömer, Jan Platoš, Ajith Abraham
Erschienen in: Simulated Evolution and Learning
Verlag: Springer Berlin Heidelberg
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Fuzzy classifiers and fuzzy rules can be informally defined as tools that use fuzzy sets or fuzzy logic for their operations. In this paper, we use genetic programming to evolve a fuzzy classifier in the form of a fuzzy search expression to predict product quality. We interpret the data mining task as a fuzzy information retrieval problem and we apply a successful information retrieval method for search query optimization to the fuzzy classifier evolution. We demonstrate the ability of the genetic programming to evolve useful fuzzy classifiers on two use cases in which we detect faulty products of a product processing plant and discover intrusions in a computer network.