Data-driven fuzzy sets for classification
作者： Sofia Visa , Anca Ralescu
DOI: 10.1504/IJAIP.2008.020817
关键词: Machine learning 、 Type-2 fuzzy sets and systems 、 Artificial intelligence 、 Fuzzy measure theory 、 Defuzzification 、 Computer science 、 Pattern recognition 、 Membership function 、 Fuzzy number 、 Fuzzy set 、 Fuzzy classification 、 Fuzzy set operations
摘要: Using the mass assignment mechanism, a fuzzy classifier can be derived directly from class relative frequency distribution. Moreover, in this framework, family of sets represent class, thus adapting to need classification. Graduality and corresponding concept error used guide process deriving representing sets. The classification algorithm is attractive due its low complexity. Successful applications include imbalanced data problems where having fewer examples interest.
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