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“A Fuzzy Classifier That Uses Both Crisp Samples and Linguistic Knowledge”
by Wen Wei and Jerry M. Mendel
June 1994
In this paper we develop a general structure of a fuzzy logic (FL) classifier that is capable of using both numerical data and linguistic information. By using fuzzy inference, we are able to handle numerical data and linguistic information in a unified framework. We show that the FL classifier includes the Bayes classifier as a special case. Our experimental results show that the FL classifier, when using linguistic information, can perform better than probabilistic classifiers that do not use linguistic information.