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- W2188032156 abstract "A fuzzy neural networkwith memory connections for classication, and weight connections for selection is introduced, thereby solving simultaneously two major problems in pattern recognition: pattern classication and feature selection. The proposed networkattempts to select important features from among the originally given plausible features, while maintaining the maximum recognition rate. The resulting value of weight connection represents the degree of importance of feature. Moreover, the knowledge acquired by the network can be described as a set of interpretable rules. The e8ectiveness of this new method has been validated by using Anderson’s IRIS data. The results are: rst, the use of two features selected by our method from among the original four in the proposed networkresults in virtually identical classier performance; and second, the constructed classier is described by three simple rules that are of if–then form. c � 2002 Elsevier Science B.V. All rights reserved." @default.
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- W2188032156 date "2002-01-01" @default.
- W2188032156 modified "2023-10-17" @default.
- W2188032156 title "A fuzzy neural networkfor pattern classication and feature selection" @default.
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