Fuzzy Classifier Design (Studies in Fuzziness and Soft Computing)
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This introduction to supervised pattern recognision and fuzzy set theory defines fuzzy "if-then" and "non-if-then" classifers, and looks at their properties. Training algorithms are detailed, and there is a discussion on fuzzy and non-fuzzy modles for fusion and selection. Series: Studies in Fuzziness and Soft Computing. Num Pages: 315 pages, 81 black & white tables, biography. BIC Classification: PBCH; PBWX; UN; UYQP. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 235 x 155 x 19. Weight in Grams: 1420. . 2000. 2000th Edition. Hardcover. . . . . Books ship from the US and Ireland. Bookseller Inventory # V9783790812985
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Product Description: This book about fuzzy classifier design briefly introduces the fundamentals of supervised pattern recognition and fuzzy set theory. Fuzzy if-then classifiers are defined and some theoretical properties thereof are studied. Popular training algorithms are detailed. Non if-then fuzzy classifiers include relational, k-nearest neighbor, prototype-based designs, etc. A chapter on multiple classifier combination discusses fuzzy and non-fuzzy models for fusion and selection.
Title: Fuzzy Classifier Design (Studies in ...
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