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Fuzzy Classifier Design /

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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 inclu...

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Bibliographic Details
Main Author: Kuncheva, Ludmila I.
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Heidelberg : Physica-Verlag HD : Imprint : Physica, 2000.
Series:Studies in fuzziness and soft computing ; 49.
Subjects:
Computer science.
Artificial intelligence.
Optical pattern recognition.
Management information systems.
Electronic books.
Online Access:Connect to the full text of this electronic book
Description
Summary: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.
Item Description:Electronic resource.
Physical Description:1 online resource (x, 315 pages)
ISBN:9783790818505 (electronic bk.)
379081850X (electronic bk.)
ISSN:1434-9922 ;