Fuzzy pattern recognition by fuzzy integrals and fuzzy rules

Michel Grabisch 1
1 SYSDEF - Systèmes d'aide à la décision et à la formation
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : We give an overview of the application of fuzzy rules and fuzzy integrals in classification, presenting the general methodology and illustrating it by giving real applications. Fuzzy rules have been most of the time devoted to fuzzy control, using the so-called “Mamdani rules”. Here we present a broader view of the topic in the framework of possibility theory. It is seen that uncertainty rules are the best-suited ones for modeling human knowledge in pattern recognition. On the other hand, fuzzy integrals, by assigning weights to groups of attributes, permit to define non linear classifiers, with powerful performances.
Type de document :
Chapitre d'ouvrage
Pattern Recognition - From Classical to Modern Approaches, World Scientific, pp.257-280, 2001, 〈10.1142/9789812386533_0009〉
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https://hal.archives-ouvertes.fr/hal-01561702
Contributeur : Lip6 Publications <>
Soumis le : jeudi 13 juillet 2017 - 11:22:48
Dernière modification le : mardi 11 décembre 2018 - 01:22:23

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Michel Grabisch. Fuzzy pattern recognition by fuzzy integrals and fuzzy rules. Pattern Recognition - From Classical to Modern Approaches, World Scientific, pp.257-280, 2001, 〈10.1142/9789812386533_0009〉. 〈hal-01561702〉

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