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A framework for designing a fuzzy rule-based classifier
Kaunas University of Technology. (Department Electrical & Control Instrumentation)
Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).ORCID-id: 0000-0003-2185-8973
Kaunas University of Technology. (Department Electrical & Control Instrumentation)
Kaunas University of Technology. (Department Electrical & Control Instrumentation)
2009 (engelsk)Inngår i: Algorithmic Decision Theory: Proceedings of the 1st International Conference, ADT 2009, Venice, Italy, October 2009 / [ed] Francesca Rossi, Alexis Tsoukias, Berlin: Springer Berlin/Heidelberg, 2009, s. 434-445Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

This paper is concerned with a general framework for designing afuzzy rule-based classifier. Structure and parameters of theclassifier are evolved through a two-stage genetic search. Theclassifier structure is constrained by a tree created using theevolving SOM tree algorithm. Salient input variables are specificfor each fuzzy rule and are found during the genetic search process.It is shown through computer simulations of four real world problemsthat a large number of rules and input variables can be eliminatedfrom the model without deteriorating the classification accuracy.

sted, utgiver, år, opplag, sider
Berlin: Springer Berlin/Heidelberg, 2009. s. 434-445
Serie
Lecture Notes in Computer Science, ISSN 0302-9743 ; 5783
Emneord [en]
Classifier, Fuzzy rule, Genetic algorithm, Knowledge extraction, Variable selection
HSV kategori
Identifikatorer
URN: urn:nbn:se:hh:diva-110DOI: 10.1007/978-3-642-04428-1_38ISI: 000273344300038Scopus ID: 2-s2.0-71549144115ISBN: 3642044271 ISBN: 9783642044274 OAI: oai:DiVA.org:hh-110DiVA, id: diva2:236181
Konferanse
ADT2009, 1st International Conference on Algorithmic Decision Theory, Venice, Italy, October 2009
Tilgjengelig fra: 2009-09-21 Laget: 2009-09-21 Sist oppdatert: 2018-01-13bibliografisk kontrollert

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