Parallel distributed genetic fuzzy rule selection

Genetic fuzzy rule selection has been successfully used to design accurate and compact fuzzy rule-based classifiers. It is, however, very difficult to handle large data sets due to the increase in computational costs. This paper proposes a simple but effective idea to improve the scalability of gene...

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Veröffentlicht in:	Soft computing (Berlin, Germany) Jg. 13; H. 5; S. 511 - 519
Hauptverfasser:	Nojima, Yusuke, Ishibuchi, Hisao, Kuwajima, Isao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer-Verlag 01.03.2009 Springer Nature B.V
Schlagworte:	Algorithms Artificial Intelligence Classification Computational Intelligence Computing costs Control Costs Data mining Datasets Design Engineering Focus Fuzzy sets Genetic algorithms Mathematical Logic and Foundations Mechatronics Robotics Subgroups Fuzzy rule-based classifier Parallel distributed implementation Genetic fuzzy rule selection Data subdivision
ISSN:	1432-7643, 1433-7479
Online-Zugang:	Volltext
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