Genetic algorithm based framework for mining fuzzy association rules

It is not an easy task to know a priori the most appropriate fuzzy sets that cover the domains of quantitative attributes for fuzzy association rules mining, simply because characteristics of quantitative data are in general unknown. Besides, it is unrealistic that the most appropriate fuzzy sets ca...

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Vydáno v:	Fuzzy sets and systems Ročník 152; číslo 3; s. 587 - 601
Hlavní autoři:	Kaya, M., Alhajj, R.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Amsterdam Elsevier B.V 16.06.2005 Elsevier
Témata:	Algorithmics. Computability. Computer arithmetics Applied sciences Association rules Computer science; control theory; systems CURE clustering algorithm Data mining Exact sciences and technology Fuzzy sets Genetic algorithms Mathematical logic, foundations, set theory Mathematics Multivariate analysis Probability and statistics Quantitative attributes Sciences and techniques of general use Set theory Statistics Theoretical computing CURE clustering algorithm Fuzzy sets Quantitative attributes Data mining Association rules Genetic algorithms Membership function Generating function Cluster analysis (statistics) Association rule Fuzzy set Census Genetic algorithm
ISSN:	0165-0114, 1872-6801
On-line přístup:	Získat plný text
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