DocumentCode :
2851247
Title :
Fuzzy Feature Subset Selection Using the Wang & Mendel Method
Author :
Cintra, Marcos Evandro ; de Arruda, C.H. ; Monard, Maria Carolina
Author_Institution :
Math. & Comput. Sci. Inst., Sao Paulo Univ., Sao Paulo
fYear :
2008
fDate :
10-12 Sept. 2008
Firstpage :
590
Lastpage :
595
Abstract :
The dimension of a knowledge domain can impact the use of genetic algorithms to automatically design fuzzy rule bases, since the search space for the genetic algorithm increases exponentially with the number of features. Filters are a possible approach to reduce the number of features. However, the filter approach does not take into consideration the particular aspects of fuzzy logic when selecting or ranking features. This work presents a method for feature subset selection using the Wang & Mendel method as the base for a wrapper. Experimental results are presented and discussed.
Keywords :
feature extraction; fuzzy logic; fuzzy set theory; genetic algorithms; Wang & Mendel method; fuzzy feature subset selection; fuzzy logic; fuzzy rule; genetic algorithms; wrapper; Computer science; Control systems; Filters; Frequency selective surfaces; Fuzzy logic; Fuzzy sets; Fuzzy systems; Genetic algorithms; Mathematics; Process control; Feature Subset Selection; Fuzzy Logic; Machine Learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Hybrid Intelligent Systems, 2008. HIS '08. Eighth International Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-0-7695-3326-1
Electronic_ISBN :
978-0-7695-3326-1
Type :
conf
DOI :
10.1109/HIS.2008.62
Filename :
4626694
Link To Document :
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