DocumentCode
1738137
Title
Optimizing fuzzy classifiers by evolutionary algorithms
Author
Grauel, Adolf ; Renners, Ingo ; Ludwig, Lars A.
Author_Institution
Dept. of Math., Paderborn Univ., Germany
Volume
1
fYear
2000
fDate
2000
Firstpage
353
Abstract
In this paper a methodology for optimizing fuzzy classifiers based on B-splines by evolutionary algorithms is presented. The algorithm proposed maximizes the performance and minimizes the size of the classifier. On a well-known classification problem the algorithm using only part of the features has a recognition rate comparable to an LDA on the total feature space
Keywords
evolutionary computation; fuzzy logic; pattern classification; B-splines; evolutionary algorithms; fuzzy classifiers; fuzzy logic; intelligent data analysis; rule induction; Data analysis; Data mining; Decision making; Evolutionary computation; Fuzzy sets; Fuzzy systems; Mathematics; Minimization methods; Optimization methods; Spline;
fLanguage
English
Publisher
ieee
Conference_Titel
Knowledge-Based Intelligent Engineering Systems and Allied Technologies, 2000. Proceedings. Fourth International Conference on
Conference_Location
Brighton
Print_ISBN
0-7803-6400-7
Type
conf
DOI
10.1109/KES.2000.885829
Filename
885829
Link To Document