Tuning pattern classifier parameters using a genetic algorithm with an application in mobile robotics

Wang, J. X. and Downs, T. (2003). Tuning pattern classifier parameters using a genetic algorithm with an application in mobile robotics. In: R. Sarker, R. Reynolds and H. Abbass, The 2003 Congress on Evolutionary Computation: CEC 2003. The 2003 Congress on Evolutionary Computation (CEC '03), Canberra, Australia, (581-586). 8-12 December 2003. doi:10.1109/CEC.2003.1299628


Author Wang, J. X.
Downs, T.
Title of paper Tuning pattern classifier parameters using a genetic algorithm with an application in mobile robotics
Conference name The 2003 Congress on Evolutionary Computation (CEC '03)
Conference location Canberra, Australia
Conference dates 8-12 December 2003
Proceedings title The 2003 Congress on Evolutionary Computation: CEC 2003
Journal name Cec: 2003 Congress On Evolutionary Computation, Vols 1-4, Proceedings
Place of Publication Piscataway, NJ, U.S.A.
Publisher The Institute of Electrical and Electronics Engineers
Publication Year 2003
Sub-type Fully published paper
DOI 10.1109/CEC.2003.1299628
ISBN 0-7803-7805-9
Editor R. Sarker
R. Reynolds
H. Abbass
Volume 1
Start page 581
End page 586
Total pages 6
Collection year 2003
Language eng
Abstract/Summary Support vector machines (SVMs) have recently emerged as a powerful technique for solving problems in pattern classification and regression. Best performance is obtained from the SVM its parameters have their values optimally set. In practice, good parameter settings are usually obtained by a lengthy process of trial and error. This paper describes the use of genetic algorithm to evolve these parameter settings for an application in mobile robotics.
Subjects E1
Keyword Genetic algorithms
Mobile robots
Pattern classification
Support vector machines
Q-Index Code E1

 
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Created: Fri, 24 Aug 2007, 12:01:39 EST