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

被引：1
|
作者：
Wang, JX [1 ]
Downs, T [1 ]
机构：
[1] Univ Queensland, Sch Informat Technol & Elect Engn, St Lucia, Qld 4072, Australia
来源：
CEC: 2003 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-4, PROCEEDINGS | 2003年
关键词：
D O I：
10.1109/CEC.2003.1299628
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
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.
引用
收藏
页码：581 / 586
页数：6
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