DocumentCode
3573875
Title
Training support vector machines with particle swarms
Author
Paquet, U. ; Engelbrecht, AP
Author_Institution
Dept. of Comput. Sci., Pretoria Univ., South Africa
Volume
2
fYear
2003
Firstpage
1593
Abstract
Training a support vector machine requires solving a constrained quadratic programming problem. Linear particle swarm optimization is intuitive and simple to implement, and is presented as an alternative to current numeric SVM training methods. Performance of the new algorithm is demonstrated on the MNIST character recognition dataset.
Keywords
character recognition; pattern classification; quadratic programming; support vector machines; character recognition dataset; constrained quadratic programming problem; linear particle swarm optimization; particle swarms; support vector machine; training support vector machines; Africa; Computer science; Constraint optimization; Convergence; Kernel; Machine learning; Packaging machines; Particle swarm optimization; Quadratic programming; Support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2003. Proceedings of the International Joint Conference on
ISSN
1098-7576
Print_ISBN
0-7803-7898-9
Type
conf
DOI
10.1109/IJCNN.2003.1223937
Filename
1223937
Link To Document