Title :
Training support vector machines with particle swarms
Author :
Paquet, U. ; Engelbrecht, AP
Author_Institution :
Dept. of Comput. Sci., Pretoria Univ., South Africa
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;
Conference_Titel :
Neural Networks, 2003. Proceedings of the International Joint Conference on
Print_ISBN :
0-7803-7898-9
DOI :
10.1109/IJCNN.2003.1223937
