| Title |
Particle swarm optimization for linear support vector machines based classifier selection / |
| Authors |
Garšva, Gintautas ; Danėnas, Paulius |
| DOI |
10.15388/NA.2014.1.2 |
| Full Text |
|
| Is Part of |
Nonlinear analysis: modelling and control.. Vilnius : Vilniaus universiteto leidykla. 2014, vol. 19, no. 1, p. 26-42.. ISSN 1392-5113. eISSN 2335-8963 |
| Keywords [eng] |
particle swarm optimization ; linear SVM ; support vector machines ; machine learning ; classification |
| Abstract [eng] |
Particle swarm optimization is a metaheuristic technique widely applied to solve various optimization problems as well as parameter selection problems for various classification techniques. This paper presents an approach for linear support vector machines classifier optimization combining its selection from a family of similar classifiers with parameter optimization. Experimental results indicate that proposed heuristics can help obtain competitive or even better results compared to similar techniques and approaches and can be used as a solver for various classification tasks. |
| Published |
Vilnius : Vilniaus universiteto leidykla |
| Type |
Journal article |
| Language |
English |
| Publication date |
2014 |
| CC license |
|
