NDLI: Particle swarm optimization for linear support vector machines based classifier selection

Content Provider	Directory of Open Access Journals (DOAJ)
Author	Gintautas Garšva Paulius Danėnas
Abstract	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.
Related Links	http://www.journals.vu.lt/nonlinear-analysis/article/view/13690
ISSN	13925113
e-ISSN	23358963
DOI	10.15388/NA.2014.1.2
Journal	Nonlinear Analysis
Issue Number	1
Volume Number	19
Language	English
Publisher	Vilnius University Press
Publisher Date	2014-01-01
Publisher Place	Lithuania
Access Restriction	Open
Subject Keyword	Analysis Particle Swarm Optimization Linear Svm Support Vector Machines Machine Learning Classification
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Analysis

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