DocumentCode
2230148
Title
Two-Step Particle Swarm Optimization to Solve the Feature Selection Problem
Author
Bello, Rafael ; Gomez, Yudel ; Nowe, Ann ; García, María M.
Author_Institution
Univ. Central de Las Villas, Las Villas
fYear
2007
fDate
20-24 Oct. 2007
Firstpage
691
Lastpage
696
Abstract
In this paper we propose a new model of particle swarm optimization called two-step PSO. The basic idea is to split the heuristic search performed by particles into two stages. We have studied the performance of this new algorithm for the feature selection problem by using the reduct concept of the rough set theory. Experimental results obtained show that the two-step approach improves over the PSO model in calculating reducts, with the same computational cost.
Keywords
particle swarm optimisation; rough set theory; feature selection problem; heuristic search; particle swarm optimization; rough set theory; two-step PSO; Ant colony optimization; Application software; Biological system modeling; Computational efficiency; Computational intelligence; Computer science; Intelligent systems; Machine learning; Particle swarm optimization; Set theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems Design and Applications, 2007. ISDA 2007. Seventh International Conference on
Conference_Location
Rio de Janeiro
Print_ISBN
978-0-7695-2976-9
Type
conf
DOI
10.1109/ISDA.2007.101
Filename
4389688
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