Journal
APPLIED SOFT COMPUTING
Volume 12, Issue 2, Pages 819-825Publisher
ELSEVIER
DOI: 10.1016/j.asoc.2011.10.008
Keywords
Classification; Prototype classifier; Swarm intelligence; Gravitational search algorithm; UCI machine learning repository
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In recent years, heuristic algorithms have been successfully applied to solve clustering and classification problems. In this paper, gravitational search algorithm (GSA) which is one of the newest swarm based heuristic algorithms is used to provide a prototype classifier to face the classification of instances in multi-class data sets. The proposed method employs GSA as a global searcher to find the best positions of the representatives (prototypes). The proposed GSA-based classifier is used for data classification of some of the well-known benchmark sets. Its performance is compared with the artificial bee colony (ABC), the particle swarm optimization (PSO), and nine other classifiers from the literature. The experimental results of twelve data sets from UCI machine learning repository confirm that the GSA can successfully be applied as a classifier to classification problems. (C) 2011 Elsevier B. V. All rights reserved.
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