文章基本信息

标题：A Novel Rough Set Reduct Algorithm for Medical Domain Based on Bee Colony Optimization
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作者：N. Suguna ; K. Thanushkodi
期刊名称：Journal of Computing
电子版ISSN：2151-9617
出版年度：2010
卷号：2
期号：6
出版社：Journal of Computing
摘要：Feature selection refers to the problem of selecting relevant features which produce the most predictive outcome. In particular, feature selection task is involved in datasets containing huge number of features. Rough set theory has been one of the most successful methods used for feature selection. However, this method is still not able to find optimal subsets. This paper proposes a new feature selection method based on Rough set theory hybrid with Bee Colony Optimization (BCO) in an attempt to combat this. This proposed work is applied in the medical domain to find the minimal reducts and experimentally compared with the Quick Reduct, Entropy Based Reduct, and other hybrid Rough Set methods such as Genetic Algorithm (GA), Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO).