文章基本信息

标题：Data Missing Solution Using Rough Set Theory and Swarm Intelligence
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作者：Ahmed Tariq Sadiq ; Mehdi Gzar Duaimi ; Samir Adil Shaker 等
期刊名称：International Journal of Advanced Computer Science and Information Technology
电子版ISSN：2296-1739
出版年度：2013
卷号：2
期号：3
页码：16
语种：English
出版社：Helvetic Editions
摘要：This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estimation through working with rough set theory. The results obtained from most code sets show that bees algorithm better than ID3 in decreasing the number of extracted rules without affecting the accuracy and increasing the accuracy ratio of null values estimation, especially when the number of null values is increasing.