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  • Authors: Demetrovics Janos, Nguyen Thi Lan Huong, Vu Duc Thi, Nguyen Long Giang (2015)

  • Feature selection is a vital problem need to be effectively solved in knowledge discovery in databases and pattern recognition because of two basic reasons: to minimize cost and to accurately classify data. Feature selection using rough set theory also is called attribute reduction have attracted much attention from researchers and numerous potential results are gained. However, most of them are applied on static data and attribute reduction in dynamic databases is still in the early stage. This paper focus on developing incremental methods and algorithms to derive reducts employing a distance measure when decision systems vary in condition attribute set. We as well conduct experiments on UCI data sets and the experimental results show that the proposed algorithms are better in term...