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《Journal of Anhui University of Technology and Science》 2004-02
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An algorithm of mining eefault decision rules based on variable support measure

YANG Ping~1 ,WAN Shang-hai~1, CHEN Geng~2 (1.Dept. of Math. & Phys., Anhui University of Technology and Science, Wuhu 241000, China; (2.Dept. of Comp. Sci. & Engn., Southeast University, Nanjing 210096,China)  
Rough set theory is a new mathematical tool to deal with imprecise, incomplete and inconsistent data. MDRBR algorithm improves efficiency of existing algorithms for mining default rules with support measure constraint. But MDRBR employs the uniform support measure threshold (denoted as sup) such that there exists following shortcoming: A lot of default rules are mined when the sup is very small; conversely, some important default rules that correspond to the sparse objects are filtered when the sup is high. This paper, introduces an algorithm of mining default rules based on variable support measure-MDRBVSM, which can efficiently improves the existing drawbacks of conventional algorithms for mining default rules. MDRBVSM effectively filter out noise and solves the problem of time-consuming of default rules. Experiment results show that the algorithm is practical.
【Fund】: 国家自然科学基金资助项目(70371015);; 安徽省自然科学基金资助项目(03042205);; 安徽省教育厅教学研究资助项目(2003kj029)
【CateGory Index】: TP311
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