Evaluating technologies based rough set theory

V. Nguyen, Nguyen Thi Ly Sa
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Abstract

Most data mining algorithms usually generate combining large rules, finding useful rules from rules set necessary and important. There have been several techniques proposed to assess the rule as useful measure which is based on rough set theory as the RIM, ERIM measure. On rough set theory has been studied, the article proposed AWERIM measure which is improved from ERIM measure and applied this specific measure to an application of the data mining problem about bank loans.
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基于粗糙集理论的评价技术
大多数数据挖掘算法通常生成组合大规则,从规则集中发现有用的规则是必要和重要的。已经提出了几种基于粗糙集理论的评估规则作为有用度量的技术,如RIM, ERIM度量。本文在研究粗糙集理论的基础上,提出了由ERIM测度改进而来的AWERIM测度,并将该测度具体应用于银行贷款数据挖掘问题。
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