摘要
Rough集方法是一种处理不确定或模糊知识的重要工具。本文对基于Rough集理论中的差异矩阵进行了研究。在引入扩充差异矩阵的基础上,提出了一种基于Rough集理论的不完备数据分析方法ROUSTIDA。该方法充分利用Rough集分析方法的优点,只需利用信息系统提供的信息,不需要另外附加信息,计算简单、直观。实验表明,该方法能充分利用信息系统中数据所反映的规律性,能有效地对不完备信息系统进行完整化分析。
The Rough set approach is an important tool to deal with uncertain or vague knowledge in AI applications. In this paper, the Rough set theory is deeply researched, a concept of extended discernibility matrix is introduced, and an algorithm ROUSTIDA for analysis with incomplete data based on Rough set theory is proposed. The advantage of this algorithm is that it uses only the information given by the operationalised data, and does not rely on other model assumptions. Experimental result shows this algorithm is efficient, comprehensible and suitable for a pre-processing step before a data-mining method is employed.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2003年第2期158-163,共6页
Pattern Recognition and Artificial Intelligence
基金
重庆市科技计划资助项目(No.2001-6878)
