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孤立点检测是数据挖掘领域的一个重要分支.随着人们对数据质量、欺诈检测、网络入侵、故障诊断等问题的关注,孤立点检测在信息科学研究领域受到越来越多学者的重视.该文简单介绍了现代孤立点检测发展的现状并在传统孤立点检测算法分析的基础上,提出了一种新的基于粗糙集的孤立点检测算法.对该算法的理论基础、算法设计进行了详细的分析,从理论和实验两个方面对其进行评估,充分证明了粗糙集在孤立点检测中的有效性.“,”Outlier detection is one important part of data mining.The problem of outlier mining attracts more and more interests in research of information science when the research fields of data quality,fraud detection,intrusion detection ,fault diagnosis and so on receive wide attentions .In this paper,it introduce the status quo of outlier detection briefly,based on the analysis of the traditional outlier data detection algorithms, it proposed a new outlier detection algorithms using rough set theory. It analyzed the theoretical foundation of algorithm and design of algorithm detailedly. From the aspect of theory and experiment, it verified the usefulness of rough set theory in outlier data detection.