Outlier detection based on Linear programming

	Outlier detection based on Linear programming
	Gao EY(高恩阳); Liu WJ(刘伟军); Wang TR(王天然); Deng HB(邓华波)
	2012
会议名称	2012 International Conference on Information Engineering
会议日期	June 27-28, 2012
会议地点	Singapore
关键词	Outlier detection Markov model Linear programming
页码	194-196
中文摘要	Outlier detection is an important step in many data-mining applications. In this paper, we propose an outlier detection mathod based on Linear Programming. The essential idea behind this technique is that two neighbor data points must be normal points or outliers in the same time, this is consistent with Markov property, hence we construct k-nearest neighbor graph model. As the main result of this paper, we show that Linear Programming method can detect outliers correctly, even if the data has outliers that form a small cluster, in contrast to state of the art outlier detection algorithm LOF.
产权排序	1
会议录	Lecture Notes in Information Technology
会议录出版者	Springer Verlag
会议录出版地	Heidelberg, Germany
语种	英语
ISBN号	978-1-61275-024-8
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/10151]
专题	沈阳自动化研究所_装备制造技术研究室
推荐引用方式 GB/T 7714	Gao EY,Liu WJ,Wang TR,et al. Outlier detection based on Linear programming[C]. 见:2012 International Conference on Information Engineering. Singapore. June 27-28, 2012.