Outlier detection based on Linear programming
文献类型：会议论文
| 作者 | Gao EY(高恩阳); Liu WJ(刘伟军) ; Wang TR(王天然); Deng HB(邓华波)
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| 出版日期 | 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 |
| 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. |
入库方式： OAI收割
来源：沈阳自动化研究所
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