| 基于反向K近邻的孤立点检测算法 |
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| 引用本文： | 岳峰,邱保志.基于反向K近邻的孤立点检测算法[J].计算机工程与应用,2007,43(7):182-184. |
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| 作者姓名： | 岳峰 邱保志 |
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| 作者单位： | 郑州大学信息工程学院 郑州大学信息工程学院 |
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| 摘 要： | 提出了基于反向K近邻（RKNN）的孤立点检测算法ODRKNN。ODRKNN算法用每个数据点的反向k近邻个数来衡量该数据点的偏离程度，在综合数据集和真实数据集上的实验结果表明，该算法能有效地检测出孤立点，且算法的效率高于算法LOF和LSC的效率.
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| 关 键 词： | 孤立点 K近邻 反向K近邻 |
| 文章编号： | 1002-8331（2007）07-0182-03 |
| 收稿时间： | 2006-04-03 |
| 修稿时间： | 2006-07 |
Outlier detection algorithm based on Reverse K Nearest Neighbors |
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| YUE Feng,QIU Bao-zhi.Outlier detection algorithm based on Reverse K Nearest Neighbors[J].Computer Engineering and Applications,2007,43(7):182-184. |
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| Authors: | YUE Feng QIU Bao-zhi |
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| Affiliation: | YUE Feng,QIU Bao-zhi( School of Information ＆ Engineering,Zhengzhou University,Zhengzhou 450052,China) |
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| Abstract: | This paper proposes a new outlier detection algorithm ODRKNN based on reverse K nearest neighbors.ODRKNN counts the number of each point's reverse K nearest neighbors to reflect its isolation degree,experimental results on synthesized and real world dataset show that ODRKNN can efficiently detect outliers and has higher efficiency than outliers detection algorithm LOF and LSC. |
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| Keywords: | outliers K Nearest Neighbors Reverse K Nearest Neighbors(RKNN) |
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