Outlier Detection Based on Local Kernel Regression for Instance Selection

doi:10.1080/18756891.2014.960230

科研成果详情

题名	Outlier Detection Based on Local Kernel Regression for Instance Selection
作者	Peng，Qinmu 1; Cheung，Yiu ming 1,2
发表日期	2014-07-04
发表期刊	International Journal of Computational Intelligence Systems
ISSN/eISSN	1875-6891
卷号	7 期号:4 页码:748-757
摘要	Abstract: In this paper, we propose an outlier detection approach based on local kernel regression for instance selection. It evaluates the reconstruction error of instances by their neighbors to identify the outliers. Experiments are performed on the synthetic and real data sets to show the efficacy of the proposed approach in comparison with the existing counterparts.
关键词	Instance Selection Local Kernel Regression Outlier Detection
DOI	10.1080/18756891.2014.960230
URL	查看来源
语种	英语English
Scopus入藏号	2-s2.0-84925936292
引用统计
文献类型	期刊论文
条目标识符	https://repository.uic.edu.cn/handle/39GCC9TT/6510
专题	北师香港浸会大学
作者单位	1.Department of Computer Science,Hong Kong Baptist University,Hong Kong SAR,China 2.United International College,Beijing Normal University – Hong Kong Baptist University,Zhuhai,China
推荐引用方式 GB/T 7714	Peng，Qinmu,Cheung，Yiu ming. Outlier Detection Based on Local Kernel Regression for Instance Selection[J]. International Journal of Computational Intelligence Systems, 2014, 7(4): 748-757.
APA	Peng，Qinmu, & Cheung，Yiu ming. (2014). Outlier Detection Based on Local Kernel Regression for Instance Selection. International Journal of Computational Intelligence Systems, 7(4), 748-757.
MLA	Peng，Qinmu,et al."Outlier Detection Based on Local Kernel Regression for Instance Selection". International Journal of Computational Intelligence Systems 7.4(2014): 748-757.