@inproceedings{45ec09a1f37f426aaad5e1bd0994da71,
title = "Sample outlier detection based on local kernel regression",
abstract = "Outlier often degrades the classification and cluster accuracy. In this paper, we present 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 both on the synthetic and real-life data sets to show the efficacy of the proposed approach in comparison with the existing counterparts.",
keywords = "instance selection, local kernel regression, outlier detection",
author = "Qinmu Peng and CHEUNG, {Yiu Ming}",
note = "Copyright: Copyright 2013 Elsevier B.V., All rights reserved.; 2012 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2012 ; Conference date: 04-12-2012 Through 07-12-2012",
year = "2012",
doi = "10.1109/WI-IAT.2012.260",
language = "English",
isbn = "9780769548807",
series = "Proceedings - 2012 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2012",
pages = "664--668",
booktitle = "Proceedings - 2012 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2012",
}