Volume 7, Issue 4, August 2014, Pages 748 - 757
Outlier Detection Based on Local Kernel Regression for Instance Selection
- Qinmu Peng, Yiu-ming Cheung
- Corresponding Author
- Qinmu Peng
Available Online 1 August 2014.
- https://doi.org/10.1080/18756891.2014.960230How to use a DOI?
- Outlier Detection, Instance Selection, Local Kernel Regression
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - JOUR AU - Qinmu Peng AU - Yiu-ming Cheung PY - 2014 DA - 2014/08 TI - Outlier Detection Based on Local Kernel Regression for Instance Selection JO - International Journal of Computational Intelligence Systems SP - 748 EP - 757 VL - 7 IS - 4 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2014.960230 DO - https://doi.org/10.1080/18756891.2014.960230 ID - Peng2014 ER -