The Application of Regression Diagnosis in Outlier Detection
Mingming Chen, Meng Gao, Jinglian Ma
Available Online November 2015.
- 10.2991/msie-15.2015.21How to use a DOI?
- Data mining; Regression diagnosis; outlier detection; Local weighted scatter smoothing.
As one of the most important tasks in data mining, outlier detection may get unexpected knowledge discovery. Regression diagnosis plays an important role in detecting outliers. This paper mainly introduces the basic theory of residual analysis and impact analysis in regression diagnosis, then makes regression diagnosis analysis on a group of data which related to altitude and species amount, and uses the local weighted scatterplot smoothing method to verify the rationality of the regression model, finally gets some useful instructions of regression diagnosis on the outlier detection.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Mingming Chen AU - Meng Gao AU - Jinglian Ma PY - 2015/11 DA - 2015/11 TI - The Application of Regression Diagnosis in Outlier Detection BT - Proceedings of the 2015 International Conference on Management Science and Innovative Education PB - Atlantis Press SP - 93 EP - 96 SN - 2352-5398 UR - https://doi.org/10.2991/msie-15.2015.21 DO - 10.2991/msie-15.2015.21 ID - Chen2015/11 ER -