The Application of Regression Diagnosis in Outlier Detection

DOI

10.2991/msie-15.2015.21How to use a DOI?

Keywords

Data mining; Regression diagnosis; outlier detection; Local weighted scatter smoothing.

Abstract

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.

Copyright

© 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/).

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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  -