Proceedings of the Korean Operations and Management Science Society Conference (한국경영과학회:학술대회논문집)
- 2006.05a
- /
- Pages.1214-1220
- /
- 2006
Using Artificial Neural Networks to detect Variance Change Point for Data Separation
- Han Young-Chul (Department of Information and Industrial Engineering, Yonsei University) ;
-
Oh Kyong-Joo
(Department of Information and Industrial Engineering, Yonsei University)
;
- Kim Tae-Yoon (Department of Statistics, Keimyung University)
- Published : 2006.05.01
Abstract
In this article, it will be shown that a nonparametric and data-adaptive approach to the variance change point (VCP) detection problem is possible by formulating it as a pattern classification problem. Technical aspects of the VCP detector are discussed, which include its training strategy and selection of proper classification tool.
Keywords
- Variance change point detection;
- Nonparametric and data-adaptive method;
- Pattern Classification;
- Artificial neural networks;
- Discriminant analysis