Robustness of resampling-based error rate estimators in two class discrimination under non-normal population. (27th December 2010)

• Record Type: Journal Article
• Authors: Yamada, Kozo; Sakurai, Hirohito; Imai, Hideyuki; Sato, Yoshiharu
• Is Part Of: International journal of reasoning-based intelligent systems. Volume 3:Number 1(2011)
• Page Start: 14
• Page End: 27
• Publication Date: 2010-12-27
• Subjects: error rate estimators -- robustness -- resampling-based estimators -- non-normality -- kurtosis -- linear discriminant function; Artificial intelligence -- Periodicals; Reasoning -- Periodicals; 006.3
• Languages: English
• ISSNs: 1755-0556

Abstract

This paper numerically investigates robustness of resampling-based error rate estimators to kurtosis when Fisher's linear discriminant function is used. In order to control the population kurtosis and to examine the robustness of estimators, we assume Pearson's type VII and exponential power distributions as a population distribution. The robustness study is carried out for several resampling-based estimators based on graphical and quantitative approaches.