Robustness of resampling-based error rate estimators in two class discrimination under non-normal population Online publication date: Sun, 26-Dec-2010
by Kozo Yamada, Hirohito Sakurai, Hideyuki Imai, Yoshiharu Sato
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 3, No. 1, 2011
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.
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