Robust classification for skewed data

Authors:
Mia Hubert;Stephan Van Der Veeken
Affiliations:
Department of Mathematics, LStat, Katholieke Universiteit Leuven, Heverlee, Belgium 3001;Department of Mathematics, LStat, Katholieke Universiteit Leuven, Heverlee, Belgium 3001
Venue:
Advances in Data Analysis and Classification
Year:
2010

Citing 6
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Abstract

In this paper we propose a robust classification rule for skewed unimodal distributions. For low dimensional data, the classifier is based on minimizing the adjusted outlyingness to each group. In the case of high dimensional data, the robustified SIMCA method is adjusted for skewness. The robustness of the methods is investigated through different simulations and by applying it to some datasets.