Depth-based Classification for Multivariate Data

• Main Author: Ondřej Vencálek
• Format: Article
• Language: English
• Published: Austrian Statistical Society 2017-04-01
• Series: Austrian Journal of Statistics
• Online Access: http://www.ajs.or.at/index.php/ajs/article/view/677

Concept of data depth provides one possible approach to the analysis of multivariate data. Among other it can be also used for classification purposes. The present paper is an overview of the research in the field of depth-based classification for multivariate data. It provides a short summary of current state of knowledge in the field of depth-based classification followed by detailed discussion of four main directions in the depth-based classification, namely semiparametric depth-based classifiers, maximal depth classifier, (maximal depth) classifiers which use local depth functions and finally advanced depth-based classifiers. We do not restrict our attention only on proposed classifiers. The paper rather aims to overview the ideas connected with depth-based classification and problems that were discussed in this context.