Abstract
Notions of data depth have motivated nonparametric multivariate analysis, especially in supervised learning. Maximum depth classifiers, classifiers based on depth-depth plots and depth distribution classifiers are nonparametric classification methodologies based on the notions of data depth and are Bayes-optimal rule under certain conditions. This paper proposes rank-rank plot for classification. Theoretical properties of the suggested classifier are investigated in some particular cases given by specific distributional assumptions. The performance of the proposed classification method is further investigated using simulated datasets.
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This work was partially supported by the grant of The Ministry of Education, Youth and Sports CZ.02.1.01/0.0/0.0/17_049/0008408.
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Vencalek, O., Makinde, O.S. RR-classifier: a nonparametric classification procedure in multidimensional space based on relative ranks. AStA Adv Stat Anal 105, 675–693 (2021). https://doi.org/10.1007/s10182-021-00423-7
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DOI: https://doi.org/10.1007/s10182-021-00423-7