On robust classification using projection depth |
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Authors: | Subhajit Dutta Anil K Ghosh |
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Institution: | (1) Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, USA;(2) Biometric Research Branch, National Cancer Institute, National Institutes of Health, Rockville, MD, USA |
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Abstract: | This article uses projection depth (PD) for robust classification of multivariate data. Here we consider two types of classifiers,
namely, the maximum depth classifier and the modified depth-based classifier. The latter involves kernel density estimation,
where one needs to choose the associated scale of smoothing. We consider both the single scale and the multi-scale versions
of kernel density estimation, and investigate the large sample properties of the resulting classifiers under appropriate regularity
conditions. Some simulated and real data sets are analyzed to evaluate the finite sample performance of these classification
tools. |
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Keywords: | |
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