RT Journal Article
T1 The DDG-classifier in the functional setting
A1 Cuesta Albertos, Juan A.
A1 Febrero Bande, Manuel
A1 Oviedo de la Fuente, Manuel
K1 DD-classifier
K1 Functional depths
K1 Functional data analysis
AB The maximum depth classifier was the first attempt to use data depths instead of multivariate raw data in classification problems. Recently, the DD-classifier has addressed some of the serious limitations of this classifier but issues still remain. This paper aims to extend the DD-classifier as follows: first, by enabling it to handle more than two groups; second, by applying regular classification methods (such as kNN, linear or quadratic classifiers, recursive partitioning, etc) to DD-plots, which is particularly useful, because it gives insights based on the diagnostics of these methods; and third, by integrating various sources of information (data depths, multivariate functional data, etc) in the classification procedure in a unified way. This paper also proposes an enhanced revision of several functional data depths and it provides a simulation study and applications to some real data sets
PB Springer
SN 1133-0686
YR 2017
FD 2017
LK http://hdl.handle.net/10347/18647
UL http://hdl.handle.net/10347/18647
LA eng
NO Cuesta-Albertos, J.A., Febrero-Bande, M. & Oviedo de la Fuente, M. TEST (2017) 26: 119. https://doi.org/10.1007/s11749-016-0502-6
NO This is a post-peer-review, pre-copyedit version of an article published in TEST. The final authenticated version is available online at: https://doi.org/10.1007/s11749-016-0502-6
NO This research was partially supported by the Spanish Ministerio de Ciencia y Tecnología, Grants MTM2011-28657-C02-02, MTM2014-56235-C2-2-P (J.A. Cuesta–Albertos) and MTM2013-41383-P (M. Febrero–Bande and M. Oviedo de la Fuente)
DS Minerva
RD 30 abr 2026