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TEST

, Volume 26, Issue 1, pp 119–142 | Cite as

The \(\hbox {DD}^G\)-classifier in the functional setting

  • J. A. Cuesta-Albertos
  • M. Febrero-Bande
  • M. Oviedo de la FuenteEmail author
Original Paper

Abstract

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.

Keywords

DD-classifier Functional depths Functional data analysis 

Mathematics Subject Classification

62-09 62G99 62H30 

Notes

Acknowledgments

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).

Supplementary material

11749_2016_502_MOESM1_ESM.rar (4.1 mb)
Supplementary material 1 (rar 4166 KB)

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Copyright information

© Sociedad de Estadística e Investigación Operativa 2016

Authors and Affiliations

  1. 1.Department of Mathematics, Statistics and ComputationUniversity of CantabriaSantanderSpain
  2. 2.Department of Statistics and Operations ResearchUniversity of Santiago de CompostelaSantiago de CompostelaSpain

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