Supervised classification of geometrical objects by integrating currents and functional data analysis
Impacto
Scholar |
Otros documentos de la autoría: Barahona, S.; Centella, P.; Gual-Arnau, Ximo; Ibáñez Gual, Maria Victoria; Sanchis Vidal, Amelia
Metadatos
Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7037
comunitat-uji-handle3:10234/8635
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https://doi.org/10.1007/s11749-019-00669-z |
Metadatos
Título
Supervised classification of geometrical objects by integrating currents and functional data analysisAutoría
Fecha de publicación
2019Editor
Springer VerlagISSN
1133-0686; 1863-8260Cita bibliográfica
BARAHONA, S., et al. Supervised classification of geometrical objects by integrating currents and functional data analysis. TEST, 2019, p. 1-24.Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://link.springer.com/article/10.1007/s11749-019-00669-zVersión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
This paper focuses on the application of supervised classification techniques to a set of geometrical objects (bodies) characterized by currents, in particular, discriminant analysis and some nonparametric methods. A ... [+]
This paper focuses on the application of supervised classification techniques to a set of geometrical objects (bodies) characterized by currents, in particular, discriminant analysis and some nonparametric methods. A current is a relevant mathematical object to model geometrical data, like hypersurfaces, through integration of vector fields over them. As a consequence of the choice of a vector-valued reproducing kernel Hilbert space (RKHS) as a test space to integrate over hypersurfaces, it is possible to consider that hypersurfaces are embedded in this Hilbert space. This embedding enables us to consider classification algorithms of geometrical objects. We present a method to apply supervised classification techniques in the obtained vector-valued RKHS. This method is based on the eigenfunction decomposition of the kernel. The novelty of this paper is therefore the reformulation of a size and shape supervised classification problem in functional data analysis terms using the theory of currents and vector-valued RKHSs. This approach is applied to a 3D database obtained from an anthropometric survey of the Spanish child population with a potential application to online sales of children’s wear. [-]
Publicado en
TEST, 2019, p. 1-24Proyecto de investigación
This paper has been partially supported by Projects DPI2017-87333-R and UJI-B2017-13. We would also like to thank the Biomechanics Institute of Valencia for providing us withthe data set.Derechos de acceso
© Sociedad de Estadística e Investigación Operativa 2019
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info:eu-repo/semantics/restrictedAccess
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