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Archetypoids: A new approach to define representative archetypal data

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Archetypoids: A new approach to define representative archetypal data

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dc.contributor.author Vinue, G. es_ES
dc.contributor.author Epifanio, I. es_ES
dc.contributor.author Alemany Mut, Mª Sandra es_ES
dc.date.accessioned 2016-09-28T06:39:44Z
dc.date.available 2016-09-28T06:39:44Z
dc.date.issued 2015
dc.identifier.issn 0167-9473
dc.identifier.uri http://hdl.handle.net/10251/70519
dc.description.abstract [EN] The new concept archetypoids is introduced. Archetypoid analysis represents each observation in a dataset as a mixture of actual observations in the dataset, which are pure type or archetypoids. Unlike archetype analysis, archetypoids are real observations, not a mixture of observations. This is relevant when existing archetypal observations are needed, rather than fictitious ones. An algorithm is proposed to find them and some of their theoretical properties are introduced. It is also shown how they can be obtained when only dissimilarities between observations are known (features are unavailable). Archetypoid analysis is illustrated in two design problems and several examples, comparing them with the archetypes, the nearest observations to them and other unsupervised methods. es_ES
dc.description.sponsorship The authors would like to thank Juan Domingo from the University of Valencia for providing the binary images of women’s trunks. They would also like to thank the Biomechanics Institute of Valencia for providing them with the dataset and the Spanish Ministry of Health and Consumer Affairs for having promoted and coordinated the ‘‘Anthropometric Study of the Female Population in Spain’’. The authors are also grateful to the Associate Editor and two reviewers for their very constructive suggestions, which have led to improvements in the manuscript. This work has been partially supported by Grant DPI2013-47279-C2-1-R.
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation MICINN/DPI2013-47279-C2-1-R es_ES
dc.relation.ispartof Computational Statistics and Data Analysis es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Archetype es_ES
dc.subject Convex hull es_ES
dc.subject Unsupervised learning es_ES
dc.subject Extremal point es_ES
dc.subject Non-negative matrix factorization es_ES
dc.title Archetypoids: A new approach to define representative archetypal data es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.csda.2015.01.018
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario Mixto de Biomecánica de Valencia - Institut Universitari Mixt de Biomecànica de València es_ES
dc.description.bibliographicCitation Vinue, G.; Epifanio, I.; Alemany Mut, MS. (2015). Archetypoids: A new approach to define representative archetypal data. Computational Statistics and Data Analysis. 87:102-115. doi:10.1016/j.csda.2015.01.018 es_ES
dc.description.accrualMethod Senia es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.csda.2015.01.018 es_ES
dc.description.upvformatpinicio 102 es_ES
dc.description.upvformatpfin 115 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 87 es_ES
dc.relation.senia 305950 es_ES
dc.contributor.funder Ministerio de Ciencia e Innovación


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