Child t-shirt size data set from 3D body scanner anthropometric measurements and a questionnaire
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Título
Child t-shirt size data set from 3D body scanner anthropometric measurements and a questionnaireFecha de publicación
2017-04Editor
ElsevierCita bibliográfica
A. Pierola, I. Epifanio, S. Alemany An ensemble of ordered logistic regression and random forest for child garment size matching Computers & Industrial Engineering, Volume 101, November 2016, Pages 455-465Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://www.sciencedirect.com/science/article/pii/S2352340917300446Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
A dataset of a fit assessment study in children is presented. Anthropometric measurements of 113 children were obtained using a 3D body scanner. Children tested a t-shirt of different sizes and a different model for ... [+]
A dataset of a fit assessment study in children is presented. Anthropometric measurements of 113 children were obtained using a 3D body scanner. Children tested a t-shirt of different sizes and a different model for boys and girls, and their fit was assessed by an expert. This expert labeled the fit as 0 (correct), −1 (if the garment was small for that child), or 1 (if the garment was large for that child) in an ordered factor called Size-fit. Moreover, the fit was numerically assessed from 1 (very poor fit) to 10 (perfect fit) in a variable called Expert evaluation. This data set contains the differences between the reference mannequin of the evaluated size and the child׳s anthropometric measurements for 27 variables. Besides these variables, in the data set, we can also find the gender, the size evaluated, and the size recommended by the expert, including if an intermediate, but nonexistent size between two consecutive sizes would have been the right size. In total, there are 232 observations. The analysis of these data can be found in Pierola et al. (2016) [2]. [-]
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Data in Brief Volume 11, April 2017Derechos de acceso
© 2017 The Author(s). Published by Elsevier Inc.
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
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