Exploring the Relationships of Grading, Sizing, and Anthropometric Data

Schofield, Nancy A.; LaBat, Karen L.

doi:10.1177/0887302x0502300102

Cited by 46 publications

(35 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Users can base their decision on their previous experience. But each company has its own sizing, and what is more, this can change over time (Schofield and LaBat, 2005). This is therefore not a reliable strategy (Sindicich and Black, 2011).…”

Section: Introductionmentioning

confidence: 99%

An ensemble of ordered logistic regression and random forest for child garment size matching

Pierola

Epifanio

Alemany

2016

Computers & Industrial Engineering

View full text Add to dashboard Cite

Size fitting is a significant problem for online garment shops. The return rates due to size misfit are very high. We propose an ensemble (with an original and novel definition of the weights) of ordered logistic regression and random forest (RF) for solving the size matching problem, where ordinal data should be classified. These two classifiers are good candidates for combined use due to their complementary characteristics. A multivariate response (an ordered factor and a numeric value assessing the fit) was considered with a conditional random forest. A fit assessment study was carried out with 113 children. They were measured using a 3D body scanner to obtain their anthropometric measurements. Children tested different garments of different sizes, and their fit was assessed by an expert. Promising results have been achieved with our methodology. Two new measures have been introduced based on RF with multivariate responses to gain a better understanding of the data. One of them is an intervention in prediction measure defined locally and globally. It is shown that it is a good alternative to variable importance measures and it can be used for new observations and with multivariate responses. The other proposed tool informs us about the typicality of a case and allows us to determine archetypical observations in each class.Keywords: Multivariate conditional random forest; Proportional odds logistic regression; Supervised learning; Ordinal classification; Childrenswear garment fitting; Variable importance ACKNOWLEDGEMENTS This work has been partially supported by Grants DPI2013-47279-C2-1-R and DPI2013-47279-C2-2-R.An ensemble of ordered logistic regression and random forest for child garment size matchingSize fitting is a significant problem for online garment shops. The return rates due to size misfit are very high. We propose an ensemble (with an original and novel definition of the weights) of ordered logistic regression and random forest (RF) for solving the size matching problem, where ordinal data should be classified. These two classifiers are good candidates for combined use due to their complementary characteristics. A multivariate response (an ordered factor and a numeric value assessing the fit) was considered with a conditional random forest. A fit assessment study was carried out with 113 children. They were measured using a 3D body scanner to obtain their anthropometric measurements. Children tested different garments of different sizes, and their fit was assessed by an expert. Promising results have been achieved with our methodology. Two new measures have been introduced based on RF with multivariate responses to gain a better understanding of the data. One of them is an intervention in prediction measure defined locally and globally. It is shown that it is a good alternative to variable importance measures and it can be used for new observations and with multivariate responses. The other proposed tool informs us about the typicality of a case and allows us to determine archetypical obs...

show abstract

Section: Introductionmentioning

confidence: 99%

An ensemble of ordered logistic regression and random forest for child garment size matching

Pierola

Epifanio

Alemany

2016

Computers & Industrial Engineering

View full text Add to dashboard Cite

show abstract

“…To produce garments that fit the population, it follows that the sizes must correspond to real grouping. However, this is often not the case, as indicated by the results obtained by Shofield and LaBat [1]. Their study of forty size charts for women's clothing showed that the different sizes are defined using arbitrary constant intervals between sizes, all vertical measurements increase as the size increases and that the differences between the principal girths are constant for all sizes.…”

Section: Introductionmentioning

confidence: 81%

Finding Clothing That Fit through Cluster Analysis and Objective Interestingness Measures

Peña

Viktor

Paquet

2009

Data Warehousing and Knowledge Discovery

View full text Add to dashboard Cite

“…Grading begins with a garment pattern that has been created for a fit model or dress form in a designer or manufacturer's base size. Grading is accomplished by applying increases (for larger sizes) or decreases (for smaller sizes) at key locations of each pattern piece to create a pattern in the next size (Schofield & LaBat, 2005). The differences (grade) between retailers' sizes were recorded from the 47 retailers' online measurements in Appendix 2.…”

Section: Sizing and Comfortmentioning

confidence: 99%

Stretch to fit – made to fit^†

Dove

2016

International Journal of Fashion Design, Technology and Educati

View full text Add to dashboard Cite

It is widely recognised that elastic fibres (spandex and lycra) are used to impart stretch to fabrics. The amount the apparel stretches to fit depends on the elastic fibres' characteristics and recovery properties, in providing pressure comfort and ease of movement. Made to fit, by comparison, is the construction of two-dimensional non-stretch pattern blocks using body darts to denote the 3D form. Building patternmaking theory can lead to a better understanding of the body to garment interaction, and the fit of apparel. This investigation commences with the identification of garment block construction methods for woven and jersey apparel, and corresponding garment fit expectations, comparing two published patternmaking methods. It proposes a system of adding bust cup grading into non-stretch garment blocks. The experimental results indicate that the proposed method would be easy to implement and could generate patterns with an improved bust girth fit. The purpose of this paper is to show that a new grading system would better serve the female population than the system currently in use. This system would also be more efficient as it would reduce the consumer time spent in fit identification as labelling would also indicate bust cup sizing. ARTICLE HISTORY

show abstract

Exploring the Relationships of Grading, Sizing, and Anthropometric Data

Cited by 46 publications

References 4 publications

An ensemble of ordered logistic regression and random forest for child garment size matching

An ensemble of ordered logistic regression and random forest for child garment size matching

Finding Clothing That Fit through Cluster Analysis and Objective Interestingness Measures

Stretch to fit – made to fit^†

Contact Info

Product

Resources

About

Exploring the Relationships of Grading, Sizing, and Anthropometric Data

Cited by 46 publications

References 4 publications

An ensemble of ordered logistic regression and random forest for child garment size matching

An ensemble of ordered logistic regression and random forest for child garment size matching

Finding Clothing That Fit through Cluster Analysis and Objective Interestingness Measures

Stretch to fit – made to fit†

Contact Info

Product

Resources

About

Stretch to fit – made to fit^†