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

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

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Pierola, A.; Epifanio, I.; Alemany Mut, MS. (2016). An ensemble of ordered logistic regression and random forest for child garment size matching. Computers and Industrial Engineering. 101:455-465. doi:10.1016/j.cie.2016.10.013

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Title: An ensemble of ordered logistic regression and random forest for child garment size matching
Author:
UPV Unit: Universitat Politècnica de València. Instituto Universitario Mixto de Biomecánica de Valencia - Institut Universitari Mixt de Biomecànica de València
Issued date:
Abstract:
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 ...[+]
Subjects: Multivariate conditional random forest , Proportional odds logistic regression , Supervised learning , Ordinal classification , Childrenswear garment fitting , Variable importance
Copyrigths: Cerrado
Source:
Computers and Industrial Engineering. (issn: 0360-8352 )
DOI: 10.1016/j.cie.2016.10.013
Publisher:
Elsevier
Publisher version: http://dx.doi.org/10.1016/j.cie.2016.10.013
Thanks:
This work has been partially supported by Grants DPI2013-47279-C2-1-R and DPI2013-47279-C2-2-R.
Type: Artículo

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