Data mining-based optimal assignment of apparel size for mass customization

Data mining-based optimal assignment of apparel size for mass customization

In this study, we have explored and discussed the data mining-based solutions to apparel size assignment using approach principle, K-means clustering, and support vector machine, respectively. A case of mass customization for men's pants in China with 200 adult males were employed to validate a...

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Bibliographic Details
Main Authors: Zhujun Wang, Cheng Chi, Mengyun Zhang, Xianyi Zeng, Pascal Bruniaux, Jianping Wang, Yingmei Xing
Format: Article
Language:English
Published: PUBLIA – SLUB Open Publishing 2020-08-01
Series:Communications in Development and Assembling of Textile Products
Subjects:
garment size
mass customization
data mining
clustering algorithm
k-means clustering
support vector machine
Online Access:https://journals.qucosa.de/cdatp/article/view/4
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