Application of Unsupervised Feature Selection in Cashmere and Wool Fiber Recognition

Application of Unsupervised Feature Selection in Cashmere and Wool Fiber Recognition

ABSTRACTSuitable features are the key to identifying cashmere and wool fibers, and feature selection is an important step in classification. Existing supervised feature selection methods need to consider the information between fiber features and class labels. Aiming at making up for this deficiency...

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Bibliographic Details
Main Authors: Yaolin Zhu, Xingze Wang, Meihua Gu, Gang Hu, Wenya Li
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Journal of Natural Fibers
Subjects:
Cashmere and wool
classification
unsupervised feature selection
clustering number
DB index
k-means clustering
Online Access:https://www.tandfonline.com/doi/10.1080/15440478.2024.2311306

Internet

https://www.tandfonline.com/doi/10.1080/15440478.2024.2311306

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