Unsupervised feature selection regression model with nonnegative sparsity constraints

• Published in: Journal of intelligent & fuzzy systems Vol. 45; no. 1; pp. 637 - 648
• Main Authors: Zhao, Xue, Li, Qiaoyan, Xing, Zhiwei, Dai, Xuezhen
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.01.2023; Sage Publications Ltd
• Subjects: Algorithms; Clustering; Constraint modelling; Feature selection; Labels; Matrices (mathematics); Optimization; Regression models; Sparsity; Unsupervised learning; Non-negative matrix factorization; unsupervised; feature selection; spectral clustering; L2,1-norm

Selecting appropriate features can better describe the characteristics and structure of data, which play an important role in further improving models and algorithms whether for supervised or unsupervised learning. In this paper, a new unsupervised feature selection regression model with nonnegative...