Unsupervised feature selection regression model with nonnegative sparsity constraints

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...

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Veröffentlicht in:	Journal of intelligent & fuzzy systems 2023-01, Vol.45 (1), p.637-648
Hauptverfasser:	Zhao, Xue, Li, Qiaoyan, Xing, Zhiwei, Dai, Xuezhen
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Clustering Constraint modelling Feature selection Labels Matrices (mathematics) Optimization Regression models Sparsity Unsupervised learning
Online-Zugang:	Volltext
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