A-SFS: Semi-supervised feature selection based on multi-task self-supervision

Feature selection is an important process in machine learning. It builds an interpretable and robust model by selecting the features that contribute the most to the prediction target. However, most mature feature selection algorithms, including supervised and semi-supervised, fail to fully exploit t...

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Veröffentlicht in:	Knowledge-based systems Jg. 252; S. 109449
Hauptverfasser:	Qiu, Zhifeng, Zeng, Wanxin, Liao, Dahua, Gui, Ning
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 27.09.2022
Schlagworte:	Attention mechanism Autoencoder Feature selection Self-supervised Attention mechanism Self-supervised Feature selection Autoencoder
ISSN:	0950-7051, 1872-7409
Online-Zugang:	Volltext
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