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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Bibliographic Details

Published in:	Knowledge-based systems Vol. 252; p. 109449
Main Authors:	Qiu, Zhifeng, Zeng, Wanxin, Liao, Dahua, Gui, Ning
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 27.09.2022
Subjects:	Attention mechanism Autoencoder Feature selection Self-supervised Attention mechanism Self-supervised Feature selection Autoencoder
ISSN:	0950-7051, 1872-7409
Online Access:	Get full text
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