Copula entropy-based golden jackal optimization algorithm for high-dimensional feature selection problems

[Display omitted] Feature selection (FS) is a crucial process that aims to remove unnecessary features from datasets. It plays a role in data mining and machine learning (ML) by reducing the risk associated with high-dimensional datasets. FS is considered a challenging problem that is difficult to s...

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Veröffentlicht in:	Expert systems with applications Jg. 238; S. 121582
Hauptverfasser:	Askr, Heba, Abdel-Salam, Mahmoud, Hassanien, Aboul Ella
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 15.03.2024
Schlagworte:	Binary enhanced golden jackal optimization Copula entropy Feature selection High-dimensional datasets High-dimensional datasets Feature selection Binary enhanced golden jackal optimization Copula entropy
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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