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...

Full description

Bibliographic Details

Published in:	Expert systems with applications Vol. 238; p. 121582
Main Authors:	Askr, Heba, Abdel-Salam, Mahmoud, Hassanien, Aboul Ella
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 15.03.2024
Subjects:	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 Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!