A relevant feature combination assisted bi-level evolutionary multi-objective algorithm for feature selection in classification

Minimizing the number of selected features and reducing the error rate are the two primary objectives in feature selection problems. However, with the exponentially expanded search space caused by the increasing number of features, existing multi-objective feature selection methods often get trapped...

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Bibliographic Details
Published in:	Scientific reports Vol. 15; no. 1; pp. 39288 - 20
Main Authors:	Xing, Lining, Li, Jun, Ma, Hong, Su, Zhenhua, Wu, Jian
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 10.11.2025 Nature Publishing Group Nature Portfolio
Subjects:	639/166 639/705 Accuracy Algorithms Bi-level Selection Classification Datasets Efficiency Feature selection Genetic algorithms Heuristic Humanities and Social Sciences Multi-objective optimization multidisciplinary Objectives Optimization Pareto optimum Relevant feature combination Science Science (multidisciplinary) Feature selection Multi-objective optimization Relevant feature combination Bi-level Selection
ISSN:	2045-2322, 2045-2322
Online Access:	Get full text
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