MSBWO: A Multi-Strategies Improved Beluga Whale Optimization Algorithm for Feature Selection

Feature selection (FS) is a classic and challenging optimization task in most machine learning and data mining projects. Recently, researchers have attempted to develop more effective methods by using metaheuristic methods in FS. To increase population diversity and further improve the effectiveness...

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Veröffentlicht in:	Biomimetics (Basel, Switzerland) Jg. 9; H. 9; S. 572
Hauptverfasser:	Fan, Zhaoyong, Xiao, Zhenhua, Li, Xi, Huang, Zhenghua, Zhang, Cong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 01.09.2024 MDPI
Schlagworte:	Accuracy Algorithms Analysis Behavior beluga whale optimization binary optimizer Biomimetics Data mining Datasets Engineering research Exploitation Falls (Accidents) Feature selection Genetic algorithms global optimization Heuristic programming Machine learning Mapping Marine mammals Mathematical models Mathematical optimization Methods Optimization algorithms Optimization techniques Whales & whaling White whale China binary optimizer feature selection global optimization beluga whale optimization
ISSN:	2313-7673, 2313-7673
Online-Zugang:	Volltext
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