Multi-objective feature selection algorithm using Beluga Whale Optimization

The advancement of science and technology has resulted in large datasets with noisy or redundant features that hamper classification. In feature selection, relevant attributes are selected to reduce dimensionality, thereby improving classification accuracy. Multi-objective optimization is crucial in...

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Veröffentlicht in:	Chemometrics and intelligent laboratory systems Jg. 257; S. 105295
Hauptverfasser:	Kouhpah Esfahani, Kiana, Mohammad Hasani Zade, Behnam, Mansouri, Najme
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 15.02.2025
Schlagworte:	Beluga Whale Optimization Feature selection Multi-objective optimization Random forest Beluga Whale Optimization Feature selection Multi-objective optimization Random forest
ISSN:	0169-7439
Online-Zugang:	Volltext
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