Novel binary walrus optimization algorithms BWaOA and BWaOA-C with crossover operator for feature selection in high-dimensional data

Abstract Redundant and irrelevant features in high-dimensional datasets hinder the development of efficient machine learning models. Most existing Feature Selection (FS) algorithms are developed based on either embedded or filter techniques, which makes it challenging to identify the highly discrimi...

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Vydané v:	Discover Computing Ročník 28; číslo 1; s. 1 - 45
Hlavní autori:	Farid Ayeche, Adel Alti
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Springer 27.10.2025
Predmet:	Binary walrus optimization algorithm Classification Feature selection K-Nearest neighbor Machine learning
ISSN:	2948-2992
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