2023
DOI: 10.1049/cth2.12498
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Binary grey wolf optimizer with a novel population adaptation strategy for feature selection

Abstract: Feature selection is a fundamental pre‐processing step in machine learning that aims to reduce the dimensionality of a dataset by selecting the most effective features from the original features. This process is regarded as a combinatorial optimization problem, and the grey wolf optimizer (GWO), a novel meta‐heuristic algorithm, has gained popularity in feature selection due to its fast convergence speed and easy implementation. In this paper, an improved binary GWO algorithm incorporating a novel Population A… Show more

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Cited by 2 publications
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