Feature selection based on multi-knowledge adhesion neighborhoods and modified Walrus optimizer

Abstract This study introduces an innovative rough set model, termed $\varepsilon$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> mml:miε</mml:mi> </mml:math> -Adhesion Rough Set Approximation (ARSA), which is developed by employing the concept of adhesion neighborhoods. Building on the classical rough set approximation (RSA) framework, ARSA extends its core concepts to offer a more adaptable and expressive approach to data analysis. The primary motivation behind this model is to