20.500.12556/DKUM-95710 Threshold adaptation for improved wrapper-based evolutionary feature selection Feature selection is essential for enhancing classification accuracy, reducing overfitting, and improving interpretability in high-dimensional datasets. Evolutionary Feature Selection (EFS) methods employ a threshold parameter � to decide feature inclusion, yet the widely used static setting �=0.5 may not yield optimal results. This paper presents the first large-scale, systematic evaluation of threshold adaptation mechanisms in wrapper-based EFS across a diverse number of benchmark datasets. We examine deterministic, adaptive, and self-adaptive threshold parameter control under a unified framework, which can be used in an arbitrary bio-inspired algorithm. Extensive experiments and statistical analyses of classification accuracy, feature subset size, and convergence properties demonstrate that adaptive mechanisms outperform the static threshold parameter control significantly. In particular, they not only provide superior tradeoffs between accuracy and subset size but also surpass the state-of-the-art feature selection methods on multiple benchmarks. Our findings highlight the critical role of threshold adaptation in EFS and establish practical guidelines for its effective application. feature selection evolutionary algorithm feature threshold evolutionary feature selection izbor funkcij evolucijski algoritmi prag funkcije evolucijska izbira lastnosti true false true MDPI Angleški jezik Slovenski jezik https://www.mdpi.com/journal/biomimetics © 2025 by the authors Članek v reviji 2025-10-14 12:09:38 2025-10-14 12:09:38 2025-10-15 03:14:25 0000-00-00 00:00:00 2025 0 0 27 str. iss. 10, [art. no.] 670 Vol. 10 2025 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2025-08-31 2025-10-02 2025-10-05 004.8 252610307 10.3390/biomimetics10100670 2313-7673 biomimetics-10-00670-v2_(1).pdf biomimetics-10-00670-v2_(1).pdf 1 FA9C9F932DA20FF789132F5C5F87DC08 7fa892f8c18a75571c10962475eb967c799cee6fa4a77c4366316fa8bc3609dd 125936cb-a8e6-11f0-97dd-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=199835 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0