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Appliedmath 04 00081 by NURİYE SANCAR is a document available to read on EtoBox.

This study introduces a two-stage feature selection method that combines Artificial Bee Colony (ABC) optimization with Adaptive LASSO (AD_LASSO) to enhance model performance in high-dimensional datasets. The first stage utilizes ABC for global feature subset selection, while the second stage refines the selection using AD_LASSO to improve interpretability and eliminate redundancy. Results demonstrate that the ABC-ADLASSO method outperforms traditional methods in accuracy and precision, particularly in compl

Author

NURİYE SANCAR

Language

EN