SHAP-Guided Feature Selection for IoT Botnet Detection: A Comparative Study with Conventional Methods
An explainability-guided feature selection framework that employs SHAP values derived from an XGBoost model to rank features and systematically compares its effectiveness with Mutual Information, Analysis of Variance (ANOVA), and Principal Component Analysis (PCA) across nine machine learning classifiers using the N-Ba...