Compact and Explainable Human Activity Recognition with Boruta-RFE Feature Selection and SHAP Interpretation
Human activity recognition (HAR) based on wearable sensors commonly involves high-dimensional sensor-derived features, which may contain substantial redundancy and complicate model interpretation. In this study, we developed and evaluated a compact and explainable machine-learning framework using the UCI Human Activity...