An interpretable and balanced machine learning framework for Parkinson’s disease prediction using feature engineering and explainable AI
Fig 10
Receiver operating characteristic (ROC) curves for the nine models under (a) original imbalanced data, (b) NearMiss undersampling, and (c) SMOTE oversampling.
These curves illustrate each model’s classification performance across data balancing techniques. (a) Base Models. (b) Near Miss Models. (c) SMOTE Models.