Table 2.

Comparison of the performance of the best ML models evaluated in (Dimitrov et al., 2020) and the SHASI-ML.

Model	Recall	Specificity	Accuracy	Precision	F1 Score
RF	0.72	0.82	0.77	0.80	0.76
RSM-1NN	0.72	0.92	0.82	0.91	0.80
XGBOOST	0.84	0.75	0.79	0.77	0.80
SHASI-ML	0.84	0.86	0.85	0.86	0.84

Metrics include Recall, Specificity, Accuracy, Precision, and F1 Score. The models compared are Random Forest (RF), RSM-1NN (Random Subset Method with 1-Nearest Neighbor), XGBoost (Extreme Gradient Boosting), and SHASI-ML.