Table 5.

Model Overall performance.

Model name	Accuracy	MAE	MSE	RMSE	R2 value
Model performance (Overall) during training
Adaboost	0.47	1.07	2.58	1.60	–0.66
Gradient Boost	0.93	0.18	0.55	0.74	0.64
Decision Tree	0.93	0.18	0.55	0.74	0.64
Random Forest	0.60	0.88	2.18	1.47	-0.47
Model performance(Overall) during testing
Adaboost	0.49	1.00	2.35	1.53	-0.68
Gradient Boost	0.92	0.21	0.65	0.81	0.53
Decision Tree	0.92	0.21	0.65	0.81	0.53
Random Forest	0.59	0.90	2.24	1.49	-0.528