Table 5.

Comparison of the root-mean-square errors (RMSEs) for training (Train), validation (Val.), and testing (Test) with Lasso and XGBoost. The validation RMSE is the average k-fold cross-validation for ΔP, PFE, and BFE with k = 5, 7, and 9, respectively.

Model	${\text{RMSE}}_{\Delta \text{P}}$ (Pa/cm2)			${\text{RMSE}}_{\text{PFE}}$ (%)			${\text{RMSE}}_{\text{BFE}}$ (%)
	Train	Val.	Test	Train	Val.	Test	Train	Val.	Test
Lasso	0.97	7.46	9.42	1.69	2.73	7.64	0.78	1.25	0.44
XGBoost	0.70	6.72	10.49	0.23	1.45	3.27	0.61	1.28	0.83