Table 3. Comparison between results of the best six regression models considered (and SVM, as a baseline), when parameter tuning is applied.

Best values are marked in bold.

Regressor	MAE (cm)	MSE	R2	MAPE
Extra trees	1.8108	8.8154	0.769	0.1152
GBR	1.8339	8.7386	0.7705	0.116
CatBoost	1.8033	8.6005	0.7742	0.1144
Light GBM	1.8780	8.9229	0.7649	0.1188
Random forest	1.8329	9.0251	0.7645	0.1161
XG Boost	1.8452	8.8572	0.7662	0.1158
SVM (baseline)	1.9343	10.1436	0.736	0.1244

Note:

Best result in bold.