Table 6.

k-Fold cross-validation performance comparison.

Model	MAE (mean ± std)	MSE (mean ± std)	R2 (mean ± std)
Gradient Boosting	0.048 ± 0.003	0.0037 ± 0.0003	0.91 ± 0.02
XGBoost	0.045 ± 0.002	0.0033 ± 0.0002	0.92 ± 0.02
LightGBM	0.047 ± 0.003	0.0034 ± 0.0003	0.92 ± 0.02
CatBoost	0.044 ± 0.002	0.0032 ± 0.0002	0.93 ± 0.01
Neural Network	0.050 ± 0.004	0.0036 ± 0.0004	0.90 ± 0.03
LSTM	0.049 ± 0.004	0.0035 ± 0.0003	0.91 ± 0.03
Stacked Regressor	0.042 ± 0.002	0.0031 ± 0.0002	0.94 ± 0.01