An Approach for Demand Forecasting in Steel Industries Using Ensemble Learning

Table 7

Comparing stacking ensemble model with the best performing ML models.

Models		MAE	RMSE	MAPE
SVR	0.931	0.202	0.246	0.902
ELM	0.942	0.183	0.226	0.880
MLP	0.961	0.149	0.186	0.569
RFR	0.966	0.133	0.172	0.517
GBR	0.969	0.125	0.164	0.401
XGBR	0.974	0.120	0.151	0.619
STACK2	0.977	0.112	0.143	0.463
STACK1	0.977	0.112	0.144	0.445

The best approaches were shown in bold type.