## 4 Result and Discussion
\begin{table}
\begin{tabular}{c l c c} \hline \hline
**Dataset** & **Machine Learning Models** & **RMSE** & **MAE** \\ \hline \multirow{4}{*}{APEXFOOT} & ML ensemble method (Randomforest) & 6.6466 & 6.4764 \\  & ML ensemble method (AdaBoost) & 7.3927 & 7.2382 \\  & ML ensemble method (GradientBoosting) & 7.6668 & 7.526 \\  & ML Stacking Ensemble Learning & 5.2078 & 5.0352 \\ \hline \multirow{4}{*}{BANKASIA} & ML ensemble method (RandomForest) & 0.4049 & 0.3000 \\  & ML ensemble method (AdaBoost) & 0.4208 & 0.2945 \\  & ML ensemble method (GradientBoosting) & 0.4052 & 0.2987 \\  & ML Stacking Ensemble Learning & 0.6428 & 0.4658 \\ \hline \multirow{4}{*}{BATASHOE} & ML ensemble method (RandomForest) & 6.2606 & 5.9338 \\  & ML ensemble method (AdaBoost) & 7.1886 & 6.9948 \\  & ML ensemble method (GradientBoosting) & 6.0615 & 5.7666 \\  & ML Stacking Ensemble Learning & 5.7256 & 5.6674 \\ \hline \multirow{4}{*}{BERGERPBL} & ML ensemble method (RandomForest) & 5.3535 & 5.2818 \\  & ML ensemble method (AdaBoost) & 7.8242 & 7.7765 \\  & ML ensemble method (GradientBoosting) & 6.6984 & 7.0529 \\  & ML Stacking Ensemble Learning & 4.9378 & 4.8600 \\ \hline \multirow{4}{*}{BEXIMCO} & ML ensemble method (RandomForest) & 6.4896 & 6.3802 \\  & ML ensemble method (AdaBoost) & 7.1802 & 7.0570 \\  & ML ensemble method (GradientBoosting) & 7.1802 & 7.5636 \\  & ML Stacking Ensemble Learning & 9.5758 & 9.5000 \\ \hline \multirow{4}{*}{BRACBANK} & ML ensemble method (Randomforest) & 5.8722 & 4.4277 \\  & ML ensemble method (AdaBoost) & 6.3241 & 4.8102 \\  & ML ensemble method (GradientBoosting) & 7.1432 & 5.7192 \\  & ML Stacking Ensemble Learning & 6.5281 & 5.6115 \\ \hline \multirow{4}{*}{CITYBANK} & ML ensemble method (Randomforest) & 3.6603 & 3.5544 \\  & ML ensemble method (Adaboost) & 5.1566 & 5.0716 \\  & ML ensemble method (GradientBoosting) & 4.5469 & 4.4633 \\  & ML Stacking Ensemble Learning & 3.6076 & 3.5365 \\ \hline \multirow{4}{*}{DESCO} & ML ensemble method (Randomforest) & 1.0350 & 0.8394 \\  & ML ensemble method (Adaboost) & 1.6060 & 1.3092 \\  & ML ensemble method (GradientBoosting) & 1.1690 & 0.9720 \\  & ML Stacking Ensemble Learning & 0.9726 & 0.8290 \\ \hline \multirow{4}{*}{DHAKABANK} & ML ensemble method (RandomForest) & 1.4607 & 1.2543 \\  & ML ensemble method (AdaBoost) & 1.7555 & 1.6016 \\  & ML ensemble method (GradientBoosting) & 1.6657 & 1.4554 \\  & ML Stacking Ensemble Learning & 1.6992 & 1.5735 \\ \hline \multirow{4}{*}{DUTCHBANGLABANK} & ML ensemble method (RandomForest) & 15.4895 & 15.4166 \\  & ML ensemble method (AdaBoost) & 18.8228 & 18.7540 \\  & ML ensemble method (GradientBoosting) & 14.9011 & 14.8032 \\  & ML Stacking Ensemble Learning & 20.4852 & 20.4260 \\ \hline \multirow{4}{*}{Eximbank} & ML ensemble method (Randomforest) & 0.9836 & 0.8807 \\  & ML ensemble method (Adaboost) & 1.4827 & 1.3170 \\  & ML ensemble method (GradientBoosting) & 1.2541 & 1.0899 \\  & ML Stacking Ensemble Learning & 0.7287 & 0.6072 \\ \hline \multirow{4}{*}{Fuwangfood} & ML ensemble method (RandomForest) & 7.3138 & 6.1929 \\  & ML ensemble method (AdaBoost) & 7.5585 & 6.2670 \\  & ML ensemble method (GradientBoosting) & 9.7713 & 8.6078 \\  & ML Stacking Ensemble Learning & 5.2664 & 4.5548 \\ \hline \multirow{4}{*}{IBNSINA} & ML ensemble method (RandomForest) & 1.3931 & 1.1716 \\  & ML ensemble method (AdaBoost) & 1.5116 & 1.2887 \\  & ML ensemble method (GradientBoosting) & 1.4613 & 1.2196 \\  & ML Stacking Ensemble Learning & 1.2653 & 1.0263 \\ \hline \multirow{4}{*}{IFIC} & ML ensemble method (Randomforest) & 3.5166 & 3.4134 \\  & ML ensemble method (AdaBoost) & 3.8412 & 3.7434 \\ \cline{1-1}  & ML ensemble method (GradientBoosting) & 4.2209 & 4.0965 \\ \cline{1-1}  & ML Stacking Ensemble Learning & 2.9332 & 2.8153 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: \(Cont.\)Table 2 provides the representation of RMSE and MAE error values obtained from twenty different datasets of a frontier market using deep learning models such as CNN, LSTM and Bi-LSTM and our proposed stacking ensemble of neural network model.