Table 3.
Result based on regression metrics for target variable Y1 (Heating_Load).
| Regression model | R2 | MSE | MAE | RAE |
|---|---|---|---|---|
| RFR-AL # 1 | 0.9950 | 0.5445 | 0.3887 | 0.0171 |
| RFR-AL #2 | 0.9947 | 0.5726 | 0.4011 | 0.0176 |
| RFR-AL # 3 | 0.9951 | 0.5287 | 0.4045 | 0.0178 |
| GBR-AL # 1 | 0.9907 | 1.0092 | 0.6424 | 0.0282 |
| GBR-AL #2 | 0.9907 | 1.0092 | 0.6425 | 0.0282 |
| GBR-AL # 3 | 0.9907 | 1.0092 | 0.6424 | 0.0282 |
| KNR-AL # 1 | 0.9700 | 3.2378 | 1.1017 | 0.0484 |
| KNR-AL #2 | 0.9700 | 3.2378 | 1.1017 | 0.0484 |
| KNR-AL # 3 | 0.9700 | 3.2378 | 1.1017 | 0.0484 |
| CBR-AL # 1 | 0.9975 | 0.2667 | 0.2984 | 0.0131 |
| CBR-AL #2 | 0.9975 | 0.2667 | 0.2984 | 0.0131 |
| CBR-AL # 3 | 0.9975 | 0.2667 | 0.2984 | 0.0131 |
| XGBR-AL # 1 | 0.9941 | 0.6414 | 0.3774 | 0.0166 |
| XGBR-AL #2 | 0.9941 | 0.6414 | 0.3774 | 0.0166 |
| XGBR-AL # 3 | 0.9941 | 0.6414 | 0.3774 | 0.0166 |
| LR-AL # 1 | 0.9666 | 3.6108 | 1.2413 | 0.0545 |
| LR-AL #2 | 0.9666 | 3.6108 | 1.2413 | 0.0545 |
| LR-AL # 3 | 0.9666 | 3.6108 | 1.2413 | 0.0545 |
| LGBMR-AL # 1 | 0.9936 | 0.6904 | 0.5035 | 0.0221 |
| LGBMR-AL #2 | 0.9936 | 0.6904 | 0.5035 | 0.0221 |
| LGBMR-AL # 3 | 0.9936 | 0.6904 | 0.5035 | 0.0221 |
| DTR-AL # 1 | 0.9948 | 0.5634 | 0.3569 | 0.0157 |
| DTR-AL #2 | 0.9943 | 0.6149 | 0.3827 | 0.0168 |
| DTR-AL # 3 | 0.9899 | 1.0896 | 0.4192 | 0.0184 |
Key: R2, prediction accuracy; MSE, mean squared error; MAE, mean absolute error; RAE, relative absolute error.