Table 6 Calculations and error Report.
From: Machine learning analysis of CO2 and methane adsorption in tight reservoir rocks
Error metric | Dataset | CO2 | CH4 | ||||||
|---|---|---|---|---|---|---|---|---|---|
Random forst | CatBoost | Extra trees | AdaBoost | Random forest | CatBoost | Extera trees | AdaBoost | ||
R 2 | Train | 0.9968 | 0.9999 | 1.0000 | 0.9985 | 0.9971 | 0.9985 | 0.9998 | 0.9970 |
Test | 0.9903 | 0.9968 | 0.9946 | 0.9877 | 0.9796 | 0.9911 | 0.9873 | 0.9742 | |
Total | 0.9947 | 0.9989 | 0.9982 | 0.9950 | 0.9923 | 0.9965 | 0.9963 | 0.9907 | |
RMSE | Train | 0.2709 | 0.0519 | 0.0243 | 0.1843 | 0.0688 | 0.0487 | 0.0183 | 0.0702 |
Test | 0.5052 | 0.2921 | 0.3756 | 0.5681 | 0.1722 | 0.1140 | 0.1359 | 0.1936 | |
Total | 0.3579 | 0.1660 | 0.2070 | 0.3476 | 0.1185 | 0.0746 | 0.0760 | 0.1213 | |
MAE | Train | 0.1611 | 0.0364 | 0.0095 | 0.1224 | 0.0378 | 0.0346 | 0.0074 | 0.0487 |
Test | 0.3381 | 0.2148 | 0.2716 | 0.3934 | 0.0980 | 0.0726 | 0.0781 | 0.1145 | |
Total | 0.2144 | 0.0901 | 0.0883 | 0.2039 | 0.0558 | 0.0460 | 0.0286 | 0.0685 | |
MAPE | Train | 8.8524 | 3.4402 | 0.8646 | 28.0617 | 6.3432 | 5.8858 | 0.9053 | 12.2420 |
Test | 22.5793 | 17.8237 | 19.6057 | 32.9776 | 20.6930 | 25.2515 | 22.2115 | 31.1199 | |
Total | 12.9831 | 7.7684 | 6.5042 | 29.5410 | 10.6515 | 11.7000 | 7.3021 | 17.9097 | |