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