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Table 4 Evaluations of machine learning models using the main dataset

From: Exploratory analysis of machine learning methods in predicting subsurface temperature and geothermal gradient of Northeastern United States

  XGBoost Random Forest Deep neural network Ridge regression
Root mean square error 4.94 ± 0.15 5.01 ± 0.17 5.08 ± 0.18 5.3 ± 0.21
Mean absolute error 3.21 ± 0.07 3.25 ± 0.08 3.39 ± 0.09 3.57 ± 0.1
Mean absolute
Percentage error
9.22 ± 0.16 9.32 ± 0.18 9.77 ± 0.33 10.38 ± 0.33