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Geothermal Energy

Science – Society – Technology

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

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