Fig. 8
From: A machine learning approach for mapping the very shallow theoretical geothermal potential
Prediction Intervals (with 95% confidence) from Quantile Random Forests for the monthly ground temperature at a depth of 100 and 50Â cm for an example of 2 months. a and c PIs in the test set, in January, respectively, for 100Â cm and 50Â cm; b and d PIs for 30 random new points, in January, respectively, for 100Â cm and 50Â cm; e and g PIs in the test set, in June, respectively, for 100Â cm and 50Â cm; f and h PIs for 30 random unknown points, in June, respectively, for 100Â cm and 50Â cm