As in RF, in GBR a cross validation is performed with LOPO strategy, the following range for each parameter of the model:number of estimators (trees), in the rage of {5,10,…,500}; the maximum number of features in each tree in {2,3,…,23}; the leaf size in {1,2,…,5}; and the learning rate in the range of {0.01,0.02,…,1}. Besides, the criterion which measures the quality of a split is set friedman mse. The numerical evaluation are reported in Table 11 and Table 12, for both the average and Hausdorff OFs.