Qu'est-ce que « Mean decrease in impurity, permutation importance » ?

The mean decrease in impurity (MDI, or gain importance) of a feature is the total loss reduction of the splits on it across a tree ensemble, computed on the training data. The permutation importance is the drop in a held-out score when the feature’s column is randomly permuted, breaking its link with the target and the other features.