The distribution of minimal depth among the decision trees of the forests for the top significant variables is shown in Figure 4. Minimal depth of a variable represents the depth of the node that splits on that variable and is the closest to the root of the decision tree. The lower mean minimal depth of a variable represents a higher number of observations (participants) categorized in a specific group based on that variable. The ranking based on the minimal depth parameter shows that two of the impulsivity variables are a the top of the importance list, followed by several reward network connections and a neuropsychological feature (total correct score in the forward trials of the visual span test).
