The distribution of minimal depth among the trees of the forest for the top significant variables is shown in Figure 3. The minimal depth of a variable represents the depth of the node which splits on that variable and is the closest to the root of the decision tree. The lower mean minimal depth of a variable represents higher number of observations (participants) categorized in a specific group on the basis of that variable (i.e., better classification). The order/rank of the top significant variables (29 FC connections, three neuropsychological scores and all four impulsivity scores) followed the same pattern (as in Table 3) in the minimal depth plot, which is based on minimal depth and the number of trees.
