Table 1 Results of the variable importance ranking from the information-driven and human-driven variable selection.

From: VENturing into machine learning for the morphological analysis of von Economo neurons

Importance ranking

Information-driven variable selection

Human-driven variable selection

1

Average length

Overall width

2

Number of stems

Total number of trees

3

Average diameter

Overall depth

4

Average fragmentation

Max path distance

5

Max fragmentation

Overall height

6

Average Rall’s ratio

Average Contraction

7

Soma surface

Soma surface

8

Number of branches

Average Rall’s ratio

9

Partition asymmetry

Total number of branches

10

Total Volume

Max branch order

11

Average branch order

Average diameter

  1. Variables identified as important by both human-driven and information-driven variable selection are shown in bold.