# Is getting several times the same variable in a branch of a regression tree the sign of overfitting?

I am using random forests to generate regression trees. My dataset has 30k observations of 15 variables.

Each tree I generate is limited to a 4 nodes depth (including terminal leaves) and to a sampling of 6 variables amongst the 16.

I get that kind of tree:

Problem here is the 2 variables DPS_g_0 and DPS_g_1 are used several time in the same branch. It means that the algo can't find a better variable to split the subset, than the same it has used on the upper level.

Is using that kind of tree a sign of an overfitted random forest?

(5) looks like you using pary package and one assumes cforest. Thought this doesn't make a big difference for this issue, it is slightly different from randomForest implementation.
• Hi charles. I indeed used party I've tried ranger package lately which gives OOB stats with quite good results. Thanks for your answer – Ben Dec 23 '15 at 11:05