Would it come from the simultaneous use of `max_depth`, `min_samples_split`, `min_samples_leaf`?
I have just done some experiments. When I drop `max_features`, I got
```
RandomizedSearchCV took 9.86 seconds for 20 candidate parameter settings.
Model with rank: 1
Mean validation score: 0.971 (std: 0.003)
Parameters: {'max_features': 7, 'min_samples_split': 4, 'bootstrap': False, 'criterion': 'entropy', 'min_samples_leaf': 2}
```

All those three parameters influence the pre-pruning.