How to tune warm_start parameter of RandomForest?

random_forest
python
randomforest
sklearn

#1

The RF documentation in sklearn has an interesting parameter warm_start that is used to “reuse the solution of the previous call to fit and add more estimators to the ensemble, otherwise, just fit a whole new forest.”

I was wondering if anyone has used it before and if yes, what was the effect on predictive power of the model?
22