How to tune parameters in Random Forest, using Scikit Learn?

Question

class sklearn.ensemble.RandomForestClassifier(n_estimators=10,
                                              criterion=\'gini\', 
                                            


        

Answer 1

n_estimators is good one as others said. It is also good at dealing with the overfitting when increasing it.

But I think min_sample_split is also helpful when dealing with overfitting occurred in a small-sample but big-features dataset.