gridsearch.py

parameters = {'n_estimators': range(10,200,10), 'max_depth': range(10,100,5)}
rf = RandomForestRegressor()
gs_rf = GridSearchCV(rf, parameters)
gs_rf.fit(X_train, y_train)
gs_rf.best_estimator_

RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse',
                      max_depth=70, max_features='auto', max_leaf_nodes=None,
                      max_samples=None, min_impurity_decrease=0.0,
                      min_impurity_split=None, min_samples_leaf=1,
                      min_samples_split=2, min_weight_fraction_leaf=0.0,
                      n_estimators=30, n_jobs=None, oob_score=False,
                      random_state=None, verbose=0, warm_start=False)