from sklearn.ensemble import ExtraTreesClassifier
from sklearn.model_selection import GridSearchCV

# Demo of model parameter tuning 

# load X_train, y_train data
model = ExtraTreesClassifier(n_estimators=100, max_features=30);

# to check preset parameters, one can use
# model.get_params().keys()

gsc = GridSearchCV(
    estimator=model,
    param_grid={
        'n_estimators': range(20,140,20),
        'max_features': range(20,140,20),
        'min_samples_leaf': range(1,4,1),
        #'min_samples_split': range(15,35,10),
    },
    scoring='r2',
    cv=3
)

grid_result = gsc.fit(X_train, y_train);
print(grid_result.best_params_);