kf = StratifiedKFold(n_splits = 5, random_state=42)
param = {"criterion":["gini", "entropy"], "max_features":[1, 2, 3, 4, 5, 10,      15, 20, 25, 30, 35, 40, "log2", "auto"],
         "max_depth":[2, 4, 8, 16, 32, 64], "class_weight":[None, "balanced"]}
cv = GridSearchCV(RandomForestClassifier(), param, scoring="accuracy", n_jobs = -1, cv=kf)
cv.fit(X_train, y_train);
print("Best score (accuracy): ", cv.best_score_)
print("Best params: ", cv.best_params_)
print("Score on X_test: ", accuracy_score(y_test, cv.predict(X_test)))