overfitting gridsearchcv

from sklearn.model_selection import GridSearchCV
decisiontree = DecisionTreeClassifier(random_state=43)

params = {'max_depth':[3,5,7],
          'min_samples_leaf':[3,5,10],
          'min_samples_split':[8,10,12]}

grid_search = GridSearchCV(estimator=decisiontree,param_grid=params,cv=4,n_jobs=-1, verbose=True, scoring='accuracy')

grid_search.fit(X_train, y_train)

print('nBest Parameters:',grid_search.best_params_)
print('nBest Score:',grid_search.best_score_)