# some init code omitted
X_train, X_test, y_train, y_test = train_test_split(X, y)

tuned_params = [{'solver': ['sgd'], 'learning_rate': ['constant'], "learning_rate_init" : [0.001, 0.01, 0.05, 0.1]},
                {"learning_rate_init" : [0.001, 0.01, 0.05, 0.1]}]

cv_method = KFold(n_splits=4, shuffle=True)
model = MLPClassifier()

grid = GridSearchCV(estimator=model, param_grid=tuned_params, cv=cv_method, scoring='accuracy')
grid.fit(X_train, y_train)
y_pred = grid.predict(X_test)

print(grid.best_score_)
print(accuracy_score(y_test, y_pred))

A dict with keys as column headers and values as columns,
that can be imported into a pandas DataFrame