import itertools

# evaluate combinations of p, d and q values for an ARIMA model
def evaluate_models(dataset, p_values, d_values, q_values):
    dataset = dataset.astype('float32')
    best_score, best_cfg = float("inf"), None
    for order in itertools.product(p_values, d_values,q_values):
        try:
            mse = evaluate_arima_model(dataset, order)
            if mse < best_score:
                best_score, best_cfg = mse, order
        except:
            continue
            mse = evaluate_arima_model(dataset, order)
    print('Best ARIMA%s RMSE=%.3f' % (best_cfg, best_score))