if scaler1 is None:  # this indicates the `fit()`
        min_f, max_f = 0.001, 0.955
        scaler1 = MinMaxScaler(feature_range=(min_f, max_f))
        # min_f and max_f are required to be fit by scaler for consistency between train and test sets
        scaler1.fit(np.array(first + [min_f, max_f]).reshape(-1, 1))