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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_feature_set_all():
 """ Return a list of entire features. A set of entire features regardless of being used to train a model or predict a class. Returns ------- feature_names : list A list of features' names. """


    features = get_feature_set()

    features.append('cusum')
    features.append('eta')
    features.append('n_points')
    features.append('period_SNR')
    features.append('period_log10FAP')
    features.append('period_uncertainty')
    features.append('weighted_mean')
    features.append('weighted_std')

    features.sort()

    return features