def inverse_transform_labels(encoder, k_preds):
    """
    Utilizes *encoder* to transform encoded labels back to the original \
    strings.

    Args:
        encoder (sklearn.preprocessing.LabelEncoder): The encoder to be \
            utilized
        k_preds (list): Contains predictions in (label, score) pairs

    Returns:
        list: Contains predictions in (label, score) pairs, where label is \
            now in the original string format
    """
    label_mapping = dict(
        zip(encoder.transform(encoder.classes_), encoder.classes_))
    k_preds_new = [(label_mapping[pred[0]], pred[1]) for k_pred in k_preds
                   for pred in k_pred]
    return k_preds_new