def METHOD_NAME(prediction, y, significance=None):
    """Calculates the error rate of conformal classifier predictions containing
     only a single output label.
    """
    labels, y = np.unique(y, return_inverse=True)
    prediction = prediction > significance
    idx = np.arange(0, y.size, 1)
    idx = filter(lambda x: np.sum(prediction[x, :]) == 1, idx)
    errors = filter(lambda x: not prediction[x, int(y[x])], idx)
    if len(idx) > 0:
        return np.size(errors) / np.size(idx)
    else:
        return 0