def mean_rule(probs):
    """
    Implements the first case of the median rule as defined by [1].
    This rule only makes sense if the classifiers output
    the posterior probabilities for each class.
    Parameters
    ----------
    probs:  Numpy 2d-array with rows representing each class, columns
            representing each classifier and elements representing
            posterior probabilities. Each column should sum up to
            one as a sanity check that the probabilities are valid.
    """

    return probs.mean(axis=1).argmax()