  A recent article proposed reduced mutual information for evaluation of
clustering, classification and community detection. The motivation is that the
standard normalized mutual information (NMI) may give counter-intuitive answers
under certain conditions and particularly when the number of clusters differs
between the two divisions under consideration. The motivation makes sense.
However, the examples given in the article are not accurate, and this comment
discusses why. In addition, this comment also empirically demonstrates that the
reduced mutual information cannot handle the difficulties of NMI and even
brings more. The necessity of Kappa is also empirically validated in this
comment.
