  This paper tries to present a more unified view of clustering, by identifying
the relationships between five different clustering algorithms. Some of the
results are not new, but they are presented in a cleaner, simpler and more
concise way. To the best of my knowledge, the interpretation of DBSCAN as a
climbing procedure, which introduces a theoretical connection between DBSCAN
and Mean shift, is a novel result.
