You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
While writing my Bachelor's Thesis which includes a comparison of clustering
34
-
validity metrics like the one presented in
35
-
`this paper <https://www.semanticscholar.org/paper/Relative-clustering-validity-criteria%3A-A-overview-Vendramin-Campello/ad93d3b55fb94827c4df45e9fc67c55a7d90d00b>`_
36
-
(but focused on the application of metrics on non-spherical/density-based clusters)
37
-
I noticed that DBCV might actually perform better if it just used euclidean distances
38
-
instead of mutual reachablity distances when constructing the minimum spanning trees.
39
-
This fork adds a parameter to the DBCV metric which toggles the usage of mutual reachability distances.
40
-
(the approach of the paper referenced above is also used in the DBCV paper)
0 commit comments