I'm new in Mining and Clustering and I wonder how to cut off the hierarchical clustering Dendrogram to obtain a specific number of clusters. The problem is here that the data is noisy and the SLINK algorithm consider these noises as a cluster and when I cut off the Dendrogram to obtain exactly K cluster, it gives me some noisy cluster and so ignores all or some of K expected clusters. So I think there should be some techniques to cut the Dendrogram without considering the noisy clusters.

Note that I know the number of K and it's not a problem how to specify this number!


  • $\begingroup$ How can noise be a cluster? If it is random, then it will scatter things randomly. If it isn't random then, is it noise? Seems to me that your noisy cluster is actually something interesting. $\endgroup$
    – Peter Flom
    Aug 2, 2023 at 11:15

1 Answer 1


Choose the height h such that there are k non-trivial (non noise) clusters.

Then cut the tree at this height.

Note that this may not be satisfiable. If your data is a single gaussian, it may not be possible to find k non-trivial clusters.


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