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Hi,
In hierarchical clustering one of the key concept is threshold of distance (euclidian) which is also key differentiator from K-Means clustering. This threshold value determines which clusters to merge and which not.
In DSS, I am unable to find this setting and it's just asking me to provide number of clusters. So wanted to check how it's different in K-Means in DSS and in which ways I can provide this threshold to my algorithm.
Thank you.
Hey,
I'm actually having the same question, and I would like to know also which method of linkage is used for the Agglomerative clustering algo ?
Thanks