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Oct 20, 2016 at 4:47 comment added Jonas You wrote hat there exists "other concepts". Can you give me a hint which other methods exist please? I am aware of several soft-clustering methods, but not even one (especially for functional data) that is insensitive of changing the cluster-result. That is why I try to find a solution for the above mentioned problem: If we use an soft-clustering algorithm that we run more often (maybe 1000 times), it would be possible to calculate the cluster-mean considering all runs. So it might be possible to get a more precise result with probabilistic backround. I hope its a little bit clearer :)
Oct 20, 2016 at 4:33 comment added Jonas Thanks for sharing your thoughts. I assumed the same in first post.
Oct 14, 2016 at 19:14 history answered Has QUIT--Anony-Mousse CC BY-SA 3.0