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Jun 8, 2021 at 15:23 history edited Haitao Du CC BY-SA 4.0
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Mar 23, 2017 at 1:53 comment added Has QUIT--Anony-Mousse Except that DBSCAN doesn't optimize a metric?
Mar 22, 2017 at 11:02 comment added usεr11852 @Anony-Mousse: The answer is particular to k-means as an example but it would be qualitatively the same if DBSCAN or spectral clustering or whatever else it was used. It just shows that a particular metric can be over-fitted.
Mar 22, 2017 at 7:10 comment added Has QUIT--Anony-Mousse And if you don't use k-means? Say, average linkage clustering? I fear thar your answer is overfitting to k-means.
Mar 21, 2017 at 21:28 comment added usεr11852 +1 because it is a constructive answer but to play devil's advocate you do know they are 3 clusters. If someone showed this data without any context a 2-cluster solution would work beautifully too. Maybe you even have some of the upper right-most points as outliers to play "real-data-have-outliers" too. It would be much more constructive (and stringent) to look at the coherence between bootstrapped/jittered/subsetted clustering runs using some statistic (eg. cophenetic correlation, Adjusted Rand-Index, etc.).
Mar 21, 2017 at 18:23 comment added Haitao Du @rz.He yes, check this answer stats.stackexchange.com/questions/261537/…
Mar 21, 2017 at 18:22 history edited Haitao Du CC BY-SA 3.0
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Mar 21, 2017 at 18:19 comment added rz.He Hi hxd1011, thanks for your quick reply. Another question, do you have any recommendations about how to determine the actual number of clusters when we do clusterings such as kmeans?
Mar 21, 2017 at 18:16 vote accept rz.He
Mar 21, 2017 at 18:15 history edited Haitao Du CC BY-SA 3.0
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Mar 21, 2017 at 18:09 history edited Haitao Du CC BY-SA 3.0
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Mar 21, 2017 at 18:00 history edited Haitao Du CC BY-SA 3.0
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Mar 21, 2017 at 17:55 history answered Haitao Du CC BY-SA 3.0