I learned that it's common to do dimensionality reduction before clustering. But,is there any situation that it is better to do clustering first then do dimensionality reduction?
Thank you so much ^^
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Clustering generally depends on some sort of distance measure. Points near each other are in the same cluster; points far apart are in different clusters. But in high dimensional spaces, distance measures do not work very well. There is a long and excellent discussion of that Here. You reduce the number of dimensions first so that your distance metric will make sense.