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search trees tend not to scale well to higher dimensions though, right?

from what I've seen I had the impression that Yinyang k-means was the best way to take advantage of the sparsity.



Most data I've used is for geospatial with D<=4 (xyzt) so for me search trees worked great. But for things like descriptor or embedding clustering yes, trees wouldn't be useful.




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