If some data are nicely separated into clusters using UMAP but not as nicely using T-SNE, what could be the interpretation ?


1 Answer 1


I just copy what I wrote on the other thread:

Hi @dantferno, from my point of view it's usual that UMAP works better than t-SNE just because of their mathematical roots. If you're interested in that you can go to the papers and check it, but to sum up: UMAP is a enhanced version of t-SNE. I always use UMAP over t-SNE, I didn't find yet a single case in which t-SNE works better than UMAP. It doesn't mean anything about your data or its structure, it's just because of the mathematical operations of the algorithms.

Actually, nowadays I see t-SNE as an obsolete algorithm because UMAP outperforms it. Not only because it obtain better results, but it's also faster.


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