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What happens when you mix cosine similarity with euclidean distance? at least give a small penalty if the euclidean distance is too far off?
by singularity2001 3y ago
What happens when you mix cosine similarity with euclidean distance? at least give a small penalty if the euclidean distance is too far off?
- wongarsu 3y agoIf your embeddings are normalized this won't change much, since euclidean distance and cosine similarity produce the same ranking on normalized vectors. If your embeddings aren't normalized it's worth trying. In our use cases it never made a substantial difference, but I imagine there are cases where it does.