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Not a real bug, and maybe it's just personal preference, but I feel like the normalization in several distances is counterintuitive.
For example, the documentation for CosineSimilarity, says
Which of course is correct, however, the default DotProductSimilarity itself normalizes the input vectors.
Also, the documentation for the LpDistance says
With default parameters, this is the Euclidean distance.
This is not true as the Euclidean distances performs on unnormalized vectors.
So maybe a bug after all(?)
The text was updated successfully, but these errors were encountered:
mcschmitz
changed the title
Normalization in distances is counterintuitive
Default normalization in distances is counterintuitive (or wrong)
Oct 16, 2023
Which of course is correct, however, the default DotProductSimilarity itself normalizes the input vectors.
Hmm, yeah it would make more sense for DotProductSimilarity to not normalize the vectors. That might be a surprising change for anyone using it currently, so I will leave that for v3.0.
Also, the documentation for the LpDistance says...
Thanks for pointing that out, I will update the docs.
Not a real bug, and maybe it's just personal preference, but I feel like the normalization in several distances is counterintuitive.
For example, the documentation for
CosineSimilarity
, saysWhich of course is correct, however, the default
DotProductSimilarity
itself normalizes the input vectors.Also, the documentation for the
LpDistance
saysThis is not true as the Euclidean distances performs on unnormalized vectors.
So maybe a bug after all(?)
The text was updated successfully, but these errors were encountered: