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Right now we are doing log( 1 + (N / n_j)), but wikipedia has log(N / (1 + n_j)) + 1 and scikit-learn does
If smooth_idf=True (the default), the constant “1” is added to the numerator and denominator of the idf as if an extra document was seen containing every term in the collection exactly once, which prevents zero divisions: idf(t) = log [ (1 + n) / (1 + df(t)) ] + 1.
Right now we are doing
log( 1 + (N / n_j))
, but wikipedia haslog(N / (1 + n_j)) + 1
and scikit-learn doesref:
https://en.wikipedia.org/wiki/Tf%E2%80%93idf
https://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.TfidfTransformer.html#sklearn.feature_extraction.text.TfidfTransformer
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