Hi,
I realized that TfidfVectorizer returns a CSR matrix, which supports array
indexing, while CountVectorizer returns a COO matrix, which doesn't. I
always liked the clean and interchangeable nature of sklearn, so I
wondered, whether it would break other pieces if we would return a CSR
matrix in CountVectorizer as well. Or is performance a concern here?
CountVectorizer's fit_transform:
https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/feature_extraction/text.py#L530
TfidfVectorizer's fit_transform:
https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/feature_extraction/text.py#L942
Thanks,
wr
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