8000 TfidfVectorizer insists on np.float64 · Issue #6468 · scikit-learn/scikit-learn · GitHub
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TfidfVectorizer insists on np.float64 #6468

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isacarnekvist opened this issue Feb 29, 2016 · 2 comments
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TfidfVectorizer insists on np.float64 #6468

isacarnekvist opened this issue Feb 29, 2016 · 2 comments

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@isacarnekvist
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I tried fixing it but it ended up in an error on line 1288 in sklearn/preprocessing/data.py in normalize() because the function inplace_csr_row_normalize_l2(X) didn't seem to be able to handle float32
@ssaeger
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ssaeger commented Feb 29, 2016

inplace_csr_row_normalize_l2 is implemented in cython and can only handle double (np.float64) at the moment. To handle float32 we need to use fused types of cython, which is not implemented yet.

@rth rth mentioned this issue Aug 31, 2017
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@rth
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rth commented Aug 31, 2017

This issue should have been fixed in #6785 with the corresponding update available in the newly released 0.19 version.

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@rth @ssaeger @isacarnekvist
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