[scikit-learn] HashingVectorizer slow in version 0.18

[Andreas Mueller]

Please open an issue on the issue tracker:
https://github.com/scikit-learn/scikit-learn/issues

On 10/11/2016 08:19 AM, Gabriel Trautmann wrote:
> Thank you for your response, have Windows 7 Enterprise 64 bit / Intel 
> Xeon E5 2640 CPU, same problem on two similar machines
>
> python-3.5.2-amd64.exe - fresh installation
>
> numpy-1.11.2+mkl-cp35-cp35m-win_amd64.whl  - from Christoph Gohlke
> scipy-0.18.1-cp35-cp35m-win_amd64.whl
> pip install scikit-lean
>
> on the same python instance if I downgrade to version 0.17 is much faster.
>
> pip uninstall scikit-lean
> pip install scikit-lean==0.17
>
> I will open an issue after I test on more machines or if someone else 
> can reproduce the problem.
>
>
>
>
> On Tue, Oct 11, 2016 at 3:02 PM, Olivier Grisel 
> <olivier.grisel at ensta.org <mailto:olivier.grisel at ensta.org>> wrote:
>
>     I cannot reproduce such a degradation on my machine:
>
>     (sklearn-0.17)ogrisel at is146148:~/code/scikit-learn$ python
>     ~/tmp/bench_vectorizer.py
>     scikit-learn 0.17.1. Numpy 1.11.2. Python 3.5.0 x86_64
>     Vectorizing 20newsgroup 11314 documents
>     Vectorization completed in  4.033604383468628  seconds, resulting
>     shape  (11314, 1048576)
>
>     (sklearn-0.18) ogrisel at is146148:~/code/scikit-learn$ python
>     ~/tmp/bench_vectorizer.py
>     scikit-learn 0.18. Numpy 1.11.2. Python 3.5.0 x86_64
>     Vectorizing 20newsgroup 11314 documents
>     Vectorization completed in  4.990509510040283  seconds, resulting
>     shape  (11314, 1048576)
>
>     Which operating system are you using?
>
>     Please feel free to open an issue on the tracker anyway.
>
>     --
>     Olivier
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