Fair enough.
Best wishes,
ilya.
2014-12-03 16:23 GMT+00:00 Gael Varoquaux <gael.varoqu...@normalesup.org>:
> On Wed, Dec 03, 2014 at 04:13:06PM +0000, Илья Патрушев wrote:
> > Sure, I understand the rationale behind the requirement of 1000+ cites
> etc.,
> > and as I mentioned above, I am quite happy to release it via PyPI.
>
> And put it in a scikit-learn-contrib repo? That would be sweet.
>
> > Wang et al. 2008 claim that their approach improves correctness of
> Affinity
> > Propagation clustering (though it increases the running times).
>
> > Correct me if I am wrong, from your reply it looks like you are not
> > persuaded by the paper and do not recommend including the algorithm in
> > sklearn.
>
> Yes. But on the other hand, I do not hold the Truth. I would be very,
> very happy to be proven wrong, and if clearly proven wrong, integrate it
> in scikit-learn.
>
> You know, I have no horses in this race. The algorithms that I develop
> are not part of scikit-learn, and will never be, because of the
> requirements that we have. I just want scikit-learn to be something
> genuinely useful. Partly out of selfishness, because I have a research
> team that is relying on it to do the data analysis.
>
> Gaël
>
>
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--
Ilya Patrushev,
MRC National Institute for Medical Research
The Ridgeway
Mill Hill
London NW7 1AA
UK
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Fax: 0208 906 4477
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