Hi all,
One component of a good roadmap would be to make sure we emphasize good
implementations of fundamental ML algorithms. One area I'd like to work
on is density estimation: KDE in particular is an important component of
a wide variety of algorithms, and there is not (to my knowledge) a good
flexible & scalable KDE implementation currently in the scipy universe.
I think we're well-poised to offer that, but it would require an
improved ball tree/kd tree implementation. I have some good ideas about
how to do this, but need to find the time to make it happen.
If there are any other fundamental algorithms that sklearn is currently
weak in, we should keep those in mind as well.
Jake
On 01/10/2013 03:29 PM, Robert Layton wrote:
On 11 January 2013 10:21, Lars Buitinck <l.j.buiti...@uva.nl
<mailto:l.j.buiti...@uva.nl>> wrote:
2013/1/10 Andreas Mueller <amuel...@ais.uni-bonn.de
<mailto:amuel...@ais.uni-bonn.de>>:
> I wanted to ask: should we try to make plans? We get a lot of
PRs and
> have more and more contributors and I think it might be nice
> if we had some form of road map to give everything a bit more
direction.
>
> I know that people mostly contribute algorithms they are using
in research,
> and that is great, because that makes for high-quality code.
> I am not sure, though, for how long the "hey look, I coded this cool
> estimator which I used in my latest paper" strategy is feasible.
What we could do is determine a focus for the next release other than
"add more features", like:
* implement Python 3 support
* fix outstanding API issues, like sparse matrix support for some
estimators.
That would be a step towards a 1.0.
--
Lars Buitinck
Scientific programmer, ILPS
University of Amsterdam
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I would say to not worry about the addition of algorithms, and have
1.0 as being a API/python3/sparse release as Lars said.
I don't think that holding off a big release because it doesn't
contain algorithm X is a good idea, as there are plenty of algorithms
we don't have yet, even important ones (depending on your definition
of important).
- Robert
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