Hi Olivier,
Thanks for comments!
So, summarizing, sklearn versus Orange is:
- use plain arrays instead of classes for storing data-sets, features, etc
- use BSD rather than GPL license
- no framework, plain library of methods
If I got it right, seems like creating sklearn was not a question of
On Sat, Dec 3, 2011 at 10:25, Gael Varoquaux
wrote:
> On Sat, Dec 03, 2011 at 12:32:59PM +0100, Olivier Grisel wrote:
>> Alexandre has a new blog post about this with simple python snippet
>> using sklearn GuassianProcess:
>
>> http://atpassos.posterous.com/bayesian-optimization
>
> That's prett
On Sat, Dec 03, 2011 at 12:32:59PM +0100, Olivier Grisel wrote:
> Alexandre has a new blog post about this with simple python snippet
> using sklearn GuassianProcess:
> http://atpassos.posterous.com/bayesian-optimization
That's pretty cool. If Alexandre agrees, this code could definitely serve
2011/12/2 María Helena Mejía Salazar :
> Hi,
>
> I modified a little bit the program of demo dbscan (plot_dbscan.py). I am
> using just distance (no similarities) and I am having bad results. There are
> just 5 points, I changed the eps as the minimum distance between the
> points and the number
Also if you have multiple scikit-learn installation in your system,
you can always check which one is active in python PYTHONPATH with:
python -c "import sklearn; print sklearn.__path__"
--
Olivier
--
All the data con
2011/12/3 Gael Varoquaux :
> On Sat, Nov 19, 2011 at 09:15:43PM -0500, James Bergstra wrote:
>
> thinking about this for quite a while. I am thrilled to know that it
> actually works, and would be _very_ interested about having this in the
> scikit. Let's discuss it at the sprints.
Alexandre has a
On Sat, Dec 3, 2011 at 8:14 PM, Olivier Grisel wrote:
> Also on a more trivial perspective, I like working on github using
> pull-request based reviews as the main inter-developer communication
> medium for code contributions. svn is such a pain once you tasted a
> decentralized tool like git or
2011/12/3 Denis Kochedykov :
> Hi all,
>
> I'm looking for an ML library for Python for our research team. I found
> a quite comprehensive one - Orange - and a relatively new one -
> scikits.learn.
> Orange definitely look good given the number of methods implemented in
> it, maturity and its GUI a
