On Sun, Dec 04, 2011 at 08:58:13PM +0800, Denis Kochedykov wrote:
> Thanks, all points are quite important for me (for most users, I think).
> Performance problems are surprising, considering Orange is mainly C++.
It's the algorithm that counts, more than the language.
G
Thank you !
On Sun, Dec 4, 2011 at 2:30 PM, Robert Layton wrote:
>
> On 3 December 2011 23:47, Olivier Grisel wrote:
>
>> 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 similarit
On 3 December 2011 23:47, Olivier Grisel wrote:
> 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 th
On 3 December 2011 22:38, Olivier Grisel wrote:
> 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
>
>
> --
2011/12/4 David Warde-Farley :
> On Sun, Dec 04, 2011 at 09:16:56PM +0800, Denis Kochedykov wrote:
>>
>> Hi David,
>>
>> Thanks, very good points. That is
>>
>> 1. C++ rather than Python (in fact this, looks like a plus for me -
>> performance, universality, etc)
>
> I agree from the perspective of
On Sun, Dec 04, 2011 at 09:16:56PM +0800, Denis Kochedykov wrote:
>
> Hi David,
>
> Thanks, very good points. That is
>
> 1. C++ rather than Python (in fact this, looks like a plus for me -
> performance, universality, etc)
I agree from the perspective of universality, but beware of the trap o
Hi David,
Thanks, very good points. That is
1. C++ rather than Python (in fact this, looks like a plus for me -
performance, universality, etc)
2. Complicated and inconvenient classes structure and API in Orange
3. Instability(?)
I think I've heard enough good reasons to use sklearn :)
Asked
Hi Olivier,
> I don't really know Orange but I think it's indeed pretty similar in
> scope to what sklearn provides if you ignore the aforementioned 3 points.
Definitely not ignoring them :) Some points are important for some
users, other important for others. Performance/stability/transparenc
Hi Brian,
Thanks, all points are quite important for me (for most users, I think).
Performance problems are surprising, considering Orange is mainly C++.
Denis.
On 04.12.2011 16:57, [email protected] wrote:
> Hi Denis,
>
> My main motivation is mostly usability. In terms of development though,
On Sun, Dec 04, 2011 at 02:49:30PM +0800, Denis Kochedykov wrote:
> 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
2011/12/4 Denis Kochedykov :
> 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
Hi Denis,
My main motivation is mostly usability. In terms of development though, I've
only really worked on decision trees, so my comments are heavily influenced by
that experience.
Here are the three main reasons why I use scikit-learn:
Simplicity (taking the cue from Olivier). If you've s
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