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, bdho...@gmail.com wrote:
> Hi Denis,
>
> My main motivation is mostly usability. In terms of development though,
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
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 as a bonus.
But I'm a bit confused - if
