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 you guys started a new library, maybe there is something wrong with Orange? Why do you need to re-implement what has been already done, instead of using that lib as a foundation and concentrate on adding a new cool stuff or improving existing?
I'm really interested. Thank you very much for any comments. Denis. ------------------------------------------------------------------------------ All the data continuously generated in your IT infrastructure contains a definitive record of customers, application performance, security threats, fraudulent activity, and more. Splunk takes this data and makes sense of it. IT sense. And common sense. http://p.sf.net/sfu/splunk-novd2d _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
