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 Orange quality/usability, but more a question of another development style/community. That is, for users who're not going to sell their software (which is not permitted by GPL), there is not much difference? Of course, convenience for developers and simplicity means more viable library in a long term. Denis. > Hi Denis, > > I my opinion here are the main reasons why scikit-learn cannot reuse orange: > > - scikit-learn is a scikit (scientific python toolkit): it is meant to > be used by he scipy community and to play by its tacit rules: the > primary data structure is plain old numpy array (or > scipy.sparse.matrix): no machine learning specific class for samples, > features, datasets... > > - scikit-learn has only dependencies on non viral open source licenses > (python, numpy, scipy and joblib all are BSD-like): hence scikit-learn > is BSD-like as well to play fair in this permissive ecosystem (being a > able to copy and paste any function or modules of scikit-learn source > code anywhere else is perfectly OK) > > - scikit-learn focuses on implementing machine learning with as few > framework code as possible and let other framework oriented projects > reuse some of scikit-learn modules if they want to do so: i.e. to > build datamining GUI for instance. > > Other scikit-learn contributors might have their own reasons to > contribute to scikit-learn rather than Orange. > > 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 hg. > ------------------------------------------------------------------------------ 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
