Hi people, So far we have had no policy of backward compatibility in sklearn/utils. However, some of the utilities there are very useful for packages that want to extend scikit-learn's functionality, such as seqlearn, sklearn-theano, nilearn...
The latest set of changes in the validation utilities have brought in a great cleanup of these utilities. However as a result it has also broken nilearn. This isn't a big deal, as nilearn isn't released, however I think that we need to think about our backward compatibility strategy in sklearn/utils. Here is my proposal: we need to apply standard deprecation cycle for everything in sklearn/utils/__init__.py and all the rest is off limits. What do people think? Gaël ------------------------------------------------------------------------------ Want excitement? Manually upgrade your production database. When you want reliability, choose Perforce Perforce version control. Predictably reliable. http://pubads.g.doubleclick.net/gampad/clk?id=157508191&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
