Here is a note from the documentation: Note: contrary to other cross-validation strategies, random splits do not guarantee that all folds will be different, although this is still very likely for sizeable datasets.
So I guess it is not possible to enforce all sets to be different. Thank you -----Original Message----- From: Gael Varoquaux [mailto:[email protected]] Sent: Thursday, August 14, 2014 2:01 PM To: [email protected] Subject: Re: [Scikit-learn-general] split function with non repeated sets > With k-fold you can shuffle the data, but let’s say you want to run > k-fold partition multiple times. Can you avoid repetition of the same > subset of samples? We call that 'shuffle split' http://scikit-learn.org/stable/modules/generated/sklearn.cross_validation.ShuffleSplit.html Examples of use: http://scikit-learn.org/stable/modules/cross_validation.html Gaël ------------------------------------------------------------------------------ _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general ------------------------------------------------------------------------------ _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
