If you're suggesting that you hold out only high-rated items, and then sample them, then that's what is done already in the code, except without the sampling. The sampling doesn't buy anything that I can see.
If you're suggesting holding out a random subset and then throwing away the held-out items with low rating, then it's also the same idea, except you're randomly throwing away some lower-rated data from both test and train. I don't see what that helps either. On Sat, Feb 16, 2013 at 9:41 PM, Tevfik Aytekin <tevfik.ayte...@gmail.com>wrote: > What I mean is you can choose ratings randomly and try to recommend > the ones above the threshold > >
