This problem is called one-class classification problem. In the domain of collaborative filtering it is called one-class collaborative filtering (since what you have are only positive preferences). You may search the web with these key words to find papers providing solutions. I'm not sure whether Mahout has algorithms for one-class collaborative filtering.
On Mon, May 6, 2013 at 1:42 PM, Sean Owen <[email protected]> wrote: > ALS-WR weights the error on each term differently, so the average > error doesn't really have meaning here, even if you are comparing the > difference with "1". I think you will need to fall back to mean > average precision or something. > > On Mon, May 6, 2013 at 11:24 AM, William <[email protected]> wrote: >> Sean Owen <srowen <at> gmail.com> writes: >> >>> >>> If you have no ratings, how are you using RMSE? this typically >>> measures error in reconstructing ratings. >>> I think you are probably measuring something meaningless. >>> >> >> >> I suppose the rate of seen movies are 1. Is it right? >> If I use Collaborative Filtering with ALS-WR to get some recommendations, I >> must have a real rating-matrix? >> >> >>
