Hi Sean, Isn't boolean preferences is supported in the context of memory-based recommendation algorithms in Mahout? Are there matrix factorization algorithms in Mahout which can work with this kind of data (that is, the kind of data which consists of users and the movies they have seen).
On Mon, May 6, 2013 at 10:34 PM, Sean Owen <[email protected]> wrote: > Yes, it goes by the name 'boolean prefs' in the project since target > variables don't have values -- they just exist or don't. > So, yes it's certainly supported but the question here is how to > evaluate the output. > > On Mon, May 6, 2013 at 8:29 PM, Tevfik Aytekin <[email protected]> > wrote: >> 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? >>>> >>>> >>>>
