JU, are you refering to this dataset?
http://labrosa.ee.columbia.edu/millionsong/tasteprofile On 18.03.2013 17:47, Sean Owen wrote: > One word of caution, is that there are at least two papers on ALS and they > define lambda differently. I think you are talking about "Collaborative > Filtering for Implicit Feedback Datasets". > > I've been working with some folks who point out that alpha=40 seems to be > too high for most data sets. After running some tests on common data sets, > alpha=1 looks much better. YMMV. > > In the end you have to evaluate these two parameters, and the # of > features, across a range to determine what's best. > > Is this data set not a bunch of audio features? I am not sure it works for > ALS, not naturally at least. > > > On Mon, Mar 18, 2013 at 12:39 PM, Han JU <[email protected]> wrote: > >> Hi, >> >> I'm wondering has someone tried ParallelALS with implicite feedback job on >> million song dataset? Some pointers on alpha and lambda? >> >> In the paper alpha is 40 and lambda is 150, but I don't know what are their >> r values in the matrix. They said is based on time units that users have >> watched the show, so may be it's big. >> >> Many thanks! >> -- >> *JU Han* >> >> UTC - Université de Technologie de Compiègne >> * **GI06 - Fouille de Données et Décisionnel* >> >> +33 0619608888 >> >
