What are implicit rankings here? RMSE would not be an appropriate measure for comparing rankings. There are ranking metrics like mean average precision that would be appropriate instead.
On Wed, Sep 14, 2016 at 9:11 PM, Pasquinell Urbani < pasquinell.urb...@exalitica.com> wrote: > It was a typo mistake, both are rmse. > > The frecency distribution of rankings is the following > > [image: Imágenes integradas 2] > > As you can see, I have heavy tail, but the majority of the observations > rely near ranking 5. > > I'm working with implicit rankings (generated by TF-IDF), can this affect > the error? (I'm currently using trainImplicit in ALS, spark 1.6.2) > > Thank you. > > > > 2016-09-14 16:49 GMT-03:00 Sean Owen <so...@cloudera.com>: > >> There is no way to answer this without knowing what your inputs are >> like. If they're on the scale of thousands, that's small (good). If >> they're on the scale of 1-5, that's extremely poor. >> >> What's RMS vs RMSE? >> >> On Wed, Sep 14, 2016 at 8:33 PM, Pasquinell Urbani >> <pasquinell.urb...@exalitica.com> wrote: >> > Hi Community >> > >> > I'm performing an ALS for retail product recommendation. Right now I'm >> > reaching rms_test = 2.3 and rmse_test = 32.5. Is this too much in your >> > experience? Does the transformation of the ranking values important for >> > having good errors? >> > >> > Thank you all. >> > >> > Pasquinell Urbani >> > >
