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 <[email protected]>: > 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 > <[email protected]> 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 >
