thank you very much, i didn't see this tool, i'll definitely try it. Clearly better to have such a specific instrument.
2018-05-10 18:36 GMT+02:00 Pat Ferrel <p...@occamsmachete.com>: > You can if you want but we have external tools for the UR that are much > more flexible. The UR has tuning that can’t really be covered by the built > in API. https://github.com/actionml/ur-analysis-tools They do MAP@k as > well as creating a bunch of other metrics and comparing different types of > input data. They use a running UR to make queries against. > > > From: Marco Goldin <markomar...@gmail.com> <markomar...@gmail.com> > Reply: user@predictionio.apache.org <user@predictionio.apache.org> > <user@predictionio.apache.org> > Date: May 10, 2018 at 7:52:39 AM > To: user@predictionio.apache.org <user@predictionio.apache.org> > <user@predictionio.apache.org> > Subject: UR evaluation > > hi all, i successfully trained a universal recommender but i don't know > how to evaluate the model. > > Is there a recommended way to do that? > I saw that *predictionio-template-recommender* actually has > the Evaluation.scala file which uses the class *PrecisionAtK *for the > metrics. > Should i use this template to implement a similar evaluation for the UR? > > thanks, > Marco Goldin > Horizons Unlimited s.r.l. > >
