Thanks Pat. The error was on my side. All good now. Cheers! On Wed, Jun 21, 2017 at 3:08 PM Pat Ferrel <[email protected]> wrote:
> If all recs come back score 0 then they are from the most popular items > only, not from the Collaborative Filtering algorithm. > > If you truly mean “all” then you have a problem in config or nearly 0 > data. Don’t mess with tuning until you solve this. > > > On Jun 21, 2017, at 2:27 PM, Daniel Gabrieli <[email protected]> > wrote: > > Hi, > > Question about the Universal Recommendation Engine (UR). > > The challenge I am experiencing right now is that all my recommendations > come back with a score of 0 (and are the same recommendations for all > users). > > After training the engine, is there a way to get the metrics about the > trained model? For example, which (if any) indicators have a meaningful > impact on the recommendation? > > I would like to tune the parameters maxCorrelatorsPerItem and minLLR but I > am not sure how to figure out how the default parameters differ from the > trained models results. For example, what is the LLR for the indicators in > the trained model currently? How many correlators are currently considered > significant? > > > Thanks! > > > >
