I'm using the ALS algorithm (implicitPrefs = True) in Spark 2.1.0 for collaborative filtering.
I am wondering if it is possible to aggregate the prediction scores. Lets say for a User1 there are the following predictions:
- Item a: 0.4
- Item b: 0.2
- Item c: 0.1
- Item d: 0.5
In my case items belong to several groups. Lets say Item a and b belong to Group1 and Item c and d to Group 2. Can I now aggregate the predictions? For example by summing them up in order to get the predictions:
- Group1: 0.4 + 0.2 = 0.6
- Group2: 0.5 + 0.1 = 0.6
P.S. Fitting the model on Groups is not wanted, because the correlation between groups and items is not constant. Therefore I don't want to refit the model every time the correlation changes. I can't figure out of if the aggregation of predictions is mathematical nonsense or not and I am happy for any help.