title: Aggregation of predictions from ALS Model - SPARK Collaborative filtering
body: <p>I'm using the ALS algorithm (implicitPrefs = True) in Spark 2.1.0 for collaborative filtering.</p>
  
  <p>I am wondering if it is possible to aggregate the prediction scores. Lets say for a User1 there are the following predictions:</p>
  
  <ul>
  <li>Item a: 0.4 </li>
  <li>Item b: 0.2</li>
  <li>Item c: 0.1</li>
  <li>Item d: 0.5</li>
  </ul>
  
  <p>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:</p>
  
  <ul>
  <li>Group1: 0.4 + 0.2 = 0.6</li>
  <li>Group2: 0.5 + 0.1 = 0.6</li>
  </ul>
  
  <p>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. </p>