title: Apache Spark ALS Recommendation Rating values higher than range
body: <p>I've ran a little ALS recommender system program as found
  on the <a href="https://spark.apache.org/docs/1.1.1/mllib-collaborative-filtering.html" rel="nofollow noreferrer">Apache Spark website</a> which utilises MLlib. When using a dataset with ratings of 1-5 (I've used the MovieLens dataset) it gives recommendations with predicted ratings of over 5 !</p>
  <p>The highest I've found in my small testing is 7.4.  Obviously, I am either misunderstanding what the code is meant to do, or something has gone awry. I have researched into Latent Factor Recommender Systems and was under the impression that the Spark Mlib ALS implementation was based on <a href="http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4781121" rel="nofollow noreferrer">this one</a>.</p>
  <p>Why would it return ratings higher than what is possible? It makes no sense.</p>
  <p>Have I misunderstood the algorithm or is the program flawed?</p>