This isn't specific to Spark, but there is not a direct relation. An input preference is a count-like value, which is converted into to confidence values via the 1 + alpha*value formula. But the matrix that is factored is the 0/1 matrix mentioned in the paper, and the resulting 'prediction' are elements from the product of the factored matrices. So it's a value that's mostly in [0,1] but not always, and is not a preference or confidence.
On Wed, May 25, 2016 at 11:50 AM, edezhath <ralph.ange...@gmail.com> wrote: > The original paper that the implicit preferences version of ALS is based on, > mentions a "preference" and "confidence" for each user-item pair. But > spark.ml.recommender.ALS only outputs a "prediction". How is this related to > preference and confidence? > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/Preference-and-confidence-in-ALS-implicit-preferences-output-tp27023.html > Sent from the Apache Spark User List mailing list archive at Nabble.com. > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
