Hello, I would like to use the spark MLlib recommendation filtering library. My goal will be to predict what a user would like to buy based on what he bought before.
I read on the spark documentation that Spark supports implicit feedback. However there is not example for this application. Would implicit feedback works on my business case and how? Can ALS accept multiple parameters. Currently I have : (userId,productId,nbPurchased) I would like to another parameter: (userId,productId,nbPurchased,frenquency) Is it possible with ALS? Thank you for your reply -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Implicit-ALS-with-multiple-features-tp21723.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
