Hi, According to the paper on which MLlib's ALS is based, the model should take all user-item preferences as an input, including those which are not related to any input observation (zero preference).
My question is: With all positive observations in hand (similar to explicit feedback data set), should I generate all negative observations in order to make implicit ALS work with the complete data set (pos union neg) ? Actually, we test on some data set like: | user | item | nbPurchase | nbPurchase is non zero, so we have no negative observations. What we did is generating all possible user-item with zero nbPurchase to have all possible user-item pair, but this operation takes some time and storage. I just want to make sure whether we have to do that with MLlib's ALS ? or it has already done that ? In that case, I could simply pass only the positive observation as the explicit ALS does. Hao. -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/implicit-ALS-dataSet-tp7067.html Sent from the Apache Spark User List mailing list archive at Nabble.com.
