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Debasish Das commented on SPARK-4231: ------------------------------------- [~srowen] I added batch predict APIs for user and product recommendation in the PR (both batch and mini-batch APIs that takes a per user topK products) For the MAP calculation code I still have kept it in examples.MovieLensALS in this PR but I feel it should be part of MatrixFactorizationModel as well where client can send a RDD of userID and list of products they don't want to be recommended in the topK...I will add this API in MatrixFactorizationModel if it makes sense... > Add RankingMetrics to examples.MovieLensALS > ------------------------------------------- > > Key: SPARK-4231 > URL: https://issues.apache.org/jira/browse/SPARK-4231 > Project: Spark > Issue Type: Improvement > Components: Examples > Affects Versions: 1.2.0 > Reporter: Debasish Das > Fix For: 1.2.0 > > Original Estimate: 24h > Remaining Estimate: 24h > > examples.MovieLensALS computes RMSE for movielens dataset but after addition > of RankingMetrics and enhancements to ALS, it is critical to look at not only > the RMSE but also measures like prec@k and MAP. > In this JIRA we added RMSE and MAP computation for examples.MovieLensALS and > also added a flag that takes an input whether user/product recommendation is > being validated. > -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org