[ https://issues.apache.org/jira/browse/SPARK-2768?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Xiangrui Meng updated SPARK-2768: --------------------------------- Assignee: Sean Owen > Add product, user recommend method to MatrixFactorizationModel > -------------------------------------------------------------- > > Key: SPARK-2768 > URL: https://issues.apache.org/jira/browse/SPARK-2768 > Project: Spark > Issue Type: Improvement > Components: MLlib > Affects Versions: 1.0.1 > Reporter: Sean Owen > Assignee: Sean Owen > Priority: Minor > Fix For: 1.1.0 > > > Right now, MatrixFactorizationModel can only predict a score for one or more > (user,product) tuples. As a comment in the file notes, it would be more > useful to expose a recommend method, that computes top N scoring products for > a user (or vice versa -- users for a product). -- This message was sent by Atlassian JIRA (v6.2#6252)