[ https://issues.apache.org/jira/browse/MAHOUT-1365?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Dmitriy Lyubimov updated MAHOUT-1365: ------------------------------------- Status: Patch Available (was: Open) > Weighted ALS-WR iterator for Spark > ---------------------------------- > > Key: MAHOUT-1365 > URL: https://issues.apache.org/jira/browse/MAHOUT-1365 > Project: Mahout > Issue Type: Task > Reporter: Dmitriy Lyubimov > Assignee: Dmitriy Lyubimov > Fix For: 1.0 > > Attachments: distributed-als-with-confidence.pdf > > > Given preference P and confidence C distributed sparse matrices, compute > ALS-WR solution for implicit feedback (Spark Bagel version). > Following Hu-Koren-Volynsky method (stripping off any concrete methodology to > build C matrix), with parameterized test for convergence. > The computational scheme is following ALS-WR method (which should be slightly > more efficient for sparser inputs). > The best performance will be achieved if non-sparse anomalies prefilitered > (eliminated) (such as an anomalously active user which doesn't represent > typical user anyway). > the work is going here > https://github.com/dlyubimov/mahout-commits/tree/dev-0.9.x-scala. I am > porting away our (A1) implementation so there are a few issues associated > with that. -- This message was sent by Atlassian JIRA (v6.2#6252)