Dmitriy Lyubimov created MAHOUT-1365:
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Summary: 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: Backlog
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 followsing 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.
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