You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Xiangrui Meng (JIRA)" <ji...@apache.org> on 2015/08/05 20:13:04 UTC
[jira] [Commented] (SPARK-7008) An implementation of Factorization
Machine (LibFM)
[ https://issues.apache.org/jira/browse/SPARK-7008?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14658621#comment-14658621 ]
Xiangrui Meng commented on SPARK-7008:
--------------------------------------
I left the JIRA open but removed the target version. I like the algorithm, but I think we want to hear more success stories of FM before we add it to MLlib.
> An implementation of Factorization Machine (LibFM)
> --------------------------------------------------
>
> Key: SPARK-7008
> URL: https://issues.apache.org/jira/browse/SPARK-7008
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Reporter: zhengruifeng
> Labels: features
> Attachments: FM_CR.xlsx, FM_convergence_rate.xlsx, QQ20150421-1.png, QQ20150421-2.png
>
>
> An implementation of Factorization Machines based on Scala and Spark MLlib.
> FM is a kind of machine learning algorithm for multi-linear regression, and is widely used for recommendation.
> FM works well in recent years' recommendation competitions.
> Ref:
> http://libfm.org/
> http://doi.acm.org/10.1145/2168752.2168771
> http://www.inf.uni-konstanz.de/~rendle/pdf/Rendle2010FM.pdf
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org