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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2015/04/28 02:47:06 UTC
[jira] [Commented] (SPARK-6346) Use faster converging optimization
method in MLlib
[ https://issues.apache.org/jira/browse/SPARK-6346?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14516069#comment-14516069 ]
Joseph K. Bradley commented on SPARK-6346:
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[~rezazadeh] I just updated the target version, but let me know if you had other plans.
> Use faster converging optimization method in MLlib
> --------------------------------------------------
>
> Key: SPARK-6346
> URL: https://issues.apache.org/jira/browse/SPARK-6346
> Project: Spark
> Issue Type: Improvement
> Components: ML, MLlib
> Reporter: Reza Zadeh
>
> According to experiments in SPARK-1503, the LBFGS algorithm converges much faster than our current proximal gradient, which is used throughout MLlib. This ticket is to track replacing slower-converging algorithms, with faster components e.g. LBFGS
> This needs unification of the Optimization interface. For example, the LBFGS implementation should not know about RDDs.
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