[jira] [Resolved] (SPARK-20029) LiR supports bound constrained optimization

["Hyukjin Kwon (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-20029?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-20029.
----------------------------------
    Resolution: Incomplete

> LiR supports bound constrained optimization
> -------------------------------------------
>
>                 Key: SPARK-20029
>                 URL: https://issues.apache.org/jira/browse/SPARK-20029
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>    Affects Versions: 2.2.0
>            Reporter: Yanbo Liang
>            Priority: Major
>              Labels: bulk-closed
>
> MLlib {{LinearRegression}} should support bound constrained optimization. Users can add bound constraints to coefficients to make the solver produce  solution in the specified range.
> In Spark MLlib, we call breeze L-BFGS-B as the solver for bound constrained optimization. And we only support L2 regularization currently.
> * https://neos-guide.org/content/bound-constrained-optimization
> * http://users.iems.northwestern.edu/~nocedal/lbfgsb.html



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