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https://issues.apache.org/jira/browse/SPARK-10668?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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DB Tsai resolved SPARK-10668.
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Resolution: Fixed
Fix Version/s: 1.6.0
Issue resolved by pull request 8884
[https://github.com/apache/spark/pull/8884]
> Use WeightedLeastSquares in LinearRegression with L2 regularization if the
> number of features is small
> ------------------------------------------------------------------------------------------------------
>
> Key: SPARK-10668
> URL: https://issues.apache.org/jira/browse/SPARK-10668
> Project: Spark
> Issue Type: New Feature
> Components: ML
> Reporter: Xiangrui Meng
> Assignee: Kai Sasaki
> Priority: Critical
> Fix For: 1.6.0
>
>
> If the number of features is small (<=4096) and the regularization is L2, we
> should use WeightedLeastSquares to solve the problem rather than L-BFGS. The
> former requires only one pass to the data.
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