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https://issues.apache.org/jira/browse/SPARK-17824?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-17824.
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Resolution: Incomplete
> QR solver for WeightedLeastSquares
> ----------------------------------
>
> Key: SPARK-17824
> URL: https://issues.apache.org/jira/browse/SPARK-17824
> Project: Spark
> Issue Type: New Feature
> Components: ML
> Reporter: Yanbo Liang
> Assignee: Yanbo Liang
> Priority: Major
> Labels: bulk-closed
>
> Cholesky decomposition is unstable (for near-singular and rank deficient
> matrices) and only works on positive definite matrices which can not be
> guaranteed in all cases, it was often used when matrix A is very large and
> sparse due to faster calculation. QR decomposition has better numerical
> properties than Cholesky and can works on matrices which are not positive
> definite. Spark MLlib {{WeightedLeastSquares}} use Cholesky decomposition to
> solve normal equation currently, we should also support or move to QR solver
> for better stability. I'm preparing to send a PR.
> cc [~dbtsai] [~sethah]
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