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Posted to issues@spark.apache.org by "Yanbo Liang (JIRA)" <ji...@apache.org> on 2016/10/07 08:09:20 UTC

[jira] [Updated] (SPARK-17824) QR solver for WeightedLeastSquares

     [ https://issues.apache.org/jira/browse/SPARK-17824?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Yanbo Liang updated SPARK-17824:
--------------------------------
    Summary: QR solver for WeightedLeastSquares  (was: QR solver for WeightedLeastSquare)

> 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
>
> Cholesky decomposition is unstable (for near-singular and rank deficient matrices), it was often used when matrix A is very large and sparse due to faster calculation. QR decomposition has better numerical properties than Cholesky. Spark MLlib WeightedLeastSquares use Cholesky decomposition to solve normal equation currently, we should also support or move to QR solver for better stability.



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