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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2015/08/05 01:19:04 UTC

[jira] [Resolved] (SPARK-7210) Test matrix decompositions for speed vs. numerical stability for Gaussians

     [ https://issues.apache.org/jira/browse/SPARK-7210?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joseph K. Bradley resolved SPARK-7210.
--------------------------------------
    Resolution: Done

> Test matrix decompositions for speed vs. numerical stability for Gaussians
> --------------------------------------------------------------------------
>
>                 Key: SPARK-7210
>                 URL: https://issues.apache.org/jira/browse/SPARK-7210
>             Project: Spark
>          Issue Type: Improvement
>          Components: MLlib
>            Reporter: Joseph K. Bradley
>            Priority: Minor
>
> We currently use SVD for inverting the Gaussian's covariance matrix and computing the determinant.  SVD is numerically stable but slow.  We could experiment with Cholesky, etc. to figure out a better option, or a better option for certain settings.



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