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Posted to issues@spark.apache.org by "Soila Kavulya (JIRA)" <ji...@apache.org> on 2015/10/28 20:52:27 UTC
[jira] [Commented] (SPARK-9837) Provide R-like summary statistics
for GLMs via iteratively reweighted least squares
[ https://issues.apache.org/jira/browse/SPARK-9837?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14979123#comment-14979123 ]
Soila Kavulya commented on SPARK-9837:
--------------------------------------
We have an implementation of R-like summary statistics for logistic regression in Spark which generates the Hessian matrix and computes summary statistics. We would to generalize it for glms and contribute it back to Spark.
> Provide R-like summary statistics for GLMs via iteratively reweighted least squares
> -----------------------------------------------------------------------------------
>
> Key: SPARK-9837
> URL: https://issues.apache.org/jira/browse/SPARK-9837
> Project: Spark
> Issue Type: Sub-task
> Components: ML, MLlib
> Reporter: Xiangrui Meng
>
> This is similar to SPARK-9836 but for GLMs other than ordinary least squares.
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