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https://issues.apache.org/jira/browse/SPARK-4907?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14253978#comment-14253978
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Apache Spark commented on SPARK-4907:
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User 'dbtsai' has created a pull request for this issue:
https://github.com/apache/spark/pull/3746
> Inconsistent loss and gradient in LeastSquaresGradient compared with R
> ----------------------------------------------------------------------
>
> Key: SPARK-4907
> URL: https://issues.apache.org/jira/browse/SPARK-4907
> Project: Spark
> Issue Type: Bug
> Components: MLlib
> Reporter: DB Tsai
>
> In most of the academic paper and algorithm implementations, people use L =
> 1/2n ||A weights-y||^2 instead of L = 1/n ||A weights-y||^2 for least-squared
> loss. See Eq. (1) in http://web.stanford.edu/~hastie/Papers/glmnet.pdf
> Since MLlib uses different convention, this will result different residuals
> and all the stats properties will be different from GLMNET package in R. The
> model coefficients will be still the same under this change.
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