[ https://issues.apache.org/jira/browse/SPARK-4907?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Xiangrui Meng resolved SPARK-4907. ---------------------------------- Resolution: Fixed Fix Version/s: 1.3.0 Issue resolved by pull request 3746 [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 > Fix For: 1.3.0 > > > 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. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org