[ https://issues.apache.org/jira/browse/SPARK-10668?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
DB Tsai resolved SPARK-10668. ----------------------------- Resolution: Fixed Fix Version/s: 1.6.0 Issue resolved by pull request 8884 [https://github.com/apache/spark/pull/8884] > Use WeightedLeastSquares in LinearRegression with L2 regularization if the > number of features is small > ------------------------------------------------------------------------------------------------------ > > Key: SPARK-10668 > URL: https://issues.apache.org/jira/browse/SPARK-10668 > Project: Spark > Issue Type: New Feature > Components: ML > Reporter: Xiangrui Meng > Assignee: Kai Sasaki > Priority: Critical > Fix For: 1.6.0 > > > If the number of features is small (<=4096) and the regularization is L2, we > should use WeightedLeastSquares to solve the problem rather than L-BFGS. The > former requires only one pass to the data. -- 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