GitHub user iyounus opened a pull request: https://github.com/apache/spark/pull/10274
[SPARK-12230][ML] WeightedLeastSquares.fit() should handle division by zero properly if standard deviation of target variable is zero. This fixes the behavior of WeightedLeastSquars.fit() when the standard deviation of the target variable is zero. If the fitIntercept is true, there is no need to train. You can merge this pull request into a Git repository by running: $ git pull https://github.com/iyounus/spark SPARK-12230_bug_fix_in_weighted_least_squares Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/10274.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #10274 ---- commit 4c549f99bcfd7fdd826a38e944799bc9fb2b9508 Author: Imran Younus <iyou...@us.ibm.com> Date: 2015-12-12T03:11:41Z fixing fit in weighted least sqaures when std of lable is zero. ---- --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org