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Joseph K. Bradley resolved SPARK-5972. -------------------------------------- Resolution: Fixed Fix Version/s: 1.4.0 Issue resolved by pull request 5330 [https://github.com/apache/spark/pull/5330] > Cache residuals for GradientBoostedTrees during training > -------------------------------------------------------- > > Key: SPARK-5972 > URL: https://issues.apache.org/jira/browse/SPARK-5972 > Project: Spark > Issue Type: Improvement > Components: MLlib > Affects Versions: 1.3.0 > Reporter: Joseph K. Bradley > Assignee: Manoj Kumar > Priority: Minor > Fix For: 1.4.0 > > > In gradient boosting, the current model's prediction is re-computed for each > training instance on every iteration. The current residual (cumulative > prediction of previously trained trees in the ensemble) should be cached. > That could reduce both computation (only computing the prediction of the most > recently trained tree) and communication (only sending the most recently > trained tree to the workers). -- 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