[ https://issues.apache.org/jira/browse/SPARK-17090?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
DB Tsai resolved SPARK-17090. ----------------------------- Resolution: Fixed Fix Version/s: 2.1.0 Issue resolved by pull request 14717 [https://github.com/apache/spark/pull/14717] > Make tree aggregation level in linear/logistic regression configurable > ---------------------------------------------------------------------- > > Key: SPARK-17090 > URL: https://issues.apache.org/jira/browse/SPARK-17090 > Project: Spark > Issue Type: Sub-task > Components: ML > Reporter: Seth Hendrickson > Priority: Minor > Fix For: 2.1.0 > > > Linear/logistic regression use treeAggregate with default aggregation depth > for collecting coefficient gradient updates to the driver. For high > dimensional problems, this can case OOM error on the driver. We should make > it configurable, perhaps via an expert param, so that users can avoid this > problem if their data has many features. -- 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