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DB Tsai commented on SPARK-17090: --------------------------------- We could make it default to 0 which automatically figure out the best aggregation depth based on the dimensions of features, and the number of partition. Before that, we can make default 0 as 2 which is the current behavior. > 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: Improvement > Components: ML > Reporter: Seth Hendrickson > Priority: Minor > > 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