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https://issues.apache.org/jira/browse/SPARK-17090?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15425913#comment-15425913
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Yanbo Liang commented on SPARK-17090:
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Making aggregation depth configurable is necessary when Linear/Logistic
Regression scaling to high dimension. I vote to expose an expert param to make
it configurable.
> 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.
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