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https://issues.apache.org/jira/browse/SPARK-18253?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon updated SPARK-18253:
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Labels: bulk-closed (was: )
> ML Instrumentation logging requires too much manual implementation
> ------------------------------------------------------------------
>
> Key: SPARK-18253
> URL: https://issues.apache.org/jira/browse/SPARK-18253
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Reporter: Seth Hendrickson
> Priority: Minor
> Labels: bulk-closed
>
> [SPARK-14567|https://issues.apache.org/jira/browse/SPARK-14567] introduced an
> {{Instrumentation}} class for standardized logging of ML training sessions.
> Right now, we manually log individual params for each algorithm, partly
> because we don't want to log all params since some params can be huge in
> size, and we could flood the logs. We should find a more sustainable way of
> logging params in ML algos. The current approach does not seem sustainable.
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