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Apache Spark commented on SPARK-19357:
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User 'BryanCutler' has created a pull request for this issue:
https://github.com/apache/spark/pull/16774
> Parallel Model Evaluation for ML Tuning
> ---------------------------------------
>
> Key: SPARK-19357
> URL: https://issues.apache.org/jira/browse/SPARK-19357
> Project: Spark
> Issue Type: Sub-task
> Components: ML
> Reporter: Bryan Cutler
>
> This is a first step of the parent task of Optimizations for ML Pipeline Tuning to perform
model evaluation in parallel. A simple approach is to naively evaluate with a possible parameter
to control the level of parallelism. There are some concerns with this:
> * excessive caching of datasets
> * what to set as the default value for level of parallelism. 1 will evaluate all models
in serial, as is done currently. Higher values could lead to excessive caching.
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