Joseph K. Bradley created SPARK-21086:
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Summary: CrossValidator, TrainValidationSplit should preserve all
models after fitting
Key: SPARK-21086
URL: https://issues.apache.org/jira/browse/SPARK-21086
Project: Spark
Issue Type: New Feature
Components: ML
Affects Versions: 2.2.0
Reporter: Joseph K. Bradley
I've heard multiple requests for having CrossValidatorModel and
TrainValidationSplitModel preserve the full list of fitted models. This sounds
very valuable.
One decision should be made before we do this: Should we save and load the
models in ML persistence? That could blow up the size of a saved Pipeline if
the models are large.
* I suggest *not* saving the models by default but allowing saving if
specified. We could specify whether to save the model as an extra Param for
CrossValidatorModelWriter, but we would have to make sure to expose
CrossValidatorModelWriter as a public API and modify the return type of
CrossValidatorModel.write to be CrossValidatorModelWriter (but this will not be
a breaking change).
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