This should follow whatever implementation is chosen for Pipeline (since these are all meta-algorithms).
Note this will also require persistence for Evaluators. Hopefully that can leverage the Java implementations; there is not a real need to make Python Evaluators be MLWritable, as far as I can tell.
- is blocked by
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SPARK-11893 Model export/import for spark.ml: TrainValidationSplit
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- Resolved
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SPARK-13951 PySpark ml.pipeline support export/import - nested Piplines
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- Resolved
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- requires
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SPARK-15402 PySpark ml.evaluation should support save/load
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- Resolved
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- links to