Description
We save ML's user-supplied params and default params as one entity in JSON. During loading the saved models, we set all the loaded params into created ML model instances as user-supplied params.
It causes some problems, e.g., if we strictly disallow some params to be set at the same time, a default param can fail the param check because it is treated as user-supplied param after loading.
The loaded default params should not be set as user-supplied params. We should save ML default params separately in JSON.
Attachments
Issue Links
- blocks
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SPARK-23265 Update multi-column error handling logic in QuantileDiscretizer
- Resolved
- is duplicated by
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SPARK-23244 Incorrect handling of default values when deserializing python wrappers of scala transformers
- Resolved
- is related to
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SPARK-23377 Bucketizer with multiple columns persistence bug
- Resolved
- relates to
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SPARK-24058 Default Params in ML should be saved separately: Python API
- Resolved
- links to