Github user vruusmann commented on the pull request:
https://github.com/apache/spark/pull/9207#issuecomment-215404038
I've been experimenting with a standalone Spark ML Pipelines to PMML
converter in recent days. The goal is to cover basic transformers (eg.
`StringIndexer`, `OneHotEncoder`, `VectorAssembler`) and most popular
tree-based models (eg. decision trees, random forest and GBMs).
The prototype should be available early next week. So far I've completely
ignored the existing Spark's serialization infrastructure, including the
`MLWritable` and `PMMLExportable` traits.
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