[scikit-learn] Jeff Levesque: custom json encoder
joel.nothman at gmail.com
Mon Feb 5 23:49:11 EST 2018
I think you need to describe what use cases you intend once you've encoded
JSON's pretty generic. You can convert any pickle into JSON, but it'll
still have the security and versioning issues of a pickle. You can convert
to PMML and convert the XML to JSON, but it'd still be limited by what PMML
can represent, and not be deserializable into a sklearn estimator.
Are you archiving the model? Are you hoping to predict from the model? Are
you hoping to continue training the model? Does it need to be
deserializable to a sklearn estimator? To a generic estimator not in the
central sklearn library?
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