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dmlc / xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
https://xgboost.readthedocs.io/en/stable/
Apache License 2.0
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Expose model shape to Python interface. #7819

Open trivialfis opened 2 years ago

trivialfis commented 2 years ago

https://github.com/ray-project/xgboost_ray/pull/212#discussion_r853154092

hristog commented 1 year ago

@trivialfis, what would be a good naming convention and output format for the newly-exposed information?

I've had a look at the linked comment but I'm not entirely sure what the expected degree of exposure and the actual format might be (in accordance to established XGBoost conventions).

trivialfis commented 1 year ago

We haven't decided yet. At the moment, save_config is the best way to do that.