Save Scikit-Learn attributes into learner attributes. (#5245)
* Remove the recommendation for pickle. * Save skl attributes in booster.attr * Test loading scikit-learn model with native booster.
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@@ -85,6 +85,14 @@ again after the model is loaded. If the customized function is useful, please co
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making a PR for implementing it inside XGBoost, this way we can have your functions
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working with different language bindings.
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Loading pickled file from different version of XGBoost
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As noted, pickled model is neither portable nor stable, but in some cases the pickled
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models are valuable. One way to restore it in the future is to load it back with that
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specific version of Python and XGBoost, export the model by calling `save_model`.
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Saving and Loading the internal parameters configuration
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