Update Python API doc (#3619)
* Add XGBRanker to Python API doc * Show inherited members of XGBRegressor in API doc, since XGBRegressor uses default methods from XGBModel * Add table of contents to Python API doc * Skip JVM doc download if not available * Show inherited members for XGBRegressor and XGBRanker * Expose XGBRanker to Python XGBoost module directory * Add docstring to XGBRegressor.predict() and XGBRanker.predict() * Fix rendering errors in Python docstrings * Fix lint
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@@ -274,7 +274,7 @@ and then loading the model in another session:
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With regards to ML pipeline save and load, please refer the next section.
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Interact with Other Bindings of XGBoost
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After we train a model with XGBoost4j-Spark on massive dataset, sometimes we want to do model serving in single machine or integrate it with other single node libraries for further processing. XGBoost4j-Spark supports export model to local by:
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.. code-block:: scala
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