Fix dask doc. [skip ci] (#6108)
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@ -200,11 +200,4 @@ addressed yet:
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- Label encoding for the ``DaskXGBClassifier`` classifier may not be supported. So users need
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to encode their training labels into discrete values first.
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- Ranking is not yet supported.
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- Empty worker is not well supported by classifier. If the training hangs for classifier
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with a warning about empty DMatrix, please consider balancing your data first. But
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regressor works fine with empty DMatrix.
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- Callback functions are not tested.
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- Only ``GridSearchCV`` from Scikit-Learn is supported. Meaning that we can distribute data
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among workers but have to train one model at a time. If you want to scale up grid searching with
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model parallelism with `Dask-ML <https://ml.dask.org/>`_, please consider using XGBoost's non-dask
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Scikit-Learn interface, for example ``xgboost.XGBRegressor``, for now.
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