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xgboost/demo/guide-python
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Jiaming Yuan 58a6723eb1
Initial support for multioutput regression. (#7514) 
* Add num target model parameter, which is configured from input labels.
* Change elementwise metric and indexing for weights.
* Add demo.
* Add tests.
2021-12-18 09:28:38 +08:00
..
basic_walkthrough.py
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boost_from_prediction.py
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callbacks.py
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cat_in_the_dat.py
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categorical.py
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continuation.py
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cross_validation.py
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custom_rmsle.py
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custom_softmax.py
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evals_result.py
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external_memory.py
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feature_weights.py
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gamma_regression.py
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generalized_linear_model.py
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multioutput_regression.py
Initial support for multioutput regression. (#7514)
2021-12-18 09:28:38 +08:00
predict_first_ntree.py
Modernize XGBoost Python document. (#7468)
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predict_leaf_indices.py
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quantile_data_iterator.py
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README.rst
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sklearn_evals_result.py
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sklearn_examples.py
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sklearn_parallel.py
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update_process.py
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2021-11-23 23:24:52 +08:00

README.rst 

XGBoost Python Feature Walkthrough
==================================


This is a collection of examples for using the XGBoost Python package.