XGBoost stands for eXtreme Gradient Boosting, an open source project that is not part of scikit-learn, though recently it has been expanded by a scikit-Learn wrapper interface that renders using models based on XGBoost more integrated into your data pipeline (xgboost.readthedocs.io/en/latest/python/python_api.html#module-xgboost.sklearn).

The XGBoost source code is available on GitHub, at github.com/dmlc/XGBoost; its documentation and some tutorials can be found at xgboost.readthedocs.io/en/latest.

The XGBoost algorithm has gained momentum and popularity in data-science competitions such as Kaggle (www.kaggle.com) and the KDD-cup 2015. As the authors (Tianqui Chen, Tong He, Carlos Guestrin) report on papers on the algorithm, among ...

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