Overview

The XGBoost library is installed in EarthAI Notebook.

The following excerpt is from XGBoost's documentation:

XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework. XGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way. The same code runs on major distributed environment (Hadoop, SGE, MPI) and can solve problems beyond billions of examples.

References

Learn more at the XGBoost Documentation Page.

Other References:

• GitHub Repo of XGBoost Examples

There are some more formal papers on XGBoost that are worth a read for more background on the library:

• Higgs Boson Discovery with Boosted Trees, 2014.
• XGBoost: A Scalable Tree Boosting System, 2016.

Video of talk by the creator of XGBoost: