XGBoost (eXtreme Gradient Boosting) is a scalable, end-to-end, tree-boosting system that has produced state-of-the-art results on many machine learning challenges.

A gradient boosting machine model performed best among five machine learning models tested for predicting delirium, according to findings recently published in JAMA Network Open. “Existing ...

Estimation is conducted by a componentwise gradient boosting algorithm, which scales well to large data sets and complex models. Applied Statistics of the Journal of the Royal Statistical Society was ...

The best-performing model for the classification of 1-year OS was the extreme gradient boosting algorithm, with AUC and F1-score values equal to 0.805 and 0.802, respectively.

Here we propose an alternative method based on conjugate gradients. The key, as we show, is that the EM step can be viewed (approximately at least) as a generalized gradient, making it natural to ...