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 ...

The BO-GBRT model accurately predicts compressive strength in self-compacting concrete with recycled aggregates, improving upon traditional testing methods.

We used a much more sophisticated version of these decision trees called the extreme gradient boosting algorithm, or XG boost algorithm, to derive hundreds of trees from which we tried to identify ...

Extreme Gradient Boosting (XGBoost) provided the best performance in each paper in which it was tested. Numerous heterogeneities exist, including definition of “injury”, granularity of data and scope ...

SIAM Journal on Numerical Analysis, Vol. 15, No. 6 (Dec., 1978), pp. 1247-1257 (11 pages) This paper studies the convergence of a conjugate gradient algorithm proposed in a recent paper by Shanno. It ...