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 ...

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.

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 ...

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 ...

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 ...

A key objective of behavioral science research is to better understand how people make decisions in situations where outcomes are unknown or uncertain, which entail a certain degree of risk.

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 ...