), random forests (RF), gradient boosting machines (GBM) and k-nearest neighbors (k-NN) in the analyze and improve phases of Six …

combining decision trees and gradient boosting is applied to data from a previous study, the results of which were … realized by means of Extreme Gradient Boosting (XGBoost under the R environment). The results indicate that some formerly found …

NWP covariates provide a pool of candidates for the nonlinear terms. A combination of stability selection and gradient … boosting selects influential terms. Markov chain Monte Carlo (MCMC) simulation estimates the final model to provide credible …

regression, random forests, gradient boosting, and neural networks) and two updating methods (moving and extending windows …).Findings – The gradient boosting method yields the greatest accuracy while the robust method provides the least volatile predictions …

NWP covariates provide a pool of candidates for the nonlinear terms. A combination of stability selection and gradient … boosting selects influential terms. Markov chain Monte Carlo (MCMC) simulation estimates the final model to provide credible …