Abstract: In order to improve the accuracy of precipitation forecasting with the linear regression of traditional statistical model and the nonlinear regression of Neural Network (NN) model, ...

Bayesian Additive Regression Trees (BART) is a nonparametric ensemble method that models complex relationships by summing a collection of decision trees, each operating as a weak learner.

Bayesian Additive Regression Trees (BART) is an ensemble Bayesian sum-of-trees model and has shown its promising applicability on either simulated data or real data sets. However, it suffers the same ...

BART (Bayesian Additive Regression Tree) is an ensemble technique based on the Bayes theorem which is used to calculate the posterior probability.Fitting and inference by this model are accomplished ...

In order to improve the accuracy of precipitation forecasting with the linear regression of traditional statistical model and the nonlinear regression of Neural Network (NN) model, especially in ...