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 ...

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.

Abstract 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 ...

BART stands for Bayesian Additive Regression Trees. It is a Bayesian approach to nonparametric function estimation using regression trees.

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 ...