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. The Bayesian ...
This is a preview. Log in through your library . Abstract Bayesian Additive Regression Trees (BART) is a flexible machine learning algorithm capable of capturing nonlinearities between an outcome and ...
Minimax L₂ risks for high-dimensional nonparametric regression are derived under two sparsity assumptions: (1) the true regression surface is a sparse function that depends only on d = O(log n) ...
The Bayesian Additive Regression Trees (BART) model appears to accurately predict the progression and severity of generalised anxiety disorder (GAD) based on pre-treatment information, potentially ...
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