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 ...
Causal Machine Learning (CML) unites ML techniques with CI in order to take advantage of both approaches’ strengths. CML ...
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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