BooST: Boosting Smooth Trees for Partial Effect Estimation in Nonlinear Regressions

10 Aug 2018Yuri FonsecaMarcelo MedeirosGabriel VasconcelosAlvaro Veiga

In this paper, we introduce a new machine learning (ML) model for nonlinear regression called the Boosted Smooth Transition Regression Trees (BooST), which is a combination of boosting algorithms with smooth transition regression trees. The main advantage of the BooST model is the estimation of the derivatives (partial effects) of very general nonlinear models... (read more)

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