BART: Bayesian Additive Regression Trees
ditive Regression Trees) which uses a sum of trees to model or approximate f(x) = E(Y j x). The essential idea is to elaborate the sum-of-trees model (2) by imposing a prior that regularizes the flt by keeping the individual tree efiects small. In efiect, the gj’s become a dimensionally adaptive random basis of \weak
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