8.26 But first, BART notation:

• Let $K$ be the total number of regression trees and
• $B$ be the number of iterations the BART algorithm will run for
• Let $\hat{f}^b_k(x)$ be the prediction at $x$ for the $k$th regression tree used in the $b$th iteration of the BART algorithm
• At the end of each iteration, the $K$ trees from that iteration will be summed:

$$\hat{f}^b(x) = \sum_{k=1}^{K}\hat{f}^b_k(x)$$ for $b=1,...,B$