i am currently reading the TMVA User Guide and have a question regarding the gradient boosting of BDTs.
In a gradient boosted BDT, are the individual trees that make up the final BDT actual decision trees or are they regression trees in there. I am particularly unsure because of this sentence on page 68:
This is done by calculating the current gradient of the loss function and then growing a regression tree whose leaf values are adjusted to match the mean value of the gradient in each region defined by the tree structure. Iterating this procedure yields the desired set of decision trees which minimises the loss function.
Looking at the code I also could not find a clear indication whether each individual tree only has output of ±1 (decision tree) or if any value in between is also possible (decision tree).