Good afternoon,
I have two questions concerning the loss functions used for the Gradient Boosted Decision Tree TMVA method.

What is the default loss function used?
This post here pretty clearly states it is crossentropy. However, page 68 of the TMVA User guide states the default for all TMVA implimentations of GradientBoost is the binomial loglikelihood loss. Thank you in advance for the clarification! 
Is it possible to define a custom loss function for use in BDTG training? this presentation suggests on slide 20 that it is possible for regression problems. If so, pointing me towards a practical example of how to do so would be greatly appreciated. For context, i require the use of a modified crossentropy loss function that would still be differentiable.
Thanks again,
Matt