[D] 2nd Order Approximation in XGboost’s Objective Function
I have a quick question regarding XGboost’s objective function. I was reading the XGboost paper (https://arxiv.org/pdf/1603.02754.pdf). I see that authors approximated the original objective function using a 2nd order Taylor series (page 2, section 2.2). Is there a particular reason why it’s expanded to 2nd degree and not higher? I’m guessing that linear apprx. is not enough and higher orders require more computational power, but is there a mathematical background or is this a design choice?