Machine Learning, Gradient Boosting, Data Science, Towards Data Science, Loss Function.
usually the optimization method, the training loss typically needs to be a function that has a convex gradient (first derivative) and hessian (second derivative). It is also preferably continuous, finite, and non-zero. The last one is important because sections where the function is zero can freeze