I am currently studying about XG boost and Ada boost.
XG boost- extreme gradient boosting.
A variant of the gradient boosting machine.
Ada boost-general method of converting rough rules of thumb into highly accurate predication rule.
I want how these two boosting algorithm are different from each other when they are used to build a classification model .