xgboost vs gradient boosting - Explain the difference.

xgboost vs gradient boosting Both xgboost and gbm follow the principle of gradient boosting. There are, however, differences in modeling details. Specifically, xgboost used a more regularized model formalization to control over-fitting, which gives it better performance. We have updated a comprehensive tutorial on introduction to the model, which you might want to take a look at. Introduction to Boosted Trees The name xgboost, though, actually refers to the engineering goal to push the limit of computational resources for boosted tree algorithms. Which is the reason why many people use xgboost. For models, it might be more suitable to be called as regularised gradient boosting.