title: How come multiple regression has so many assumptions, while advanced machine learning algorithms have next to none?
body: <p>I am analyzing a real-estate dataset. While all regression assumptions fail, my XGBoosting model thrives. Am I missing something? Is XGBoost just the superior model in this case? The dataset is around 67.000 observations and 30 variables.</p>