In the kaggle forums I found an example model where someone was using XGBRegressor for a binary (0/1) classification problem (sorry, cannot find the link any more). This was for a competition where output is measured by AUC, so only ranks mattered.
I then tried this for a different problem with my data and also found a slight improvement using the Regressor instead of the Classifier.
Some of my predictions where negative, but it would be no problem to shift them to the [0,1] interval.
So is using regression for binary classification a common approach, and what are the pros and cons?