When you train your XGBoost regression model, you can obtain feature importances by using:
Although I tried to reconstruct the value and have done some research on it, I am still struggling to figure out, how gain is computed in XGBoost?
It is partially explained here: Relative variable importance for Boosting
But this is focused on classification. And even though there is a link saying that
squared error with Friedman's improvement score is used, I have not reached the same numbers.