Machine Learning, Data Science, Design.
preferred choice: step max_depth down :) If Gamma is useful (i.e train CV skyrockets at godlike speed when test CV can’t follow), crank up Gamma. This is where the experience with tuning Gamma is useful (so you lose the lowest amount of time). Depending on what you see between the train/test CV