Add diverse handful of XGBoost models (some shallow, some deeper, and different row/col sample rates, etc) to the top of the AutoML queue using parameters chosen by Branden Murray, Mark Landry and Dmitry Larko. Also compare the ranges against this project.
- Also update the User Guide, R and Python docstrings for the AutoML methods to note the addition of the XGBoost models (where we list the models that are included).
- Not necessary right now, but at some point we should update the leaderboard output in the user guide to include XGBoost models (by re-running the code after it's created). You only have to run it once (from R or Python, then copy/paste the results so they are consistent in the different places the leaderboard output is shown).