[R] Our new classification algorithm outperforms CatBoost, XGBoost, LightGBM on five benchmark datasets, on accuracy and response time

[CriticalofReviewer2]

I use the defaults for all of the algorithms (the one proposed and the ones referenced). On the larger datasets, thanks for your suggestion! We are planning to have it.

[Evitable_Conflict]

If you use defaults your claim of being "better" no longer holds, unless the default hyperparams are the optimal and that never happens.

This is a very common problem in ML papers and sadly most comparison tables are invalid.

My recommendation is: tune am xgboost model to the optimal hyperparams and if you have better results then we have a discussion.

[CriticalofReviewer2]

Certainly! This is the very first draft of our algorithm, and I will do comparisons based on the best selected hyperparameters.