Although AutoGluon-Tabular can be used with model tuning, its design can deliver good performance using stacking and ensemble methods, meaning hyperparameter optimization is not necessary. Rather than focusing on model tuning, AutoGluon-Tabular succeeds by stacking models in multiple layers and training in a layer-wise manner.
For more information about AutoGluon-Tabular hyperparameters, see AutoGluon-Tabular hyperparameters.
