@moritz_skb every KNIME nodes has some sort of documentation like the XGBoost Tree Ensemble Learner:
There you will find additional links and literature to explain what has been done. In this case to the official documentation and there you will find what the algorithm does:
https://xgboost.readthedocs.io/en/stable/tutorials/categorical.html
The KNIME implementation might ‘compress’ such settings or provide some of them by default or with switches in the node.
If you want to do the data preparations yourself you could automate that using tools like vtreat or KNIME nodes (like Category to Number):
Also there is this approach:
For H2O Gradient Boosting Machine Learner and H2O Random Forest Learner this list also can serve as an overview of what methods are widely used:
https://docs.h2o.ai/h2o/latest-stable/h2o-docs/data-science/algo-params/categorical_encoding.html
You will in this case find the options in the KNIME nodes:
