I wanted to raise a doubt regarding the definition of feature interaction according to XGBoost documentation. In the statistical sense, feature interaction happens when two (or more) feature combine together to significantly impact the prediction (which can be visualized as the multiplicative term in the linear regression models). But as XGBoost, all the feature in a traversal path are interacting features.
In case of linear models, let’s say you have two features X and Y which do not interact in statistical sense, but you can still make a decision tree splits on both X and Y. So according to your definition, there is interaction between these features but that’s not accurate.
Maybe feature interaction in XGBoost should be named as something else to avoid this confusion?