Model Dump Parser (like XGBFI) for LightGBM and CatBoost Currently my employer has multiple GLM in a live environment. I am interested in identifying new features and interactions to enhance the accuracy of these GLM; for now I am limited to the GLM structure so simply deploying a solution which automatically accounts for interactions is not possible.
I have in the past used XGBoost to identify powerful feature interactions through the use of XGBFI / XGBFIR. I am now looking in to using LightGBM and CatBoost to do the same but cannot seem to find a tool like XGBFI which works on those models.
Question: Does anything similar to XGBFI exist for LightGBM and CatBoost?
Both LightGBM and CatBoost have functions that give you the models' feature importances. They are described in the respective docs here:

LightGBM: plot_importance and lightgbm.importance
Catboost: has get_feature_importance which is described in more detail on its concepts page