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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?

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Both LightGBM and CatBoost have functions that give you the models' feature importances. They are described in the respective docs here:

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