A Guide to Feature Importance Methods for Scientific Inference

Understand

While machine learning (ML) models are increasingly used due to their high predictive power, their use in understanding the data-generating process (DGP) is limited.

• Understanding the DGP requires insights into feature-target associations, which many ML models cannot directly provide due to their opaque internal mechanisms.
• Feature importance (FI) methods provide useful insights into the DGP under certain conditions.
• Since the results of different FI methods have different interpretations, selecting the correct FI method for a concrete use case is crucial and still requires expert knowledge.