Mindful Modeler • 898 implied HN points • 07 Feb 23
- It's important to avoid assuming one method is always the best for all interpretation contexts when working with machine learning interpretability tools like SHAP.
- Different interpretability methods like SHAP and permutation feature importance (PFI) have unique goals and can provide different insights, so it's crucial to choose the method that aligns with the specific question you want to answer.
- Research on interpretability should be more driven by questions rather than methods, to ensure that the tools used provide meaningful insights based on the context.