How do I evaluate feature importance in my model?

How do I evaluate feature importance in my model?

You can evaluate feature importance using techniques like permutation importance, SHAP values, or feature importance from tree-based models.

Can you explain how SHAP values work?

SHAP values provide a way to understand the contribution of each feature to the model's predictions by calculating the average impact of each feature across all predictions.

What are some tools I can use to calculate feature importance?

You can use libraries like Scikit-learn, XGBoost, or SHAP in Python to calculate feature importance easily.

Are there any limitations to these methods?

Yes, some methods may not work well with certain types of data or models, and they can be computationally expensive.