This project demonstrates the use of Shapley values for model interpretability in machine learning. Shapley values provide a fair method to explain the contribution of each feature to a model's prediction, offering a deeper understanding of how machine learning models make decisions.
- Shapley Values: A concept from cooperative game theory that assigns a fair contribution score to each feature based on its impact on the model’s output.
- Explainable AI: A field of AI aimed at making models and predictions transparent and interpretable to humans.