Idea Behind LIME and SHAP

The intuition behind ML interpretation models

In machine learning, there has been a trade-off between model complexity and model performance. Complex machine learning models e.g. deep learning (that perform better than interpretable models e.g. linear regression) have been treated as black boxes. Research paper by Ribiero et al (2016) titled “Why Should I Trust You” aptly encapsulates the issue with ML black boxes. Model interpretability is a growing field of research. Please read here for the importance of machine interpretability. This blog discusses…