Applied Machine Learning Explainability Techniques

Chapter 5: Practical Exposure to Using LIME in ML

After reading the last chapter, you should now have a good conceptual understanding of Local Interpretable Model-agnostic Explanations (LIME). We saw how the LIME Python framework can explain black-box models for classification problems. We also discussed some of the pros and cons of the LIME framework. In practice, LIME is still one of the most popular XAI frameworks as it can be easily applied to tabular datasets and text and image datasets. LIME can provide model-agnostic local explanations for solving both regression and classification problems.

In this chapter, you will get much more in-depth practical exposure to using LIME in ML. These are the main topics of discussion for this chapter: ...