Description
We explain the key differences between explainability and interpretability and why they're so important for machine learning and AI, before taking a look at several techniques and methods for improvin ...
Summary
- Machine Learning Explainability vs Interpretability: When you think most machine learning engineering is applying algorithms in a very specific way to uncover a certain desired outcome, the model itself can feel like a secondary element - it’s simply a means to an end.
- What this means in practice is that the LIME model develops an approximation of the model by testing it out to see what happens when certain aspects within the model are changed.