Hands-On Explainable AI (XAI) with Python

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Anchors XAI

The explainable AI (XAI) tools we have explored up to now are model-agnostic. They can be applied to any machine learning (ML) model. The XAI tools we implemented come from solid mathematical theory and Python modules. In Chapter 8, Local Interpretable Model-Agnostic Explanations (LIME), we even ran several ML models to prove that LIME, for example, was model-agnostic.

We can represent model-agnostic (ma) tools as a function of ML(x) algorithms in which ma(x) -> Explanations. You can read the function as a model-agnostic tool that will generate explanations for any ML model.

However, the opposite is not true! Explanations(x) -> ma is false. You can read the function as an explanation of any ML model that can be obtained by any ...