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Explaining Models with Classic Methods and SHAP

Michael Mayer has some ‘splainin to do:

Let’s explain a {tidymodels} random forest by classic explainability methods (permutation importance, partial dependence plots (PDP), Friedman’s H statistics), and also fancy SHAP.

Disclaimer: {hstats}, {kernelshap} and {shapviz} are three of my own packages.

What I really appreciate in here is that Michael includes classic methods here. It can be easy to say “Oh, this is old and therefore no longer relevant.” But that would be quite wrong.