Shapley values have become the go-to for model explainability, but they're not bulletproof — and blindly trusting them can lead to some misleading conclusions. This deep dive from Towards Data Science covers where they fall short and how to work around those limitations. Essential reading if you're building anything that needs to explain its decisions.
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