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SHAP is a recently proposed algorithm for interpretable machine learning by
Lundberg, Scott M., and Su-In Lee. “A unified approach to interpreting model predictions.” Advances in Neural Information Processing Systems. 2017
and tree-SHAP is a specific version of implementation for tree-based machine learning like CART, Random Forest, Gradient Boost, etc.
Lundberg, Scott M., Gabriel G. Erion, and Su-In Lee. “Consistent individualized feature attribution for tree ensembles.” arXiv preprint arXiv:1802.03888 (2018)
SHAP is a recently proposed algorithm for interpretable machine learning by
and tree-SHAP is a specific version of implementation for tree-based machine learning like CART, Random Forest, Gradient Boost, etc.
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