SHapley Additive exPlanations or SHAP : What is it ?

SHapley Additive exPlanations, more commonly known as SHAP, is used to explain the output of Machine Learning models. It is based on Shapley values, which

Verifying explainability of a deep learning tissue classifier trained on RNA-seq data

A) Shapley additive explanations (SHAP) analysis for the 12 feature RF

8 Shapley Additive Explanations (SHAP) for Average Attributions

9.6 SHAP (SHapley Additive exPlanations)

SHAP with Python (Code and Explanations)

Explaining ML models with SHAP and SAGE

9.6 SHAP (SHapley Additive exPlanations)

R/English】SHapley Additive exPlanations (SHAP) #R - Qiita

A gentle introduction to SHAP values in R