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

A novel approach to explain the black-box nature of machine learning in compressive strength predictions of concrete using Shapley additive explanations (SHAP) - ScienceDirect

Shapley Additive exPlanations (SHAP) using Knime on Vimeo

SHAP Explained Papers With Code

A gentle introduction to SHAP values in R

Using SHAP for Global Explanations of Model Predictions

SHapley Additive exPlanations or SHAP : What is it ?

SHapley Additive exPlanations or SHAP : What is it ?

Prediction of HHV of fuel by Machine learning Algorithm: Interpretability analysis using Shapley Additive Explanations (SHAP) - ScienceDirect

Welcome to the SHAP documentation — SHAP latest documentation

Towards Explainable Artificial Intelligence in Financial Fraud Detection: Using Shapley Additive Explanations to Explore Feature Importance

What is Shapley Additive Explanations (SHAP)

SHAP : A Comprehensive Guide to SHapley Additive exPlanations

Shapley Values — mlfinlab 1.5.0 documentation

SHapley Additive exPlanations(SHAP): A Simple Explainer

Interpretable AI with SHAP. A case for interpretable AI, by Quin Daly