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shapley
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A game theoretic approach to explain the output of any machine learning model.
Shapley Interactions and Shapley Values for Machine Learning
For calculating global feature importance using Shapley values.
The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).
Explaining the output of machine learning models with more accurately estimated Shapley values
Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)
Fast approximate Shapley values in R
ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any model or data and different Shapley Values for tree-based models.
Amazon SageMaker Solution for explaining credit decisions.
A Julia package for interpretable machine learning with stochastic Shapley values
streamlit-shap provides a wrapper to display SHAP plots in Streamlit.
Break Down with interactions for local explanations (SHAP, BreakDown, iBreakDown)
An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model
For calculating Shapley values via linear regression.
A lightweight implementation of removal-based explanations for ML models.
Counterfactual SHAP: a framework for counterfactual feature importance
Shapley Values with H2O AutoML Example (ML Interpretability)
