Shapley Value Methods ML Frameworks

Tools and libraries for computing, analyzing, and interpreting Shapley values for feature importance, model explanation, and data valuation. Does NOT include general feature importance methods, model interpretability frameworks, or explainability systems that don't specifically use Shapley value theory.

There are 44 shapley value methods frameworks tracked. 1 score above 70 (verified tier). The highest-rated is shap/shap at 82/100 with 25,115 stars. 2 of the top 10 are actively maintained.

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#	Framework	Score	Tier	Stars	Language
1	shap/shap A game theoretic approach to explain the output of any machine learning model.	82	Verified	25,115	Jupyter Notebook
2	mmschlk/shapiq Shapley Interactions and Shapley Values for Machine Learning	68	Established	695	Python
3	iancovert/sage For calculating global feature importance using Shapley values.	56	Established	285	Python
4	aerdem4/lofo-importance Leave One Feature Out Importance	53	Established	863	Python
5	predict-idlab/powershap A power-full Shapley feature selection method.	53	Established	214	Python
6	ReX-XAI/ReX Causal Responsibility EXplanations for Image Classifiers and Tabular Data	50	Established	41	Python
7	linkedin/FastTreeSHAP Fast SHAP value computation for interpreting tree-based models	50	Established	554	Python
8	snehankekre/streamlit-shap streamlit-shap provides a wrapper to display SHAP plots in Streamlit.	46	Emerging	91	Python
9	GitsSaikat/QuXAI Explainers for Quantum Machine Learning Models	46	Emerging	9	Python
10	haghish/shapley Weighted Shapley Values and Weighted Confidence Intervals for Multiple...	44	Emerging	18	R
11	wilsonjr/ClusterShapley Explaining dimensionality results using SHAP values	42	Emerging	55	C++
12	bank-of-england/Shapley_regressions Statistical inference on machine learning or general non-parametric models	42	Emerging	44	Python
13	mlr-org/xplainfi Model-agnostic feature importance methods	41	Emerging	4	R
14	AidanCooper/shap-analysis-guide How to Interpret SHAP Analyses: A Non-Technical Guide	40	Emerging	58	Jupyter Notebook
15	stavrostheocharis/easy_explain An XAI library that helps to explain AI models in a really quick & easy way	40	Emerging	17	Python
16	ajsanjoaquin/Shapley_Valuation PyTorch reimplementation of computing Shapley values via Truncated Monte...	39	Emerging	27	Python
17	jpmorganchase/cf-shap Counterfactual SHAP: a framework for counterfactual feature importance	39	Emerging	21	HTML
18	easeml/datascope Measuring data importance over ML pipelines using the Shapley value.	39	Emerging	45	Python
19	AstraZeneca/awesome-shapley-value Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)	38	Emerging	154	—
20	ModelOriented/kernelshap Different SHAP algorithms	38	Emerging	60	R
21	MauroLuzzatto/explainy explainy is a Python library for generating machine learning model...	38	Emerging	18	Python
22	jpmorganchase/cf-shap-facct22 Counterfactual Shapley Additive Explanation: Experiments	37	Emerging	11	Jupyter Notebook
23	tsitsimis/tinyshap Python package providing a minimal implementation of the SHAP algorithm...	37	Emerging	8	Jupyter Notebook
24	akassharjun/ShapleyValueFL A pip library for calculating the Shapley Value for computing the marginal...	32	Emerging	29	Python
25	AmirhosseinHonardoust/Shap-Mini A minimal, reproducible explainable-AI demo using SHAP values on tabular...	30	Emerging	20	Python
26	zabir-nabil/What-If-Explainability Explaining Trees (LightGBM) with FastTreeShap (Shapley) and What if tool	30	Emerging	6	Jupyter Notebook
27	eaguaida/causal-explainer an open-source alternative to localised explanations in DNN/ML models	30	Emerging	1	Python
28	Nelsonchris1/ML-explainability-app This is a web app built for easy explainability of machine learning models...	30	Emerging	20	Python
29	AndMastro/EdgeSHAPer EdgeSHAPer: Bond-Centric Shapley Value-Based Explanation Method for Graph...	29	Experimental	27	Jupyter Notebook
30	cohortshapley/cohortshapley Cohort Shapley: A local explanation method for black box prediction with...	27	Experimental	25	Jupyter Notebook
31	FernandoLpz/SHAP-Classification-example This repository contains an example of how to implement the shap library to...	27	Experimental	10	Jupyter Notebook
32	wideraHannes/SHAP-In-NLP Code for my thesis about SHAP. Implementation of DecisionTree, SVM, BERT on...	22	Experimental	5	Jupyter Notebook
33	Lorean44/DataTypical 🔍 Analyze datasets with DataTypical to identify key instances and their...	22	Experimental	—	Python
34	JoranMichiels/decomposition-shap Explain model and feature dependencies by decomposition of SHAP values	20	Experimental	7	Python
35	schufa-innovationlab/pltreeshap A SHAP implementation for piecewise linear trees	20	Experimental	6	Cython
36	CCaribe9/SHAPEffects Code and experiments related to SHAPEffects paper: 'A feature selection...	20	Experimental	6	Jupyter Notebook
37	harris-chris/joint-shapley-values Source code for the Joint Shapley values: a measure of joint feature importance	19	Experimental	13	Jupyter Notebook
38	mayer79/permshap Permutation SHAP	19	Experimental	3	R
39	mlr-org/gadget Decomposing Global Feature Effects Based on Feature Interactions	19	Experimental	2	R
40	0Kan0/Algorithm-for-the-generation-of-group-counterfactual-scenarios Final Master Project made by Alberto Cano Turnes	19	Experimental	3	Jupyter Notebook
41	mdbenito/re-classwise-shapley Code for the reproduction of Class-wise Shapley paper from Schoch, Xu, Ji [2022].	18	Experimental	2	TeX
42	Stokaru/tabular-ml-shap-consistency 🔍 Streamline tabular binary classification with model interpretability and...	14	Experimental	—	Python
43	ccomkhj/interpretable-lightgbm SHAP explainer for LightGBM models - Generate feature importance plots,...	12	Experimental	6	Python
44	bostjanv76/featConstr Explainable Feature Construction (EFC)	11	Experimental	—	Java

Comparisons in this category

shap and shapiq (82 vs 68) shap and FastTreeSHAP (82 vs 50) shap and sage (82 vs 56) shap and streamlit-shap (82 vs 46) shap and kernelshap (82 vs 38) shap and shap-analysis-guide (82 vs 40) shap and Shapley_regressions (82 vs 42) shap and cf-shap (82 vs 39)