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 42 shapley value methods frameworks tracked. 2 score above 70 (verified tier). The highest-rated is shap/shap at 92/100 with 25,115 stars and 14,461,405 monthly downloads. 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.	92	Verified	25,115	Jupyter Notebook
2	mmschlk/shapiq Shapley Interactions and Shapley Values for Machine Learning	74	Verified	695	Python
3	predict-idlab/powershap A power-full Shapley feature selection method.	60	Established	214	Python
4	linkedin/FastTreeSHAP Fast SHAP value computation for interpreting tree-based models	53	Established	554	Python
5	aerdem4/lofo-importance Leave One Feature Out Importance	53	Established	863	Python
6	iancovert/sage For calculating global feature importance using Shapley values.	49	Emerging	285	Python
7	ReX-XAI/ReX Causal Responsibility EXplanations for Image Classifiers and Tabular Data	43	Emerging	41	Python
8	GitsSaikat/QuXAI Explainers for Quantum Machine Learning Models	39	Emerging	9	Python
9	wilsonjr/ClusterShapley Explaining dimensionality results using SHAP values	39	Emerging	55	C++
10	snehankekre/streamlit-shap streamlit-shap provides a wrapper to display SHAP plots in Streamlit.	39	Emerging	91	Python
11	haghish/shapley Weighted Shapley Values and Weighted Confidence Intervals for Multiple...	37	Emerging	18	R
12	MauroLuzzatto/explainy explainy is a Python library for generating machine learning model...	36	Emerging	18	Python
13	bank-of-england/Shapley_regressions Statistical inference on machine learning or general non-parametric models	35	Emerging	44	Python
14	mlr-org/xplainfi Model-agnostic feature importance methods	34	Emerging	4	R
15	AidanCooper/shap-analysis-guide How to Interpret SHAP Analyses: A Non-Technical Guide	33	Emerging	58	Jupyter Notebook
16	stavrostheocharis/easy_explain An XAI library that helps to explain AI models in a really quick & easy way	33	Emerging	17	Python
17	ajsanjoaquin/Shapley_Valuation PyTorch reimplementation of computing Shapley values via Truncated Monte...	32	Emerging	27	Python
18	easeml/datascope Measuring data importance over ML pipelines using the Shapley value.	32	Emerging	45	Python
19	jpmorganchase/cf-shap Counterfactual SHAP: a framework for counterfactual feature importance	32	Emerging	21	HTML
20	ModelOriented/kernelshap Different SHAP algorithms	31	Emerging	60	R
21	AstraZeneca/awesome-shapley-value Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)	31	Emerging	154	—
22	jpmorganchase/cf-shap-facct22 Counterfactual Shapley Additive Explanation: Experiments	30	Emerging	11	Jupyter Notebook
23	tsitsimis/tinyshap Python package providing a minimal implementation of the SHAP algorithm...	30	Emerging	8	Jupyter Notebook
24	AmirhosseinHonardoust/Shap-Mini A minimal, reproducible explainable-AI demo using SHAP values on tabular...	26	Experimental	20	Python
25	akassharjun/ShapleyValueFL A pip library for calculating the Shapley Value for computing the marginal...	25	Experimental	29	Python
26	eaguaida/causal-explainer an open-source alternative to localised explanations in DNN/ML models	23	Experimental	1	Python
27	zabir-nabil/What-If-Explainability Explaining Trees (LightGBM) with FastTreeShap (Shapley) and What if tool	23	Experimental	6	Jupyter Notebook
28	Nelsonchris1/ML-explainability-app This is a web app built for easy explainability of machine learning models...	23	Experimental	20	Python
29	Lorean44/DataTypical 🔍 Analyze datasets with DataTypical to identify key instances and their...	22	Experimental	—	Python
30	AndMastro/EdgeSHAPer EdgeSHAPer: Bond-Centric Shapley Value-Based Explanation Method for Graph...	22	Experimental	27	Jupyter Notebook
31	FernandoLpz/SHAP-Classification-example This repository contains an example of how to implement the shap library to...	20	Experimental	10	Jupyter Notebook
32	cohortshapley/cohortshapley Cohort Shapley: A local explanation method for black box prediction with...	20	Experimental	25	Jupyter Notebook
33	mlr-org/gadget Decomposing Global Feature Effects Based on Feature Interactions	16	Experimental	2	R
34	wideraHannes/SHAP-In-NLP Code for my thesis about SHAP. Implementation of DecisionTree, SVM, BERT on...	15	Experimental	5	Jupyter Notebook
35	Stokaru/tabular-ml-shap-consistency 🔍 Streamline tabular binary classification with model interpretability and...	14	Experimental	—	Python
36	schufa-innovationlab/pltreeshap A SHAP implementation for piecewise linear trees	13	Experimental	6	Cython
37	CCaribe9/SHAPEffects Code and experiments related to SHAPEffects paper: 'A feature selection...	13	Experimental	6	Jupyter Notebook
38	JoranMichiels/decomposition-shap Explain model and feature dependencies by decomposition of SHAP values	13	Experimental	7	Python
39	0Kan0/Algorithm-for-the-generation-of-group-counterfactual-scenarios Final Master Project made by Alberto Cano Turnes	12	Experimental	3	Jupyter Notebook
40	mayer79/permshap Permutation SHAP	12	Experimental	3	R
41	harris-chris/joint-shapley-values Source code for the Joint Shapley values: a measure of joint feature importance	12	Experimental	13	Jupyter Notebook
42	mdbenito/re-classwise-shapley Code for the reproduction of Class-wise Shapley paper from Schoch, Xu, Ji [2022].	11	Experimental	2	TeX

Comparisons in this category

shap and shapiq (92 vs 74) shap and FastTreeSHAP (92 vs 53) shap and sage (92 vs 49) shap and streamlit-shap (92 vs 39) shap and shap-analysis-guide (92 vs 33) shap and Shapley_regressions (92 vs 35) shap and cf-shap (92 vs 32) shapiq and sage (74 vs 49) shapiq and awesome-shapley-value (74 vs 31) shapiq and cf-shap (74 vs 32)