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The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).
This package can be used for dominance analysis or Shapley Value Regression for finding relative importance of predictors on given dataset. This library can be used for key driver analysis or marginal resource allocation models.
Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)
pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation
SHAP Plots in R
Compute SHAP values for your tree-based models using the TreeSHAP algorithm
A Julia package for interpretable machine learning with stochastic Shapley values
An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model
This repo is the implementation of paper ''SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning''.
A Matlab Toolbox for Cooperative Game Theory
Measuring data importance over ML pipelines using the Shapley value.
A pip library for calculating the Shapley Value for computing the marginal contribution of each client in a Federated Learning environment.
PyTorch reimplementation of computing Shapley values via Truncated Monte Carlo sampling from "What is your data worth? Equitable Valuation of Data" by Amirata Ghorbani and James Zou [ICML 2019]
Codebase for "Greedy Shapley Client Selection for Communication-Efficient Federated Learning"
Hopefully, a compact and general-purpose Python package for Multiperturbation Shapley value Analysis (MSA).
A methodology designed to measure the contribution of the features to the predictive performance of any econometric or machine learning model.
Weighted Shapley Values and Weighted Confidence Intervals for Multiple Machine Learning Models and Stacked Ensembles
This is the official source code for CVPR 2024 paper [WWW: A Unified Framework for Explaining What, Where and Why of Neural Networks by Interpretation of Neuron Concepts]
LINe: Out-of-Distribution Detection by Leveraging Important Neurons (CVPR 2023)
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