There are 3 repositories under shapley-values topic.
Fast approximate Shapley values in R
Paper collection of federated learning. Conferences and Journals Collection for Federated Learning from 2019 to 2021, Accepted Papers, Hot topics and good research groups. Paper summary
Counterfactual SHAP: a framework for counterfactual feature importance
Source code for the Joint Shapley values: a measure of joint feature importance
In this paper we researched the accuracy and usability of machine learning models for MMM analyses.
Weighted Shapley Values and Weighted Confidence Intervals for Multiple Machine Learning Models and Stacked Ensembles
Beyond User Self-Reported Likert Scale Ratings: A Comparison Model for Automatic Dialog Evaluation (ACL 2020)
Counterfactual Shapley Additive Explanation: Experiments
This repository is the official implementation of Explainable Prediction of Acute Myocardial Infarction using Machine Learning and Shapley Values published in IEEE Access in November 2020.
HERALD: An Annotation Efficient Method to Train User Engagement Predictors in Dialogs (ACL 2021)
Reference implementation of the paper Unsupervised Features Ranking via Coalitional Game Theory for Categorical Data
Slides for the "Interpretable SDM with Julia" workshop
Code and experiments related to SHAPEffects paper: 'A feature selection method based on Shapley values robust to concept shift in regression'
Experimental toolbox for quantum Shapley values.
Android malware detection using machine learning.
Reference implementation of the paper Redundancy-aware unsupervised ranking based on game theory - application to gene enrichment analysis
Using SHAP values to explain model features
An investigation on the use of shapley explanations for unsupervised anomaly-detection models
Migration networks and housing prices analysis and ML tools
A Julia port of the fastshap package in R
Heart disease prediction by exploring different models, and feature importance visualization
ML implementations in Multi-scale model for lignin biosynthesis in Populus Trichocarpa
Group Recommendation Systems with Diversity-based Clustering and Game Theory
Two Group Recommendation Approaches based on the Contribution of the Users and Pairwise Preferences
API backend to deploy a machine learning model to the web
A method for conditional shapley value estimation, built off the shapr package: https://github.com/NorskRegnesentral/shapr/tree/master
This is a visual and interactive part of a bigger Adults project. Income prediction is based on Random Forest model. Front part is created with dash framework
Msc. Thesis: Revising the clinical criteria for Dementia using explainable machine learning.
Python/Jupyter Notebook to my Bachelor-Thesis in Computer Science. Explains contributions of features that are not part of a Machine Learning model by using Transfer Learning and Shapley Values/SHAP.