Weighted Shapley Values and Weighted Confidence Intervals for Multiple Machine Learning Models and Stacked Ensembles
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Updated
Jul 30, 2024 - R
Weighted Shapley Values and Weighted Confidence Intervals for Multiple Machine Learning Models and Stacked Ensembles
Group Recommendation Systems with Diversity-based Clustering and Game Theory
Two Group Recommendation Approaches based on the Contribution of the Users and Pairwise Preferences
A radiomic interpretation tool based on Shapley values
[IJCAI 2024] Redefining Contributions: Shapley-Driven Federated Learning
A Proxy-Based Algorithm for Explaining Survival Models with SHAP
Analysis of baseball stats using ML w/ feature explainability
Fast approximate Shapley values in R
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
A method for conditional shapley value estimation, built off the shapr package: https://github.com/NorskRegnesentral/shapr/tree/master
Msc. Thesis: Revising the clinical criteria for Dementia using explainable machine learning.
Experimental toolbox for quantum Shapley values.
TimeSHAP explains Recurrent Neural Network predictions.
Slides for the "Interpretable SDM with Julia" workshop
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.
Shapley-based decomposition to anatomize the of out-of-sample accuracy of time-series forecasting models
Counterfactual SHAP: a framework for counterfactual feature importance
Counterfactual Shapley Additive Explanation: Experiments
Graph neural network library
Code and experiments related to SHAPEffects paper: 'A feature selection method based on Shapley values robust to concept shift in regression'
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