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A game theoretic approach to explain the output of any machine learning model.
Created
2016-11-22
2,775 commits to master branch, last one 13 days ago
For calculating global feature importance using Shapley values.
Created
2020-03-13
89 commits to master branch, last one 3 months ago
Shapley Interactions for Machine Learning
Created
2023-10-17
789 commits to main branch, last one 4 days ago
The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).
Created
2020-01-30
357 commits to master branch, last one about a year ago
Explaining the output of machine learning models with more accurately estimated Shapley values
Created
2018-05-16
254 commits to master branch, last one 4 days ago
Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)
Created
2022-04-29
87 commits to master branch, last one 2 years ago
Fast approximate Shapley values in R
Created
2019-07-17
105 commits to master branch, last one 9 months ago
Multi-Touch Attribution
Created
2018-10-31
82 commits to master branch, last one 2 years ago
ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any model or data and different Shapley Values for tree-based mode...
Created
2021-03-24
133 commits to main branch, last one 2 years ago
Amazon SageMaker Solution for explaining credit decisions.
Created
2020-04-02
38 commits to master branch, last one about a year ago
A Julia package for interpretable machine learning with stochastic Shapley values
Created
2020-01-23
118 commits to master branch, last one 2 years ago
streamlit-shap provides a wrapper to display SHAP plots in Streamlit.
Created
2022-01-31
21 commits to main branch, last one 2 years ago
Break Down with interactions for local explanations (SHAP, BreakDown, iBreakDown)
Created
2018-10-17
246 commits to master branch, last one about a year ago
For calculating Shapley values via linear regression.
Created
2020-11-22
5 commits to master branch, last one 3 years ago
A lightweight implementation of removal-based explanations for ML models.
Created
2020-11-20
4 commits to main branch, last one 3 years ago