shapley
There are 41 repositories under shapley topic.
shap/shap
A game theoretic approach to explain the output of any machine learning model.
iancovert/sage
For calculating global feature importance using Shapley values.
benedekrozemberczki/shapley
The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).
NorskRegnesentral/shapr
Explaining the output of machine learning models with more accurately estimated Shapley values
AstraZeneca/awesome-shapley-value
Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)
bgreenwell/fastshap
Fast approximate Shapley values in R
salimamoukou/acv00
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 models.
eeghor/mta
Multi-Touch Attribution
awslabs/sagemaker-explaining-credit-decisions
Amazon SageMaker Solution for explaining credit decisions.
nredell/ShapML.jl
A Julia package for interpretable machine learning with stochastic Shapley values
ModelOriented/iBreakDown
Break Down with interactions for local explanations (SHAP, BreakDown, iBreakDown)
snehankekre/streamlit-shap
streamlit-shap provides a wrapper to display SHAP plots in Streamlit.
nredell/shapFlex
An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model
iancovert/shapley-regression
For calculating Shapley values via linear regression.
iancovert/removal-explanations
A lightweight implementation of removal-based explanations for ML models.
redichh/ShapleyR
Package for a nice and smoothe usage of the shapley value for mlr
SeanPLeary/shapley-values-h2o-example
Shapley Values with H2O AutoML Example (ML Interpretability)
jpmorganchase/cf-shap
Counterfactual SHAP: a framework for counterfactual feature importance
elbersb/shapley
Compute Shapley-Shorrocks value decompositions
FernandoLpz/SHAP-Classification-example
This repository contains an example of how to implement the shap library to interpret a machine learning model.
tsurubee/shappack
Interpretable machine learning based on Shapley values
jpmorganchase/cf-shap-facct22
Counterfactual Shapley Additive Explanation: Experiments
shubh1608/Jupyter-Notebook-Template
Jupyter Notebook Templates for quick prototyping of machine learning solutions
uyanik/ShapKa
An open source library for key drivers analysis based on Shapley values and Kano Theory
LamineTourelab/Explainable-AI
In this repository you will fine explainability of machine learning models.
hiyamgh/Forecasting-Demand-Primary-Health-Care
Predicting Demand in Primary Health Care Centers in Lebanon: Insight from Syrian Refugees Crisis
jasonjfoster/rollshap
Analytical computation of rolling and expanding Shapley values for time-series data.
matthieuvion/match2kd
Save thousands of API calls. Custom model & dataset aiming at predicting a game difficulty score ("lobby avg kd") without calling players' games history stats and profiles.
ruoxi-jia-group/2d-shapley
This is an official repository for "2D-Shapley: A Framework for Fragmented Data Valuation" (ICML2023).
leo-cb/HeartDiseasePrediction_ModelDev
Exploratory data analysis, model development and model explainability for the heart disease web application. Stack: Databricks, Pyspark, MLFlow, AutoML, Shapley, Docker.
tam-ng/Survival_Analysis_ICU_24hrs
Using data within first 24 hours of intensive care to develop a machine learning model that could improve the current patient survival probability prediction system (apache_4a) and is more generalized to patients outside of the US
vla6/Stereotyping_ROCDS
Examines fairness metrics for models including gender stereotyping versus group differences due to appropriate predictors. Also explores feature bias mitigation
Oxygen-Oriented-Programming/Clean-Air-Compass-GeoJson-FastAPI
FastAPI for gathering LocationIQ bounding box and PurpleAir Sensor Data then creating interpolated GeoJson using KNN-Regression
beckypangpang/horse-racing-prediction-SHAP
This repository contains the code for machine learning models designed to predict the outcomes of horse races, with SHAP (SHapley Additive exPlanations) interpretation incorporated for enhanced model interpretability.
leo-cb/HeartDiseasePrediction_WebApp
Flask app that predicts the risk of heart disease based on a GBT ML model, and shows the confidence in the prediction as well as the factors behind the prediction (explainability).
Wafama/Spatiotemporal-Data-Analysis
Analysing Time series and spatiotemporal data