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15 public repositories
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A game theoretic approach to explain the output of any machine learning model.
Updated
Aug 19, 2020
Jupyter Notebook
Break Down with interactions for local explanations (SHAP, BreakDown, iBreakDown)
Explaining the output of machine learning models with more accurately estimated Shapley values
Fast approximate Shapley values in R
Updated
May 16, 2020
Python
Amazon SageMaker Solution for explaining credit decisions.
Updated
Aug 18, 2020
Python
Package for a nice and smoothe usage of the shapley value for mlr
A Julia package for interpretable machine learning with stochastic Shapley values
Updated
Jul 10, 2020
Julia
For calculating global feature importance using Shapley values.
Updated
Aug 19, 2020
Python
Shapley Values with H2O AutoML Example (ML Interpretability)
Updated
Mar 17, 2019
HTML
An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model
An open source python package to identify customer satisfaction drivers based on Shapley values and Kano Theory
Updated
Jun 8, 2020
Jupyter Notebook
Compute Shapley-Shorrocks value decompositions
A project for Intelligent Systems course done in 2019.3, it's a regression model using the XGBoost algorithm to predict future values of investment fund shares.
Updated
Dec 18, 2019
Jupyter Notebook
Predicting Demand in Primary Health Care Centers in Lebanon: Insight from Syrian Refugees Crisis
Updated
Aug 19, 2020
Jupyter Notebook
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