nredell/shapFlex: Stochastic Shapley Values with Causal Constraints in Machine Learning

The purpose of 'shapFlex' is to compute stochastic Shapley values which can be used to interpret and assess the fairness of any machine learning model while incorporating causal constraints into the trained model's feature space.

Getting started

Package details

AuthorNickalus Redell
MaintainerNickalus Redell <[email protected]>
LicenseMIT + file LICENSE
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
nredell/shapFlex documentation built on Jan. 24, 2020, 11:45 p.m.