DESCRIPTION

Package: shapFlex
Type: Package
Title: Stochastic Shapley Values with Causal Constraints in Machine Learning
Version: 0.3.0
Author: Nickalus Redell
Maintainer: Nickalus Redell <nickalusredell@gmail.com>
Description: 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.
License: MIT + file LICENSE
URL: https://github.com/nredell/shapFlex/
Encoding: UTF-8
LazyData: true
Depends: 
    R (>= 3.4.0)
Imports: 
    dplyr (>= 0.8.0.1),
    tidyr (>= 0.8.3),
    future.apply (>= 1.3.0),
    methods,
    rlang (>= 0.4.0),
    magrittr (>= 1.5),
    testthat (>= 2.3.0),
    randomForest (>= 4.6.14),
    igraph (>= 1.2.4),
    purrr (>= 0.3.3)
RoxygenNote: 7.0.2
Collate: 
    'shapFlex.R'
    'r2.R'
    'zzz.R'
    'data_adult.R'
Suggests: 
    covr (>= 3.3.2),
    ggplot2 (>= 3.1.0),
    knitr (>= 1.22),
    rmarkdown (>= 1.11)
VignetteBuilder: knitr