DESCRIPTION

Package: distillML
Type: Package
Title: Model Distillation and Interpretability Methods for Machine Learning Models
Version: 0.1.0.14
Authors@R: c(
    person("Brian", "Cho", role = "aut"),
    person("Theo", "Saarinen", role = c("aut","cre"), email = "theo_s@berkeley.edu"),
    person("Jasjeet", "Sekhon", role = "aut"),
    person("Simon", "Walter", role = "aut")
    )
Maintainer: Theo Saarinen <theo_s@berkeley.edu>
BugReports: https://github.com/forestry-labs/distillML/issues
URL: https://github.com/forestry-labs/distillML
Description: Provides several methods for model distillation and interpretability 
    for general black box machine learning models and treatment effect estimation
    methods. For details on the algorithms implemented, see <https://forestry-labs.github.io/distillML/index.html>
    Brian Cho, Theo F. Saarinen, Jasjeet S. Sekhon, Simon Walter.
License: GPL (>=3)
Encoding: UTF-8
Imports:
    ggplot2,
    glmnet,
    Rforestry,
    dplyr,
    R6 (>= 2.0),
    checkmate,
    purrr,
    tidyr,
    data.table,
    mltools,
    gridExtra
Suggests:
    testthat,
    knitr,
    rmarkdown,
    mvtnorm
Collate:
    'predictor.R'
    'interpret.R'
    'distiller.R'
    'plotter.R'
    'surrogate.R'
RoxygenNote: 7.2.3