Package: distillML
Type: Package
Title: Model Distillation and Interpretability Methods for Machine
        Learning Models
Version: 0.1.0.9
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, MASS, 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: 7.1.2
NeedsCompilation: no
Packaged: 2022-07-06 00:08:44 UTC; theosaa
Author: Brian Cho [aut],
  Theo Saarinen [aut, cre],
  Jasjeet Sekhon [aut],
  Simon Walter [aut]
Repository: CRAN
Date/Publication: 2022-07-07 08:50:06 UTC
Built: R 4.2.0; ; 2022-07-08 12:04:34 UTC; unix
