Package: shapr
Version: 1.0.7
Title: Prediction Explanation with Dependence-Aware Shapley Values
Description: Complex machine learning models are often hard to interpret. However, in
  many situations it is crucial to understand and explain why a model made a specific
  prediction. Shapley values is the only method for such prediction explanation framework
  with a solid theoretical foundation. Previously known methods for estimating the Shapley
  values do, however, assume feature independence. This package implements methods which accounts for any feature
  dependence, and thereby produces more accurate estimates of the true Shapley values.
  An accompanying 'Python' wrapper ('shaprpy') is available through PyPI.
Authors@R: c(
    person("Martin", "Jullum", email = "Martin.Jullum@nr.no", role = c("cre", "aut"), comment = c(ORCID = "0000-0003-3908-5155")),
    person("Lars Henry Berge", "Olsen", email = "lhbolsen@nr.no", role = "aut", comment = c(ORCID = "0009-0006-9360-6993")),
    person("Annabelle", "Redelmeier", email = "ardelmeier@gmail.com", role = "aut"),
    person("Jon", "Lachmann", email = "Jon@lachmann.nu", role = "aut", comment = c(ORCID = "0000-0001-8396-5673")),
    person("Nikolai", "Sellereite", email = "nikolaisellereite@gmail.com", role = "aut", comment = c(ORCID = "0000-0002-4671-0337")),
    person("Anders", "Løland", email = "Anders.Loland@nr.no", role = "ctb"),
    person("Jens Christian", "Wahl", email = "jens.c.wahl@gmail.com", role = "ctb"),
    person("Camilla", "Lingjærde", role = "ctb"),
    person("Norsk Regnesentral", role =  c("cph", "fnd"))
    )
URL: https://norskregnesentral.github.io/shapr/,
        https://github.com/NorskRegnesentral/shapr/
BugReports: https://github.com/NorskRegnesentral/shapr/issues
License: MIT + file LICENSE
Encoding: UTF-8
ByteCompile: true
Language: en-US
RoxygenNote: 7.3.3
Depends: R (>= 3.5.0)
Imports: stats, data.table (>= 1.15.0), Rcpp (>= 0.12.15), Matrix,
        future.apply, methods, cli, rlang
Suggests: ranger, xgboost, mgcv, testthat (>= 3.0.0), knitr, rmarkdown,
        roxygen2, ggplot2, gbm, party, partykit, waldo, progressr,
        future, ggbeeswarm, vdiffr, forecast, torch, GGally, coro,
        parsnip, recipes, workflows, tune, dials, yardstick, hardhat,
        rsample
LinkingTo: RcppArmadillo, Rcpp
VignetteBuilder: knitr
Config/testthat/edition: 3
NeedsCompilation: yes
Packaged: 2025-12-21 00:29:02 UTC; jullum
Author: Martin Jullum [cre, aut] (ORCID:
    <https://orcid.org/0000-0003-3908-5155>),
  Lars Henry Berge Olsen [aut] (ORCID:
    <https://orcid.org/0009-0006-9360-6993>),
  Annabelle Redelmeier [aut],
  Jon Lachmann [aut] (ORCID: <https://orcid.org/0000-0001-8396-5673>),
  Nikolai Sellereite [aut] (ORCID:
    <https://orcid.org/0000-0002-4671-0337>),
  Anders Løland [ctb],
  Jens Christian Wahl [ctb],
  Camilla Lingjærde [ctb],
  Norsk Regnesentral [cph, fnd]
Maintainer: Martin Jullum <Martin.Jullum@nr.no>
Repository: CRAN
Date/Publication: 2025-12-22 16:30:02 UTC
Built: R 4.4.3; x86_64-w64-mingw32; 2025-12-24 00:51:00 UTC; windows
Archs: x64
