Package: midr
Type: Package
Title: Learning from Black-Box Models by Maximum Interpretation
        Decomposition
Version: 0.6.2.900
Authors@R: c(
    person("Ryoichi", "Asashiba", email = "ryoichi.asashiba@gmail.com",
           role = c("aut", "cre"), comment = c(ORCID = "0009-0001-9532-7000")),
    person("Hirokazu", "Iwasawa", role = c("aut")),
    person("Reiji", "Kozuma", role = c("ctb"))
  )
Description: The goal of 'midr' is to provide a model-agnostic method
        for interpreting and explaining black-box predictive models by
        creating a globally interpretable surrogate model. The package
        implements 'Maximum Interpretation Decomposition' (MID), a
        functional decomposition technique that finds an optimal
        additive approximation of the original model. This
        approximation is achieved by minimizing the squared error
        between the predictions of the black-box model and the
        surrogate model. The theoretical foundations of MID are
        described in Iwasawa & Matsumori (2025) [Forthcoming], and the
        package itself is detailed in Asashiba et al. (2025)
        <doi:10.48550/arXiv.2506.08338>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: graphics, grDevices, Rcpp, RcppEigen, rlang, stats, utils
Suggests: datasets, ggplot2, khroma, knitr, RColorBrewer, rmarkdown,
        scales, testthat, viridisLite
Config/testthat/edition: 3
RoxygenNote: 7.3.2
URL: https://github.com/ryo-asashi/midr,
        https://ryo-asashi.github.io/midr/
BugReports: https://github.com/ryo-asashi/midr/issues
LinkingTo: Rcpp
Repository: https://ryo-asashi.r-universe.dev
Date/Publication: 2026-10-05 15:02:36 UTC
RemoteUrl: https://github.com/ryo-asashi/midr
RemoteRef: HEAD
RemoteSha: 898758e1e66c2d47033fbfc00bc76be7c1fd6d40
NeedsCompilation: yes
Packaged: 2026-10-05 16:55:46 UTC; root
Author: Ryoichi Asashiba [aut, cre] (ORCID:
    <https://orcid.org/0009-0001-9532-7000>),
  Hirokazu Iwasawa [aut],
  Reiji Kozuma [ctb]
Maintainer: Ryoichi Asashiba <ryoichi.asashiba@gmail.com>