Package: labelnoise
Title: Find Label Errors in Classification Data with Confident Learning
Version: 0.1.0
Authors@R: 
    person("Ridson", "Al Farizal P", , "ridsonalfarizal15@gmail.com", role = c("aut", "cre", "cph"),
           comment = c(ORCID = "0000-0003-0617-0214"))
Description: Finds examples whose given class label is likely wrong,
        using out-of-sample predicted probabilities from any
        classifier. Implements confident learning (Northcutt, Jiang and
        Chuang, 2021) <doi:10.1613/jair.1.12125>: per-class confidence
        thresholds, the confident joint, calibrated estimates of the
        joint distribution of given and true labels, noise transition
        matrices, and five rank-and-prune rules for flagging label
        issues. Also provides model-agnostic label quality scores (Kuan
        and Mueller, 2022) <doi:10.5281/zenodo.18168246> and a
        per-class label health summary. Inputs can be a label vector
        with a probability matrix, a data frame of predictions,
        resampling results from 'tune', predictions from 'mlr3', or a
        fitted 'caret' model.
License: MIT + file LICENSE
URL: https://ridsonap.is-a.dev/labelnoise/,
        https://github.com/ridsonap/labelnoise
BugReports: https://github.com/ridsonap/labelnoise/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: cli, rlang (>= 1.1.0), stats, utils, tibble, tidyselect
Suggests: caret, knitr, lgr, mlr3, nnet, parsnip, rmarkdown, rsample,
        testthat (>= 3.0.0), tune, withr, workflows, yardstick
VignetteBuilder: knitr
Config/testthat/edition: 3
Config/roxygen2/version: 8.0.0
NeedsCompilation: no
Packaged: 2026-11-14 00:35:47 UTC; root
Author: Ridson Al Farizal P [aut, cre, cph] (ORCID:
        <https://orcid.org/0000-0003-0617-0214>)
Maintainer: Ridson Al Farizal P <ridsonalfarizal15@gmail.com>
Repository: https://cran.r-universe.dev
Date/Publication: 2026-11-13 17:10:08 UTC
RemoteUrl: https://github.com/cran/labelnoise
RemoteRef: HEAD
RemoteSha: 1bae123c1d1650db1fbe1491b84b5e4254faed3c