Package: roclab
Title: ROC-Optimizing Binary Classifiers
Version: 0.1.4
Authors@R: 
    c(
      person("Gimun", "Bae", 
             email = "gimunbae0201@gmail.com", 
             role = c("aut", "cre")),
      person("Seung Jun", "Shin", 
             email = "sjshin@korea.ac.kr", 
             role = "aut")
    )
Description: Implements ROC (Receiver Operating
        Characteristic)–Optimizing Binary Classifiers, supporting both
        linear and kernel models. Both model types provide a variety of
        surrogate loss functions. In addition, linear models offer
        multiple regularization penalties, whereas kernel models
        support a range of kernel functions. Scalability for large
        datasets is achieved through approximation-based options, which
        accelerate training and make fitting feasible on large data.
        Utilities are provided for model training, prediction, and
        cross-validation. The implementation builds on the
        ROC-Optimizing Support Vector Machines. For more information,
        see Hernàndez-Orallo, José, et al. (2004)
        <doi:10.1145/1046456.1046489>, presented in the ROC Analysis in
        AI Workshop (ROCAI-2004).
License: MIT + file LICENSE
Encoding: UTF-8
Imports: stats, graphics, utils, ggplot2, fastDummies, kernlab, pracma,
        rsample, dplyr, caret, pROC
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Suggests: mlbench, knitr, rmarkdown, testthat (>= 3.0.0)
Config/testthat/edition: 3
VignetteBuilder: knitr
URL: https://github.com/gimunBae/roclab
BugReports: https://github.com/gimunBae/roclab/issues
Config/pak/sysreqs: libicu-dev
Repository: https://gimunbae.r-universe.dev
Date/Publication: 2026-08-21 02:27:40 UTC
RemoteUrl: https://github.com/gimunbae/roclab
RemoteRef: HEAD
RemoteSha: 6271ff5cf1dd2c66efa5e1cc81004e1eee54a9d4
NeedsCompilation: no
Packaged: 2026-09-20 07:12:22 UTC; root
Author: Gimun Bae [aut, cre],
  Seung Jun Shin [aut]
Maintainer: Gimun Bae <gimunbae0201@gmail.com>