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
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
NeedsCompilation: no
Packaged: 2025-11-04 06:35:47 UTC; bgd55
Author: Gimun Bae [aut, cre],
  Seung Jun Shin [aut]
Maintainer: Gimun Bae <gimunbae0201@gmail.com>
Repository: CRAN
Date/Publication: 2025-11-04 07:10:02 UTC
Built: R 4.6.0; ; 2026-04-25 13:51:03 UTC; unix
