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cff-version: 1.2.0
message: 'To cite package "roclab" in publications use:'
type: software
license: MIT
title: 'roclab: ROC-Optimizing Binary Classifiers'
version: 0.1.4
doi: 10.32614/CRAN.package.roclab
abstract: 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) <https://doi.org/10.1145/1046456.1046489>, presented in the ROC Analysis
  in AI Workshop (ROCAI-2004).
authors:
- family-names: Bae
  given-names: Gimun
  email: gimunbae0201@gmail.com
- family-names: Shin
  given-names: Seung Jun
  email: sjshin@korea.ac.kr
repository: https://gimunbae.r-universe.dev
repository-code: https://github.com/gimunBae/roclab
commit: 109e27c6128c80a453d66bcf1fff505533739cc0
url: https://github.com/gimunBae/roclab
date-released: '2025-11-04'
contact:
- family-names: Bae
  given-names: Gimun
  email: gimunbae0201@gmail.com