# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "dfr" in publications use:' type: software license: GPL-3.0-or-later title: 'dfr: Dual Feature Reduction for SGL' version: 0.1.1 doi: 10.48550/arXiv.2405.17094 identifiers: - type: doi value: 10.32614/CRAN.package.dfr abstract: Implementation of the Dual Feature Reduction (DFR) approach for the Sparse Group Lasso (SGL) and the Adaptive Sparse Group Lasso (aSGL) (Feser and Evangelou (2024) ). The DFR approach is a feature reduction approach that applies strong screening to reduce the feature space before optimisation, leading to speed-up improvements for fitting SGL (Simon et al. (2013) ) and aSGL (Mendez-Civieta et al. (2020) and Poignard (2020) ) models. DFR is implemented using the Adaptive Three Operator Splitting (ATOS) (Pedregosa and Gidel (2018) ) algorithm, with linear and logistic SGL models supported, both of which can be fit using k-fold cross-validation. Dense and sparse input matrices are supported. authors: - family-names: Feser given-names: Fabio email: ff120@ic.ac.uk orcid: https://orcid.org/0009-0007-3088-9727 preferred-citation: type: article title: Dual feature reduction for the sparse-group lasso and its adaptive variant authors: - family-names: Feser given-names: Fabio email: ff120@ic.ac.uk orcid: https://orcid.org/0009-0007-3088-9727 - family-names: Evangelou given-names: Marina orcid: https://orcid.org/0000-0003-0789-8944 journal: arXiv year: '2024' doi: 10.48550/arXiv.2405.17094 url: https://arxiv.org/abs/2405.17094 repository: https://ff1201.r-universe.dev repository-code: https://github.com/ff1201/dfr commit: d572628d6b5801d61a8b2b2316ef59db22f2edd9 url: https://github.com/ff1201/dfr date-released: '2024-11-16' contact: - family-names: Feser given-names: Fabio email: ff120@ic.ac.uk orcid: https://orcid.org/0009-0007-3088-9727 references: - type: manual title: dfr authors: - family-names: Feser given-names: Fabio email: ff120@ic.ac.uk orcid: https://orcid.org/0009-0007-3088-9727 year: '2024' url: https://CRAN.R-project.org/package=dfr