Efficient algorithm for solving PU (Positive and Unlabeled) problem in low or high dimensional setting with lasso or group lasso penalty. The algorithm uses Maximization-Minorization and (block) coordinate descent. Sparse calculation and parallel computing are supported for the computational speed-up. See Hyebin Song, Garvesh Raskutti (2018) <doi:10.48550/arXiv.1711.08129>.
Version: 3.2.5 Depends: R (≥ 2.10) Imports: Rcpp (≥ 0.12.8), methods, Matrix, doParallel, foreach, ggplot2 LinkingTo: Rcpp, RcppEigen, Matrix Suggests: testthat, knitr, rmarkdown Published: 2023-12-18 DOI: 10.32614/CRAN.package.PUlasso Author: Hyebin Song [aut, cre], Garvesh Raskutti [aut] Maintainer: Hyebin Song <hps5320 at psu.edu> BugReports: https://github.com/hsong1/PUlasso/issues License: GPL-2 URL: https://arxiv.org/abs/1711.08129 NeedsCompilation: yes Materials: README CRAN checks: PUlasso results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=PUlasso to link to this page.
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