xplus: Positive and Unlabeled Learning from Unbalanced Cases and Sparse Structures

Provides PLUS-derived extensions for positive and unlabeled (PU) learning from unbalanced cases and sparse structures, based on Zhou et al. (2022) <doi:10.1371/journal.pcbi.1009956>. Iteratively relabels unlabeled observations via penalised logistic regression and pseudo-label updates, then refits a final sparse model. Includes weighted bootstrap sampling, convergence diagnostics, prediction, coefficient extraction, and assessment utilities.

Version:	1.0.2
Depends:	R (≥ 4.1.0)
Imports:	glmnet (≥ 4.1-8), Matrix, methods, stats, tibble, utils
Suggests:	covr, knitr, rmarkdown, survival, testthat (≥ 3.0.0)
Published:	2026-09-26
DOI:	10.32614/CRAN.package.xplus (may not be active yet)
Author:	Angel Robles [aut, cre]
Maintainer:	Angel Robles <a.l.robles.fernandez at gmail.com>
BugReports:	https://github.com/alrobles/xplus/issues
License:	GPL (≥ 3)
URL:	https://github.com/alrobles/xplus, https://alrobles.github.io/xplus/
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	xplus results

Documentation:

Reference manual:	xplus.html , xplus.pdf
Vignettes:	Introduction to xplus (source, R code)

Downloads:

Package source:	xplus_1.0.2.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): xplus_1.0.2.tgz, r-oldrel (arm64): xplus_1.0.2.tgz, r-release (x86_64): xplus_1.0.2.tgz, r-oldrel (x86_64): xplus_1.0.2.tgz

Linking:

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