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:
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