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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.
Getting started
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Package details |
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| Author | Angel Robles [aut, cre] (ORCID: <https://orcid.org/0000-0002-4674-4270>) |
| Maintainer | Angel Robles <a.l.robles.fernandez@gmail.com> |
| License | GPL (>= 3) |
| Version | 1.0.2 |
| URL | https://github.com/alrobles/xplus https://alrobles.github.io/xplus/ |
| Package repository | View on CRAN |
| Installation |
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