What is PU learning? | When to use xplus | Basic workflow | Model assessment
This package is considered a duplicate. The official version of this package is found at:https://alrobles.r-universe.dev/xplus
Package: xplus 1.0.2
Angel Robles
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.
Authors:
xplus_1.0.2.tar.gz
xplus_1.0.2.zip(r-4.7-any)xplus_1.0.2.zip(r-4.6-any)
xplus_1.0.2.tar.gz(r-4.7-any)xplus_1.0.2.tar.gz(r-4.6-any)
xplus_1.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
xplus/json (API)
| # Install 'xplus' in R: |
| install.packages('xplus', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/alrobles/xplus/issues
Pkgdown/docs site:https://alrobles.github.io
Datasets:
- binexample - Example binary labels dataset
- cutoff_example - Example cutoff values
- fit_xplus_example - Example fitted xplus object
- lacs - LACS dataset
- lacsSample - LACS sample dataset
- predicted_coefficients_example - Example predicted coefficients
- predicted_y_example - Example predicted probabilities
- xplus_object_example - Example xplus object
Last updated from:244c36d368. Checks:6 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 155 | ||
| source / vignettes | OK | 224 | ||
| linux-release | OK | 153 | ||
| windows-devel | OK | 97 | ||
| windows-release | OK | 98 | ||
| wasm-release | OK | 149 |
Exports:assessaucauc_matrixget_aucget_predictionsxplus
Dependencies:clicodetoolsforeachglmnetglueiteratorslatticelifecyclemagrittrMatrixpillarpkgconfigRcppRcppEigenrlangshapesurvivaltibbleutf8vctrs
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Assess predictive performance | assess assess.xplus |
| Compute area under the ROC curve | auc |
| Compute AUC from matrix labels | auc_matrix |
| Example binary labels dataset | binexample |
| Extract coefficients from an xplus model | coef.xplus |
| Example cutoff values | cutoff_example |
| Example fitted xplus object | fit_xplus_example |
| Compute AUC for predictions from a model | get_auc get_auc.xplus |
| Build a tidy prediction table | get_predictions |
| LACS dataset | lacs |
| LACS sample dataset | lacsSample |
| Predict from an xplus model | predict.xplus |
| Example predicted coefficients | predicted_coefficients_example |
| Example predicted probabilities | predicted_y_example |
| Print method for summary.xplus objects | print.summary.xplus |
| Print an xplus model | print.xplus |
| Summarize an xplus model | summary.xplus |
| Fit an xplus model | xplus |
| Example xplus object | xplus_object_example |