PRROC: Precision-Recall and ROC Curves for Weighted and Unweighted Data (original) (raw)
Computes the areas under the precision-recall (PR) and ROC curve for weighted (e.g., soft-labeled) and unweighted data. In contrast to other implementations, the interpolation between points of the PR curve is done by a non-linear piecewise function. In addition to the areas under the curves, the curves themselves can also be computed and plotted by a specific S3-method. References: Davis and Goadrich (2006) <doi:10.1145/1143844.1143874>; Keilwagen et al. (2014) <doi:10.1371/journal.pone.0092209>; Grau et al. (2015) <doi:10.1093/bioinformatics/btv153>.
| Version: | 1.4 |
|---|---|
| Depends: | rlang |
| Suggests: | testthat, ggplot2, ROCR |
| Published: | 2025-03-18 |
| DOI: | 10.32614/CRAN.package.PRROC |
| Author: | Jan Grau [aut, cre], Jens Keilwagen [aut] |
| Maintainer: | Jan Grau |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Citation: | PRROC citation info |
| CRAN checks: | PRROC results |
Documentation:
Downloads:
Reverse dependencies:
| Reverse imports: | biospear, dagHMM, DeepPINCS, E2E, FRASER, GroupBN, ICBioMark, immunaut, mlr3measures, MSiP, OUTRIDER, PatientLevelPrediction, prcbench, preciseTAD, priorityelasticnet, saseR, SIAMCAT, simtrait, TSLA, usefun |
|---|---|
| Reverse suggests: | BioMoR, PheVis, WeightedROC |
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