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: | 1.3.1 |
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Suggests: | testthat, ggplot2, ROCR |
Published: | 2018-06-19 |
DOI: | 10.32614/CRAN.package.PRROC |
Author: | Jan Grau and Jens Keilwagen |
Maintainer: | Jan Grau |
License: | GPL-3 |
NeedsCompilation: | no |
Citation: | PRROC citation info |
CRAN checks: | PRROC results |
Documentation:
Downloads:
Reverse dependencies:
Reverse imports: | biospear, DeepPINCS, FRASER, GroupBN, HPiP, ICBioMark, immunaut, mlr3measures, MSiP, OUTRIDER, prcbench, preciseTAD, priorityelasticnet, saseR, SIAMCAT, simtrait, usefun |
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Reverse suggests: | PheVis, WeightedROC |
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