Precision-Recall and ROC Curves for Weighted and Unweighted Data

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) ; Keilwagen et al. (2014) ; Grau et al. (2015) .


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("PRROC")

1.4 by Jan Grau, 2 years ago


Browse source code at https://github.com/cran/PRROC


Authors: Jan Grau [aut, cre] , Jens Keilwagen [aut]


Documentation:   PDF Manual  


GPL-3 license


Depends on rlang

Suggests testthat, ggplot2, ROCR


Imported by DDESONN, E2E, GroupBN, ICBioMark, PEAXAI, PatientLevelPrediction, TSLA, autoFlagR, biospear, dagHMM, immunaut, mlr3measures, prcbench, priorityelasticnet, riskscores, simtrait, usefun.

Suggested by BioMoR, PheVis, WeightedROC, bioLeak, featR.


See at CRAN