title: PRROC: computing and visualizing precision-recall and receiver operating characteristic curves in R.
abstract: Precision-recall (PR) and receiver operating characteristic (ROC) curves are valuable measures of classifier performance. Here, we present the R-package PRROC, which allows for computing and visualizing both PR and ROC curves. In contrast to available R-packages, PRROC allows for computing PR and ROC curves and areas under these curves for soft-labeled data using a continuous interpolation between the points of PR curves. In addition, PRROC provides a generic plot function for generating publication-quality graphics of PR and ROC curves.
authors: Institute of Computer Science and Universitätszentrum Informatik, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany.
authors: Jan
authors: J
authors: Grau
authors: Institute of Computer Science and Universitätszentrum Informatik, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany, German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany and.
authors: Ivo
authors: I
authors: Grosse
authors: Institute for Biosafety in Plant Biotechnology, Julius Kühn-Institut (JKI) - Federal Research Centre for Cultivated Plants, Quedlinburg, Germany.
authors: Jens
authors: J
authors: Keilwagen
mesh_terms: D019540:Area Under Curve; D003196:Computer Graphics; D003627:Data Interpretation, Statistical; D006801:Humans; D008432:Mathematical Computing; D010363:Pattern Recognition, Automated; D012372:ROC Curve; D012984:Software; D014584:User-Computer Interface