Publication | Open Access
PRROC: computing and visualizing precision-recall and receiver operating characteristic curves in R
440
Citations
9
References
2015
Year
EngineeringMachine LearningData ExplorationRoc CurvesStatistical AnalysisClassification MethodData ScienceData MiningPattern RecognitionManagementExploratory Data AnalysisAutomatic ClassificationR-package PrrocKnowledge DiscoveryIntelligent ClassificationComputer ScienceFunctional Data AnalysisData ClassificationGraphical AnalysisClassifier SystemPr CurvesData Modeling
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.
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