publication . Article . Other literature type . 2005

ROCR: visualizing classifier performance in R

Oliver Sander; Tobias Sing; Thomas Lengauer; Niko Beerenwinkel;
Open Access
  • Published: 11 Aug 2005 Journal: Bioinformatics, volume 21, pages 3,940-3,941 (issn: 1367-4803, eissn: 1460-2059, Copyright policy)
  • Publisher: Oxford University Press (OUP)
Abstract
Summary: ROCR is a package for evaluating and visualizing the performance of scoring classifiers in the statistical language R. It features over 25 performance measures that can be freely combined to create two-dimensional performance curves. Standard methods for investigating trade-offs between specific performance measures are available within a uniform framework, including receiver operating characteristic (ROC) graphs, precision/recall plots, lift charts and cost curves. ROCR integrates tightly with R's powerful graphics capabilities, thus allowing for highly adjustable plots. Being equipped with only three commands and reasonable default values for optional...
Subjects
free text keywords: Statistics and Probability, Computational Theory and Mathematics, Biochemistry, Molecular Biology, Computational Mathematics, Computer Science Applications, Graphics, Classifier (linguistics), Computer science, Receiver operating characteristic, Data mining, computer.software_genre, computer, Graph, Performance curves, Standard methods
Any information missing or wrong?Report an Issue