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Bioinformatics Advance Access published online on August 11, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti623
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oupjournals.org
Received March 10, 2005
Revised June 1, 2005
Accepted August 9, 2005

Applications note

ROCR: visualizing classifier performance in R

Tobias Sing 1* {dagger}, Oliver Sander 1 {dagger}, Niko Beerenwinkel 2, and Thomas Lengauer 1 {dagger}

1 Department of Computational Biology and Applied Algorithmics, Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany
2 Department of Mathematics, University of California, Berkeley, CA 94720-3840, USA

* To whom correspondence should be addressed.
Tobias Sing, E-mail: tobias.sing{at}mpi-sb.mpg.de


  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 which 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 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 parameters, ROCR combines flexibility with ease of usage.

Availability: http://rocr.bioinf.mpi-sb.mpg.de. ROCR can be used under the terms of the GNU General Public License. Running within R, it is platform-independent.

{dagger} work at MPI supported by EU NoE BioSapiens (LSHG-CT-2003-503265)
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