ROCR

Visualizing the Performance of Scoring Classifiers


Licenses
CNRI-Python-GPL-Compatible/CNRI-Python-GPL-Compatible

Documentation

Please support our work by citing the ROCR article in your publications:
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Sing T, Sander O, Beerenwinkel N, Lengauer T. [2005]
ROCR: visualizing classifier performance in R.
Bioinformatics 21(20):3940-1. 

Free full text:
http://bioinformatics.oxfordjournals.org/content/21/20/3940.full


Getting started with ROCR:
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* After installation (cf. file 'INSTALL'), and starting R,
  load the package with 'library(ROCR)'.

* For a short overview of ROCR:
  demo(ROCR)

* For an overview of ROCR's online help: 
  help(package=ROCR)

* ROCR help pages:
  help(prediction)
  help(performance)
  help(plot.performance)
  help('prediction-class')
  help('performance-class')
  
* For more information, visit the ROCR website:
  http://rocr.bioinf.mpi-sb.mpg.de

* Good luck!