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ROCR: visualizing classifier performance in R

Tobias Sing,Oliver Sander,Niko Beerenwinkel,Thomas Lengauer

Computer science

Receiver operating characteristic

Lift (data mining)

2005

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 parameters, ROCR combines flexibility with ease of usage.

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“ROCR: visualizing classifier performance in R” is a paper by Tobias Sing Oliver Sander Niko Beerenwinkel Thomas Lengauer published in 2005. It has an Open Access status of “bronze”. You can read and download a PDF Full Text of this paper here.