ROCR: visualizing classifier performance in R

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ID: 290007
2005
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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 parameters, ROCR combines flexibility with ease of usage.
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openalex_W2145126338 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Tobias Sing, Oliver Sander, Niko Beerenwinkel, Thomas Lengauer
Journal BMC Bioinformatics
Year 2005
DOI
10.1093/bioinformatics/bti623
URL
https://academic.oup.com/bioinformatics/article-pdf/21/20/3940/48980957/bioinformatics_21_20_3940.pdf
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