ROCR: visualizing classifier performance in R

被引:2409
作者
Sing, T
Sander, O
Beerenwinkel, N
Lengauer, T
机构
[1] Max Planck Inst Informat, Dept Computat Biol & Appl Algorithm, D-66123 Saarbrucken, Germany
[2] Univ Calif Berkeley, Dept Math, Berkeley, CA 94720 USA
关键词
D O I
10.1093/bioinformatics/bti623
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:3940 / 3941
页数:2
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