ROCR: Visualizing classifier performance in R

2.4kCitations
Citations of this article
1.4kReaders
Mendeley users who have this article in their library.

This article is free to access.

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. © The Author 2005. Published by Oxford University Press. All rights reserved.

Cite

CITATION STYLE

APA

Sing, T., Sander, O., Beerenwinkel, N., & Lengauer, T. (2005). ROCR: Visualizing classifier performance in R. Bioinformatics, 21(20), 3940–3941. https://doi.org/10.1093/bioinformatics/bti623

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free