rocc: ROC Based Classification

Functions for a classification method based on receiver operating characteristics (ROC). Briefly, features are selected according to their ranked AUC value in the training set. The selected features are merged by the mean value to form a meta-gene. The samples are ranked by their meta-gene value and the meta-gene threshold that has the highest accuracy in splitting the training samples is determined. A new sample is classified by its meta-gene value relative to the threshold. In the first place, the package is aimed at two class problems in gene expression data, but might also apply to other problems.

Version: 1.3
Depends: ROCR
Imports: methods
Published: 2019-12-06
DOI: 10.32614/CRAN.package.rocc
Author: Martin Lauss
Maintainer: Martin Lauss <martin.lauss at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: rocc results


Reference manual: rocc.pdf


Package source: rocc_1.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): rocc_1.3.tgz, r-oldrel (arm64): rocc_1.3.tgz, r-release (x86_64): rocc_1.3.tgz, r-oldrel (x86_64): rocc_1.3.tgz
Old sources: rocc archive

Reverse dependencies:

Reverse suggests: fscaret


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