PRROC: Precision-Recall and ROC Curves for Weighted and Unweighted Data

Computes the areas under the precision-recall (PR) and ROC curve for weighted (e.g., soft-labeled) and unweighted data. In contrast to other implementations, the interpolation between points of the PR curve is done by a non-linear piecewise function. In addition to the areas under the curves, the curves themselves can also be computed and plotted by a specific S3-method.

AuthorJan Grau and Jens Keilwagen
Date of publication2015-02-26 02:14:52
MaintainerJan Grau <grau@informatik.uni-halle.de>
LicenseGPL-3
Version1.1

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Files

PRROC
PRROC/inst
PRROC/inst/CITATION
PRROC/inst/tests
PRROC/inst/tests/test-ROC.R
PRROC/inst/tests/test-PR.R
PRROC/inst/doc
PRROC/inst/doc/PRROC.R
PRROC/inst/doc/PRROC.Rnw
PRROC/inst/doc/PRROC.pdf
PRROC/tests
PRROC/tests/all_tests.R
PRROC/NAMESPACE
PRROC/R
PRROC/R/PRROC.R
PRROC/vignettes
PRROC/vignettes/PRROC.Rnw
PRROC/MD5
PRROC/build
PRROC/build/vignette.rds
PRROC/DESCRIPTION
PRROC/man
PRROC/man/PRROC-package.Rd PRROC/man/pr.curve.Rd PRROC/man/roc.curve.Rd PRROC/man/print.PRROC.Rd PRROC/man/plot.PRROC.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

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