The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
The MCC-F1 analysis is a method to evaluate the performance of binary classifications. The MCC-F1 curve is more reliable than the Receiver Operating Characteristic (ROC) curve and the Precision-Recall (PR)curve under imbalanced ground truth. The MCC-F1 analysis also provides the MCC-F1 metric that integrates classifier performance over varying thresholds, and the best threshold of binary classification.
Version: | 1.1 |
Depends: | R (≥ 3.3.3), ggplot2 |
Imports: | ROCR |
Published: | 2019-11-11 |
DOI: | 10.32614/CRAN.package.mccf1 |
Author: | Chang Cao [aut, cre], Michael Hoffman [aut], Davide Chicco [aut] |
Maintainer: | Chang Cao <kirin.cao at mail.utoronto.ca> |
BugReports: | https://stackoverflow.com/questions/tagged/mccf1 |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | https://bitbucket.org/hoffmanlab/mccf1/ |
NeedsCompilation: | no |
CRAN checks: | mccf1 results |
Reference manual: | mccf1.pdf |
Package source: | mccf1_1.1.tar.gz |
Windows binaries: | r-devel: mccf1_1.1.zip, r-release: mccf1_1.1.zip, r-oldrel: mccf1_1.1.zip |
macOS binaries: | r-release (arm64): mccf1_1.1.tgz, r-oldrel (arm64): mccf1_1.1.tgz, r-release (x86_64): mccf1_1.1.tgz, r-oldrel (x86_64): mccf1_1.1.tgz |
Old sources: | mccf1 archive |
Please use the canonical form https://CRAN.R-project.org/package=mccf1 to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.