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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 |
| 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 |
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These binaries (installable software) and packages are in development.
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