mccf1: Creates the MCC-F1 Curve and Calculates the MCC-F1 Metric and the Best Threshold

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>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: mccf1 results


Reference manual: mccf1.pdf
Package source: mccf1_1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): mccf1_1.1.tgz, r-release (x86_64): mccf1_1.1.tgz, r-oldrel: mccf1_1.1.tgz
Old sources: mccf1 archive


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