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 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

Documentation:

Reference manual:

mccf1.pdf

Downloads:

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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