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: 1.0
Depends: R (≥ 3.3.3)
Imports: ROCR, ggplot2
Published: 2018-08-13
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

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Reference manual: mccf1.pdf
Package source: mccf1_1.0.tar.gz
Windows binaries: r-devel: mccf1_1.0.zip, r-release: mccf1_1.0.zip, r-oldrel: mccf1_1.0.zip
OS X binaries: r-release: mccf1_1.0.tgz, r-oldrel: mccf1_1.0.tgz

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