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.


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1.1 by Chang Cao, a year ago

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Authors: Chang Cao [aut, cre] , Michael Hoffman [aut] , Davide Chicco [aut]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports ROCR

Depends on ggplot2

See at CRAN