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.
|Author||Chang Cao [aut, cre], Michael Hoffman [aut], Davide Chicco [aut]|
|Maintainer||Chang Cao <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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