The Benefits of the Matthews Correlation Coefficient (MCC) Over the Diagnostic Odds Ratio (DOR) in Binary Classification Assessment

The Benefits of the Matthews Correlation Coefficient (MCC) Over the Diagnostic Odds Ratio (DOR) in Binary Classification Assessment

To assess the quality of a binary classification, researchers often take advantage of a four-entry contingency table called <italic>confusion matrix</italic>, containing true positives, true negatives, false positives, and false negatives. To recap the four values of a confusion matrix i...

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Bibliographic Details
Main Authors: Davide Chicco, Valery Starovoitov, Giuseppe Jurman
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Matthews correlation coefficient
diagnostic odds ratio
binary classification
confusion matrix
supervised machine learning
confusion tetrahedron
Online Access:https://ieeexplore.ieee.org/document/9385097/

Internet

https://ieeexplore.ieee.org/document/9385097/

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