File:ROC curve example highlighting sub-area with low sensitivity and low specificity.png

Summary

Description
English: Example of receiver operating characteristic (ROC) curve highlighting the area under the curve (AUC) sub-area with low sensitivity and low specificity in red and the sub-area with high or sufficient sensitivity and specificity in green
Date
Source Davide Chicco, Giuseppe Jurman, "The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification", BioData Mining 16, 4 (2023). https://doi.org/10.1186/s13040-023-00322-4
Author Davide Chicco and Giuseppe Jurman

Licensing

w:en:Creative Commons
attribution
This file is licensed under the Creative Commons Attribution 4.0 International license.
You are free:
  • to share – to copy, distribute and transmit the work
  • to remix – to adapt the work
Under the following conditions:
  • attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
Category:CC-BY-4.0#ROC%20curve%20example%20highlighting%20sub-area%20with%20low%20sensitivity%20and%20low%20specificity.png Category:Statistics Category:Machine learning research Category:Metrics Category:Machine learning
Category:CC-BY-4.0 Category:Machine learning Category:Machine learning research Category:Metrics Category:Statistics