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

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ROC_curve_example_highlighting_sub-area_with_low_sensitivity_and_low_specificity.png (403 × 412 pixels, file size: 42 KB, MIME type: image/png)

Captions

Captions

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

Summary

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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

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current13:41, 26 September 2023Thumbnail for version as of 13:41, 26 September 2023403 × 412 (42 KB)Larry.europe (talk | contribs)Uploaded a work by Davide Chicco and Giuseppe Jurman from 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 with UploadWizard

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