Deep ROC analysis and AUC as balanced average accuracy, for improved classifier selection, audit and explanation

Carrington, A.M., Manuel, D.G., Fieguth, P. et al. (9 more authors) (2022) Deep ROC analysis and AUC as balanced average accuracy, for improved classifier selection, audit and explanation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45 (1). pp. 329-341. ISSN 0162-8828

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Item Type: Article
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© 2022 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Keywords: Sensitivity; Area measurement; Hospitals; Predictive models; Analytical models; Measurement uncertainty; Licenses
Dates:
  • Published: 25 January 2022
  • Published (online): 25 January 2022
  • Accepted: 19 January 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 16 Nov 2022 11:33
Last Modified: 26 Jun 2024 03:28
Status: Published
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Refereed: Yes
Identification Number: 10.1109/tpami.2022.3145392
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