https://github.com/yandexdataschool/roc_comparison

The fast version of DeLong's method for computing the covariance of unadjusted AUC.
https://github.com/yandexdataschool/roc_comparison

data-science statistics

Last synced: about 2 hours ago
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The fast version of DeLong's method for computing the covariance of unadjusted AUC.

• Host: GitHub
• URL: https://github.com/yandexdataschool/roc_comparison
• Owner: yandexdataschool
• License: mit
• Created: 2017-09-07T10:36:39.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2022-07-13T15:47:34.000Z (over 2 years ago)
• Last Synced: 2023-10-20T23:54:37.249Z (about 1 year ago)
• Topics: data-science, statistics
• Language: Python
• Homepage:
• Size: 18.6 KB
• Stars: 116
• Watchers: 12
• Forks: 38
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
A Python implementation of an algorithm for computing the statistical significance of comparing two sets of predictions by ROC AUC. Also can compute variance of a single ROC AUC estimate. [X. Sun and W. Xu, "Fast Implementation of DeLong’s Algorithm for Comparing the Areas Under Correlated Receiver Operating Characteristic Curves," in IEEE Signal Processing Letters, vol. 21, no. 11, pp. 1389-1393, Nov. 2014, doi: 10.1109/LSP.2014.2337313.](https://doi.org/10.1109/LSP.2014.2337313)