https://github.com/tsabsch/goldeneye

Python implementation of the goldeneye algorithm to investigate how classifiers utilise the structure of a dataset.
https://github.com/tsabsch/goldeneye

data-science model-explanation

Last synced: about 1 year ago
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Python implementation of the goldeneye algorithm to investigate how classifiers utilise the structure of a dataset.

• Host: GitHub
• URL: https://github.com/tsabsch/goldeneye
• Owner: tsabsch
• License: mit
• Created: 2017-11-28T19:13:54.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2018-02-05T15:42:24.000Z (over 8 years ago)
• Last Synced: 2025-01-17T15:28:05.504Z (over 1 year ago)
• Topics: data-science, model-explanation
• Language: Python
• Size: 6.84 KB
• Stars: 2
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# goldeneye

Python implementation of the GoldenEye algorithm to investigate how classifiers utilise the structure of a dataset.

The original R implementation can be found at https://bitbucket.org/aheneliu/goldeneye

## References

Henelius, Andreas, et al. "A peek into the black box: exploring classifiers by randomization." Data mining and knowledge discovery 28.5-6 (2014): 1503-1529.

Henelius, Andreas, et al. "Goldeneye++: A closer look into the black box." International Symposium on Statistical Learning and Data Sciences. Springer, Cham, 2015.