Scoring Systems - At the Extreme of Interpretable Machine Learning - Cynthia Rudin - Duke University

Scoring Systems - At the Extreme of Interpretable Machine Learning - Cynthia Rudin - Duke University

Alan Turing Institute via YouTube Direct link

Intro

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1 of 22

Intro

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Scoring Systems - At the Extreme of Interpretable Machine Learning - Cynthia Rudin - Duke University

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  1. 1 Intro
  2. 2 Can a typo lead to extra prison time
  3. 3 Blackbox vs interpretable models
  4. 4 Are blackbox models more accurate
  5. 5 History of scoring systems
  6. 6 Designing optimal scoring systems
  7. 7 Elastic net example
  8. 8 Validation
  9. 9 RiskSlim
  10. 10 Cutting planes
  11. 11 Mixed integer programs
  12. 12 Lattice cutting plane
  13. 13 Recap
  14. 14 Applications
  15. 15 Accuracy
  16. 16 Criminal recidivism
  17. 17 ProPublica
  18. 18 Age vs Compass
  19. 19 Compass depends on race
  20. 20 Inputting data reliably
  21. 21 Compass is interpretable
  22. 22 Summary

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