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Learning optimized risk scores

Publication ,  Journal Article
Ustun, B; Rudin, C
Published in: Journal of Machine Learning Research
June 1, 2019

Risk scores are simple classification models that let users make quick risk predictions by adding and subtracting a few small numbers. These models are widely used in medicine and criminal justice, but are difficult to learn from data because they need to be calibrated, sparse, use small integer coefficients, and obey application-specific constraints. In this paper, we introduce a machine learning method to learn risk scores. We formulate the risk score problem as a mixed integer nonlinear program, and present a cutting plane algorithm to recover its optimal solution. We improve our algorithm with specialized techniques that generate feasible solutions, narrow the optimality gap, and reduce data-related computation. Our algorithm can train risk scores in a way that scales linearly in the number of samples in a dataset, and that allows practitioners to address application-specific constraints without parameter tuning or post-processing. We benchmark the performance of different methods to learn risk scores on publicly available datasets, comparing risk scores produced by our method to risk scores built using methods that are used in practice. We also discuss the practical benefits of our method through a real-world application where we build a customized risk score for ICU seizure prediction in collaboration with the Massachusetts General Hospital.

Duke Scholars

Published In

Journal of Machine Learning Research

EISSN

1533-7928

ISSN

1532-4435

Publication Date

June 1, 2019

Volume

20

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 4905 Statistics
  • 4611 Machine learning
  • 17 Psychology and Cognitive Sciences
  • 08 Information and Computing Sciences
 

Citation

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Ustun, B., & Rudin, C. (2019). Learning optimized risk scores. Journal of Machine Learning Research, 20.
Ustun, B., and C. Rudin. “Learning optimized risk scores.” Journal of Machine Learning Research 20 (June 1, 2019).
Ustun B, Rudin C. Learning optimized risk scores. Journal of Machine Learning Research. 2019 Jun 1;20.
Ustun, B., and C. Rudin. “Learning optimized risk scores.” Journal of Machine Learning Research, vol. 20, June 2019.
Ustun B, Rudin C. Learning optimized risk scores. Journal of Machine Learning Research. 2019 Jun 1;20.

Published In

Journal of Machine Learning Research

EISSN

1533-7928

ISSN

1532-4435

Publication Date

June 1, 2019

Volume

20

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 4905 Statistics
  • 4611 Machine learning
  • 17 Psychology and Cognitive Sciences
  • 08 Information and Computing Sciences