Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application to Credit-Risk Evaluation
Publication
, Journal Article
Rudin, C; Shaposhnik, Y
Published in: https://www.jmlr.org/papers/
May 28, 2019
Duke Scholars
Published In
https://www.jmlr.org/papers/
Publication Date
May 28, 2019
Volume
24
Related Subject Headings
- Artificial Intelligence & Image Processing
- 4905 Statistics
- 4611 Machine learning
- 17 Psychology and Cognitive Sciences
- 08 Information and Computing Sciences
Citation
APA
Chicago
ICMJE
MLA
NLM
Rudin, C., & Shaposhnik, Y. (2019). Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application to Credit-Risk Evaluation. Https://Www.Jmlr.Org/Papers/, 24.
Rudin, Cynthia, and Yaron Shaposhnik. “Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application to Credit-Risk Evaluation.” Https://Www.Jmlr.Org/Papers/ 24 (May 28, 2019).
Rudin C, Shaposhnik Y. Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application to Credit-Risk Evaluation. https://www.jmlr.org/papers/. 2019 May 28;24.
Rudin, Cynthia, and Yaron Shaposhnik. “Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application to Credit-Risk Evaluation.” Https://Www.Jmlr.Org/Papers/, vol. 24, May 2019.
Rudin C, Shaposhnik Y. Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application to Credit-Risk Evaluation. https://www.jmlr.org/papers/. 2019 May 28;24.
Published In
https://www.jmlr.org/papers/
Publication Date
May 28, 2019
Volume
24
Related Subject Headings
- Artificial Intelligence & Image Processing
- 4905 Statistics
- 4611 Machine learning
- 17 Psychology and Cognitive Sciences
- 08 Information and Computing Sciences