Learning customized and optimized lists of rules with mathematical programming
Abstract We introduce a mathematical programming approach to building rule lists, which are a type of interpretable, nonlinear, and logical machine learning classifier involving IF-THEN rules. Unlike traditional decision tree algorithms like CART and C5.0, this method does not use gre...
Main Authors: | Rudin, Cynthia, Ertekin, Şeyda |
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Other Authors: | Sloan School of Management |
Format: | Article |
Language: | English |
Published: |
Springer Berlin Heidelberg
2021
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Online Access: | https://hdl.handle.net/1721.1/131392 |
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