Machine Learning with Operational Costs

This work proposes a way to align statistical modeling with decision making. We provide a method that propagates the uncertainty in predictive modeling to the uncertainty in operational cost, where operational cost is the amount spent by the practitioner in solving the problem. The method allows us...

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Bibliographic Details
Main Authors: Tulabandhula, Theja (Contributor), Rudin, Cynthia (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Operations Research Center (Contributor), Sloan School of Management (Contributor)
Format: Article
Language:English
Published: Association for Computing Machinery (ACM), 2013-10-18T13:26:17Z.
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