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, Rudin, Cynthia
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format: Article
Language:en_US
Published: Association for Computing Machinery (ACM) 2013
Online Access:http://hdl.handle.net/1721.1/81426

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