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Validation of Voting Committee

Bax, Eric (1997) Validation of Voting Committee. California Institute of Technology , Pasadena, CA. (Unpublished)

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This paper contains a method to bound the test errors of voting committees with members chosen from a pool of trained classifiers. There are so many prospective committees that validating them directly does not achieve useful error bounds. Because there are fewer classifiers than prospective committees, it is better to validate the classifiers individually, than use linear programming to infer committee error bounds. We test the method using credit card data. Also, we extend the method to infer bounds fro classifiers in general.

Item Type:Report or Paper (Technical Report)
Additional Information:© 1997 California Institute of Technology. Thanks to Joel Franklin for advice, teaching, and encouragement. Thanks to Yaser Abu-Mostafa for teaching, and thanks to Amir Atiya, Zehra Cataltepe, Malik Magdon-Ismail, Alexander Nicholson, Sam Roweis, Joseph Sill, and Xubo Song for useful pointers and discussions.
Group:Computer Science Technical Reports
Subject Keywords:machine learning, learning theory, fusion, committees, voting, vapnik-Chervonenkis, linear programming
Record Number:CaltechCSTR:1997.cs-tr-97-13
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Usage Policy:You are granted permission for individual, educational, research and non-commercial reproduction, distribution, display and performance of this work in any format.
ID Code:26898
Deposited By: Imported from CaltechCSTR
Deposited On:19 Jul 2001
Last Modified:03 Oct 2019 03:19

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