MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

uBoost: a boosting method for producing uniform selection efficiencies from multivariate classifiers

Author(s)
Stevens, Justin; Williams, Michael
Thumbnail
DownloadWilliams_uBoost.pdf (762.1Kb)
OPEN_ACCESS_POLICY

Open Access Policy

Creative Commons Attribution-Noncommercial-Share Alike

Terms of use
Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/
Metadata
Show full item record
Abstract
The use of multivariate classifiers, especially neural networks and decision trees, has become commonplace in particle physics. Typically, a series of classifiers is trained rather than just one to enhance the performance; this is known as boosting. This paper presents a novel method of boosting that produces a uniform selection efficiency in a selected multivariate space. Such a technique is well suited for amplitude analyses or other situations where optimizing a single integrated figure of merit is not what is desired.
Date issued
2013-12
URI
http://hdl.handle.net/1721.1/88588
Department
Massachusetts Institute of Technology. Department of Physics; Massachusetts Institute of Technology. Laboratory for Nuclear Science
Journal
Journal of Instrumentation
Publisher
IOP Publishing
Citation
Stevens, J, and M Williams. “uBoost: a Boosting Method for Producing Uniform Selection Efficiencies from Multivariate Classifiers.” Journal of Instrumentation 8, no. 12 (December 23, 2013): P12013–P12013.
Version: Author's final manuscript
ISSN
1748-0221

Collections
  • MIT Open Access Articles

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.