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On Evidential Combination Rules for Ensemble Classifiers
University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
2008 (English)In: Proceedings of the 11th International Conference on Information Fusion, IEEE , 2008, 553-560 p.Conference paper, (Refereed)
Abstract [en]

Ensemble classifiers are known to generally perform better than each individual classifier of which they consist. One approach to classifier fusion is to apply Shafer’s theory of evidence. While most approaches have adopted Dempster’s rule of combination, a multitude of combination rules have been proposed. A number of combination rules as well as two voting rules are compared when used in conjunction with a specific kind of ensemble classifier, known as random forests, w.r.t. accuracy, area under ROC curve and Brier score on 27 datasets. The empirical evaluation shows that the choice of combination rule can have a significant impact on the performance for a single dataset, but in general the evidential combination rules do not perform better than the voting rules for this particular ensemble design. Furthermore, among the evidential rules, the associative ones appear to have better performance than the non-associative.

Place, publisher, year, edition, pages
IEEE , 2008. 553-560 p.
Keyword [en]
Ensemble classifiers, random forests, evidence theory, Dempster-Shafer theory, combination rules
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-3606DOI: 10.1109/ICIF.2008.4632259Scopus ID: 2-s2.0-56749142942ISBN: 978-3-00-024883-2 OAI: oai:DiVA.org:his-3606DiVA: diva2:291094
Available from: 2010-01-29 Created: 2010-01-29 Last updated: 2013-03-15

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Boström, HenrikJohansson, RonnieKarlsson, Alexander
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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
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Output format
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  • asciidoc
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