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Bagging likelihood-based belief decision trees
University of Jinan, CHI.
Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.ORCID iD: 0000-0001-5824-425X
University of Science and Technology of China, CHI.
2017 (English)In: 20th International Conference on Information Fusion, Fusion 2017: Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2017, 8009664Conference paper, Published paper (Refereed)
Abstract [en]

To embed ensemble techniques into belief decision trees for performance improvement, the bagging algorithm is explored. Simple belief decision trees based on entropy intervals extracted from evidential likelihood are constructed as the base classifiers, and a combination of individual trees promises to lead to a better classification accuracy. Requiring no extra querying cost, bagging belief decision trees can obtain good classification performance by simple belief tree combination, making it an alternative to single belief tree with querying. Experiments on UCI datasets verify the effectiveness of bagging approach. In various uncertain cases, the bagging method outperforms single belief tree without querying, and is comparable in accuracy to single tree with querying. © 2017 International Society of Information Fusion (ISIF).

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017. 8009664
Keyword [en]
bagging, belief function theory, decision trees, evidential likelihood, Decision theory, Forestry, Information fusion, Uncertainty analysis, Bagging algorithms, Bagging approach, Classification accuracy, Classification performance, Ensemble techniques, Trees (mathematics)
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:bth-15216DOI: 10.23919/ICIF.2017.8009664Scopus ID: 2-s2.0-85029439190ISBN: 9780996452700 OAI: oai:DiVA.org:bth-15216DiVA: diva2:1145526
Conference
20th International Conference on Information Fusion, Fusion, Xian
Available from: 2017-09-29 Created: 2017-09-29 Last updated: 2017-09-29Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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