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dc.contributor.authorValdovinos Rosas, Rosa María
dc.contributor.authorSánchez Garreta, José Salvador
dc.date.accessioned2014-06-26T10:23:10Z
dc.date.available2014-06-26T10:23:10Z
dc.date.issued2009
dc.identifier.citationVALDOVINOS, R.M., SÁNCHEZ, J.S. Combining Multiple Classifiers with Dynamic Weighted Voting. En: Hybrid Artificial Intelligence Systems: 4th International Conference, HAIS 2009, Salamanca, Spain, June 10-12, 2009. Proceedings, p. 510-516. Springer Berlin Heidelberg, 2009. (Lecture Notes in Computer Science; 5572) ISBN 978-3-642-02319-4ca_CA
dc.identifier.isbn978-3-642-02319-4
dc.identifier.urihttp://hdl.handle.net/10234/96173
dc.description.abstractWhen a multiple classifier system is employed, one of the most popular methods to accomplish the classifier fusion is the simple majority voting. However, when the performance of the ensemble members is not uniform, the efficiency of this type of voting generally results affected negatively. In this paper, new functions for dynamic weighting in classifier fusion are introduced. Experimental results demonstrate the advantages of these novel strategies over the simple voting scheme.ca_CA
dc.format.extent6 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherSpringer Berlin Heidelbergca_CA
dc.relation.isPartOfSeriesLecture Notes in Computer Science;5572
dc.subjectmultiple classifier systemca_CA
dc.subjectdynamic weighting votingca_CA
dc.titleCombining Multiple Classifiers with Dynamic Weighted Votingca_CA
dc.typeinfo:eu-repo/semantics/bookPartca_CA
dc.identifier.doihttp://dx.doi.org/10.1007/978-3-642-02319-4_61
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.relation.publisherVersionhttp://link.springer.com/chapter/10.1007/978-3-642-02319-4_61ca_CA


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