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dc.contributor.authorNebot Troyano, Guillermo
dc.contributor.authorBelanche Muñoz, Luis Antonio
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics
dc.identifier.citationNebot, G.; Belanche, Ll. A kernel extension to handle missing data. A: SGAI International Conference on Artificial Intelligence. "Research and Development in Intelligent Systems XXVI". Cambridge: Springer-Verlag, 2009, p. 165-178.
dc.description.abstractAn extension for univariate kernels that deals with missing values is proposed. These extended kernels are shown to be valid Mercer kernels and can adapt to many types of variables, such as categorical or continuous. The proposed kernels are tested against standard RBF kernels in a variety of benchmark problems showing different amounts of missing values and variable types. Our experimental results are very satisfactory, because they usually yield slight to much better improvements over those achieved with standard methods.
dc.format.extent14 p.
dc.subjectÀrees temàtiques de la UPC::Informàtica::Sistemes operatius
dc.subject.lcshOperating systems (Computers)
dc.subject.otherUnivariate kernels
dc.subject.otherMissing values
dc.titleA kernel extension to handle missing data
dc.typeConference report
dc.subject.lemacSistemes operatius (Ordinadors)
dc.contributor.groupUniversitat Politècnica de Catalunya. SOCO - Soft Computing
dc.rights.accessOpen Access
dc.description.versionPostprint (author’s final draft)
upcommons.citation.authorNebot, G.; Belanche, Ll.
upcommons.citation.contributorSGAI International Conference on Artificial Intelligence
upcommons.citation.publicationNameResearch and Development in Intelligent Systems XXVI
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