Fast missing value imputation using ensemble of SOMs

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorSorjamaa, Antti
dc.contributor.authorLendasse, Amaury
dc.contributor.departmentDepartment of Information and Computer Scienceen
dc.contributor.departmentTietojenkäsittelytieteen laitosfi
dc.contributor.schoolFaculty of Information and Natural Sciencesen
dc.contributor.schoolInformaatio- ja luonnontieteiden tiedekuntafi
dc.date.accessioned2011-11-28T13:26:31Z
dc.date.available2011-11-28T13:26:31Z
dc.date.issued2010
dc.description.abstractThis report presents a methodology for missing value imputation. The methodology is based on an ensemble of Self-Organizing Maps (SOM), which is weighted using Nonnegative Least Squares algorithm. Instead of a need for lengthy validation procedure as when using single SOMs, the ensemble proceeds straight into final model building. Therefore, the methodology has very low computational time while retaining the accuracy. The performance is compared to other state-of-the-art methodologies using two real world databases from different fields.en
dc.format.extent20
dc.format.mimetypeapplication/pdf
dc.identifier.isbn978-952-60-3248-1
dc.identifier.issn1797-5042
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/911
dc.identifier.urnurn:nbn:fi:tkk-013167
dc.language.isoenen
dc.publisherAalto University School of Science and Technologyen
dc.publisherAalto-yliopiston teknillinen korkeakoulufi
dc.relation.ispartofseriesTKK reports in information and computer scienceen
dc.relation.ispartofseries33en
dc.subject.keywordself-organizing mapsen
dc.subject.keywordensemble of SOMsen
dc.subject.keywordmissing value imputationen
dc.subject.keywordnonnegative least squaresen
dc.subject.keywordfast computationen
dc.subject.otherComputer scienceen
dc.titleFast missing value imputation using ensemble of SOMsen
dc.type.dcmitypetexten
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