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Fast missing value imputation using ensemble of SOMs

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Sorjamaa, Antti
dc.contributor.author Lendasse, Amaury
dc.date.accessioned 2011-11-28T13:26:31Z
dc.date.available 2011-11-28T13:26:31Z
dc.date.issued 2010
dc.identifier.isbn 978-952-60-3248-1
dc.identifier.issn 1797-5042
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/911
dc.description.abstract This 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.extent 20
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Aalto University School of Science and Technology en
dc.publisher Aalto-yliopiston teknillinen korkeakoulu fi
dc.relation.ispartofseries TKK reports in information and computer science en
dc.relation.ispartofseries 33 en
dc.subject.other Computer science en
dc.title Fast missing value imputation using ensemble of SOMs en
dc.contributor.school Faculty of Information and Natural Sciences en
dc.contributor.school Informaatio- ja luonnontieteiden tiedekunta fi
dc.contributor.department Department of Information and Computer Science en
dc.contributor.department Tietojenkäsittelytieteen laitos fi
dc.subject.keyword self-organizing maps en
dc.subject.keyword ensemble of SOMs en
dc.subject.keyword missing value imputation en
dc.subject.keyword nonnegative least squares en
dc.subject.keyword fast computation en
dc.identifier.urn urn:nbn:fi:tkk-013167
dc.type.dcmitype text en

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