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dc.contributor.authorRaudys, Šarūnas
dc.date.accessioned2023-09-18T18:53:13Z
dc.date.available2023-09-18T18:53:13Z
dc.date.issued2002
dc.identifier.issn0302-9743
dc.identifier.other(BIS)VGT02-000005114
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/132811
dc.description.abstractParallels between Feature Extraction / Selection and Multiple Classification Systems methodologies are considered. Both approaches allow the designer to introduce prior information about the pattern recognition task to be solved. However, both are heavily affected by computational difficulties and by the problem of small sample size/classifier complexity. Neither approach is capable of selecting a unique data analysis algorithm.eng
dc.format.extentp. 27-41
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.titleMultiple classification systems in the context of feature extraction and selection
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.facultyFundamentinių mokslų fakultetas / Faculty of Fundamental Sciences
dc.subject.researchfieldT 007 - Informatikos inžinerija / Informatics engineering
dcterms.sourcetitleMultiple Classifer Systems : Third International Workshop : Proceedings "MCS 2002", Cagliari, Italy, June 24-26, 2002. Lecture Notes in Computer Science
dc.description.volumeVol. 2364
dc.publisher.nameSpringer
dc.publisher.cityBerlin
dc.identifier.elaba3621300


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