Feature selection for multi-label classification using multivariate mutual information
DC Field | Value | Language |
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dc.contributor.author | Lee, Jaesung | - |
dc.contributor.author | Kim, Dae-Won | - |
dc.date.available | 2019-03-09T02:03:22Z | - |
dc.date.issued | 2013-02 | - |
dc.identifier.issn | 0167-8655 | - |
dc.identifier.issn | 1872-7344 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/14855 | - |
dc.description.abstract | Recently, classification tasks that naturally emerge in multi-label domains, such as text categorization, automatic scene annotation, and gene function prediction, have attracted great interest. As in traditional single-label classification, feature selection plays an important role in multi-label classification. However, recent feature selection methods require preprocessing steps that transform the label set into a single label, resulting in subsequent additional problems. In this paper, we propose a feature selection method for multi-label classification that naturally derives from mutual information between selected features and the label set. The proposed method was applied to several multi-label classification problems and compared with conventional methods. The experimental results demonstrate that the proposed method improves the classification performance to a great extent and has proved to be a useful method in selecting features for multi-label classification problems. (C) 2012 Elsevier B.V. All rights reserved. | - |
dc.format.extent | 9 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | ELSEVIER SCIENCE BV | - |
dc.title | Feature selection for multi-label classification using multivariate mutual information | - |
dc.type | Article | - |
dc.identifier.doi | 10.1016/j.patrec.2012.10.005 | - |
dc.identifier.bibliographicCitation | PATTERN RECOGNITION LETTERS, v.34, no.3, pp 349 - 357 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.wosid | 000315013000015 | - |
dc.identifier.scopusid | 2-s2.0-84870668654 | - |
dc.citation.endPage | 357 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 349 | - |
dc.citation.title | PATTERN RECOGNITION LETTERS | - |
dc.citation.volume | 34 | - |
dc.type.docType | Article | - |
dc.publisher.location | 네델란드 | - |
dc.subject.keywordAuthor | Multi-label feature selection | - |
dc.subject.keywordAuthor | Multivariate feature selection | - |
dc.subject.keywordAuthor | Multivariate mutual information | - |
dc.subject.keywordAuthor | Label dependency | - |
dc.subject.keywordPlus | TEXT CATEGORIZATION | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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