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An efficient multivariate feature ranking method for gene selection in high-dimensional microarray data
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Junghye | - |
dc.contributor.author | Choi, In Young | - |
dc.contributor.author | Jun, Chi-Hyuck | - |
dc.date.accessioned | 2024-05-02T05:42:23Z | - |
dc.date.available | 2024-05-02T05:42:23Z | - |
dc.date.created | 2024-04-19 | - |
dc.date.created | 2024-04-19 | - |
dc.date.issued | 2021-03 | - |
dc.identifier.citation | EXPERT SYSTEMS WITH APPLICATIONS, Vol.166 | - |
dc.identifier.issn | 0957-4174 | - |
dc.identifier.uri | https://hdl.handle.net/10371/200470 | - |
dc.description.abstract | Classification of microarray data plays a significant role in the diagnosis and prediction of cancer. However, its high-dimensionality (>tens of thousands) compared to the number of observations ( | - |
dc.language | 영어 | - |
dc.publisher | PERGAMON-ELSEVIER SCIENCE LTD | - |
dc.title | An efficient multivariate feature ranking method for gene selection in high-dimensional microarray data | - |
dc.type | Article | - |
dc.identifier.doi | 10.1016/j.eswa.2020.113971 | - |
dc.citation.journaltitle | EXPERT SYSTEMS WITH APPLICATIONS | - |
dc.identifier.wosid | 000598522500011 | - |
dc.identifier.scopusid | 2-s2.0-85092327251 | - |
dc.citation.volume | 166 | - |
dc.description.isOpenAccess | Y | - |
dc.contributor.affiliatedAuthor | Lee, Junghye | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.subject.keywordAuthor | Multivariate feature selection | - |
dc.subject.keywordAuthor | Gene selection | - |
dc.subject.keywordAuthor | High-dimensional data | - |
dc.subject.keywordAuthor | Microarray data | - |
dc.subject.keywordAuthor | Classification | - |
dc.subject.keywordAuthor | Multiclass | - |
dc.subject.keywordAuthor | Mixed-type data | - |
dc.subject.keywordAuthor | Markov blanket | - |
dc.subject.keywordAuthor | Ranking | - |
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- Graduate School of Engineering Practice
- Department of Engineering Practice
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