DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, JH | - |
dc.contributor.author | Oh, SY | - |
dc.date.accessioned | 2017-07-19T12:48:45Z | - |
dc.date.available | 2017-07-19T12:48:45Z | - |
dc.date.created | 2016-02-15 | - |
dc.date.issued | 2016-03-17 | - |
dc.identifier.issn | 0013-5194 | - |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/36481 | - |
dc.description.abstract | A novel feature selection method based on geometric distance is proposed. It utilises both the average distance between classes along with the evenness of these distances to evaluate feature subsets. The feature evaluation and selection process used therein is very easy to understand, because it lends itself to a simple geometrical analysis. Moreover, because the method does not calculate the relevance or redundancy between features, it is faster than other filter methods that use information or statistical dependency concepts. The experiments demonstrate its markedly better classification performance as well as fast computation compared with existing methods. | - |
dc.language | English | - |
dc.publisher | IET | - |
dc.relation.isPartOf | ELECTRONICS LETTERS | - |
dc.title | Feature selection based on geometric distance for high-dimensional data | - |
dc.type | Article | - |
dc.identifier.doi | 10.1049/EL.2015.4172 | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | ELECTRONICS LETTERS, v.52, no.6, pp.473 - 474 | - |
dc.identifier.wosid | 000371860000034 | - |
dc.date.tcdate | 2019-02-01 | - |
dc.citation.endPage | 474 | - |
dc.citation.number | 6 | - |
dc.citation.startPage | 473 | - |
dc.citation.title | ELECTRONICS LETTERS | - |
dc.citation.volume | 52 | - |
dc.contributor.affiliatedAuthor | Oh, SY | - |
dc.identifier.scopusid | 2-s2.0-84960926967 | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
dc.description.wostc | 1 | - |
dc.description.scptc | 2 | * |
dc.date.scptcdate | 2018-05-121 | * |
dc.description.isOpenAccess | N | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | feature selection | - |
dc.subject.keywordAuthor | set theory | - |
dc.subject.keywordAuthor | statistical analysis | - |
dc.subject.keywordAuthor | geometric distance | - |
dc.subject.keywordAuthor | high-dimensional data | - |
dc.subject.keywordAuthor | feature selection method | - |
dc.subject.keywordAuthor | feature subset evaluation | - |
dc.subject.keywordAuthor | feature evaluation process | - |
dc.subject.keywordAuthor | feature selection process | - |
dc.subject.keywordAuthor | geometrical analysis | - |
dc.subject.keywordAuthor | statistical dependency concepts | - |
dc.subject.keywordAuthor | information dependency concepts | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
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