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Short Note on Optimizing Feature Selection to Improve Medical Diagnosis
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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | 곽취(Cui Guo) | - |
| dc.contributor.author | 류홍서 | - |
| dc.date.accessioned | 2021-09-05T14:12:38Z | - |
| dc.date.available | 2021-09-05T14:12:38Z | - |
| dc.date.created | 2021-06-17 | - |
| dc.date.issued | 2014 | - |
| dc.identifier.issn | 1225-1119 | - |
| dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/100275 | - |
| dc.description.abstract | A new classification framework called ‘support feature machine’ was introduced in [2] for analyzing medical data. Contrary to authors’ claim, however, the proposed method is not designed to guarantee minimizing the use of the spatial feature variables. This paper mathematically remedies this drawback and provides comments on models from [2]. | - |
| dc.language | English | - |
| dc.language.iso | en | - |
| dc.publisher | 한국경영과학회 | - |
| dc.title | Short Note on Optimizing Feature Selection to Improve Medical Diagnosis | - |
| dc.title.alternative | Short Note on Optimizing Feature Selection to Improve Medical Diagnosis | - |
| dc.type | Article | - |
| dc.contributor.affiliatedAuthor | 류홍서 | - |
| dc.identifier.doi | 10.7737/JKORMS.2014.39.4.071 | - |
| dc.identifier.bibliographicCitation | 한국경영과학회지, v.39, no.4, pp.71 - 74 | - |
| dc.relation.isPartOf | 한국경영과학회지 | - |
| dc.citation.title | 한국경영과학회지 | - |
| dc.citation.volume | 39 | - |
| dc.citation.number | 4 | - |
| dc.citation.startPage | 71 | - |
| dc.citation.endPage | 74 | - |
| dc.type.rims | ART | - |
| dc.identifier.kciid | ART001933236 | - |
| dc.description.journalClass | 2 | - |
| dc.description.journalRegisteredClass | kci | - |
| dc.subject.keywordAuthor | Support Features | - |
| dc.subject.keywordAuthor | Feature Selection | - |
| dc.subject.keywordAuthor | Integer Programming | - |
| dc.subject.keywordAuthor | Multiobjective Programming | - |
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