Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 강경태 | - |
dc.date.accessioned | 2023-06-23T01:29:46Z | - |
dc.date.available | 2023-06-23T01:29:46Z | - |
dc.date.issued | 2017-02 | - |
dc.identifier.citation | 한국컴퓨터정보학회논문지, v. 22, NO. 2, Page. 81.0-87.0 | - |
dc.identifier.issn | 1598-849X;2383-9945 | - |
dc.identifier.uri | https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE07113046 | en_US |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/182275 | - |
dc.description.abstract | Nowadays wine is increasingly enjoyed by a wider range of consumers, and wine certification and quality assessment are key elements in supporting the wine industry to develop new technologies for both wine making and selling processes. There have been many attempts to construct a more methodical approach to the assessment of wines, but most of them rely on objective decision rather than subjective judgement. In this paper, we propose a data mining approach to predict human wine taste preferences that is based on easily available analytical tests at the certification step. We used sequential forward selection and decision tree for this purpose. Experiments with the wine quality dataset from the UC Irvine Machine Learning Repository demonstrate the accuracies of 76.7% and 78.7% for red and white wines respectively. | - |
dc.description.sponsorship | the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2016-H8501-16-1018) supervised by the IITP (Institute for Information & communications Technology Promotion) | - |
dc.language | ko | - |
dc.publisher | 한국컴퓨터정보학회 | - |
dc.subject | Decision Tree | - |
dc.subject | Wine Quality | - |
dc.subject | Classification | - |
dc.subject | Sequential Forward Selection | - |
dc.title | 순차순방향선택 기반 특징 추출 및 의사나무를 이용한 와인 품질 측정 | - |
dc.title.alternative | Wine Quality Assessment Using a Decision Tree with the Features Recommended by the Sequential Forward Selection | - |
dc.type | Article | - |
dc.relation.no | 2 | - |
dc.relation.volume | 22 | - |
dc.identifier.doi | 10.9708/jksci.2017.22.02.081 | - |
dc.relation.page | 81.0-87.0 | - |
dc.relation.journal | 한국컴퓨터정보학회논문지 | - |
dc.contributor.googleauthor | 이승한 | - |
dc.contributor.googleauthor | 강경태 | - |
dc.contributor.googleauthor | 노동건 | - |
dc.sector.campus | E | - |
dc.sector.daehak | 소프트웨어융합대학 | - |
dc.sector.department | 인공지능학과 | - |
dc.identifier.pid | ktkang | - |
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