Assessing wine quality using a decision tree

Lee, Seunghan; Park, Juyoung; Kang, Kyungtae

doi:10.1109/SysEng.2015.7302752

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Assessing wine quality using a decision tree

Lee, Seunghan;
Park, Juyoung;
Kang, Kyungtae

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11

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21

초록

Even though wine-drinkers generally agree that wines may be ranked by quality, wine-tasting is famously subjective. There have been many attempts to construct a more methodical approach to the assessment of wines. We propose a method of assessing wine quality using a decision tree, and test it against the wine-quality dataset from the UC Irvine Machine Learning Repository. Results are 60% in agreement with traditional assessment techniques. © 2015 IEEE.

키워드

Artificial intelligence; Decision trees; Learning systems; Statistical tests; Systems engineering; Machine learning repository; Methodical approach; Traditional assessment; Wine quality; Wine tasting; Wine; Artificial intelligence; Decision trees; Learning systems; Statistical tests; Systems engineering; Machine learning repository; Methodical approach; Traditional assessment; Wine quality; Wine tasting; Wine

제목: Assessing wine quality using a decision tree

저자: Lee, Seunghan; Park, Juyoung; Kang, Kyungtae

DOI: 10.1109/SysEng.2015.7302752

발행일: 2015-09

유형: Conference Paper

저널명: 1st IEEE International Symposium on Systems Engineering, ISSE 2015 - Proceedings

페이지: 176 ~ 178

언어: ENG

출판사: Institute of Electrical and Electronics Engineers Inc.

발행국가: 미국

분량: 3 페이지