Research on red wine quality prediction model based on Deep Learning architecture.
Pages 80 - 85
Abstract
The quality control and classification of wine during the winemaking process are of great importance. Therefore, wineries must obtain information related to wine quality during red wine fermentation and aging through a fast, simple, accurate, and economical approach. In this research paper, we focus on the quality of red wine and have taken various measures to evaluate our proposed framework, such as accuracy and sensitivity. The introduced LGBM model significantly improves prediction accuracy and compares the performance of the proposed framework with existing literature. The results show that our framework achieves an accuracy of 81.5%, surpassing previous works. This will aid wine manufacturers in controlling quality before producing wine.
References
[1]
Andrew L Waterhouse, Gavin L Sacks, and David W Jeffery. Understanding wine chemistry. John Wiley & Sons,2016.
[2]
KR Dahal, JN Dahal, H Banjade, and S Gaire. Prediction of wine quality using machine learning algorithms. Open Journal of Statistics, 11(2):278–289, 2021.Chelsea Finn. 2018. Learning to Learn with Gradients. PhD Thesis, EECS Department, University of Berkeley.
[3]
Sunny Kumar, Kanika Agrawal, and Nelshan Mandan. Red wine quality prediction using machine learning techniques. In 2020 International Conference on Computer Communication and Informatics (ICCCI), pages 1–6. IEEE, 2020.
[4]
Bipul Shaw, Ankur Kumar Suman, and Biswarup Chakraborty. Wine quality analysis using machine learning. In Emerging technology in modeling and graphics, pages 239–247. Springer, 2020.
[5]
Ujjawal Gupta, Yatindra Patidar, Abhishek Agarwal, Kushal Pal Singh, Wine quality analysis using machine learning algorithms. In Micro-Electronics and Telecommunication Engineering, pages 11–18. Springer, 2020.
[6]
Piyush Bhardwaj, Parul Tiwari, Kenneth Olejar Jr., Wendy Parr, and Don Kulasiri. A machine learning application in wine quality prediction. Machine Learning with Applications, 8:100261, 2022.
[7]
Paulo Cortez, António Cerdeira, Fernando Almeida, Telmo Matos, and José Reis. Modeling wine preferences by data mining from physicochemical properties. Decision support systems, 47(4):547–553, 2009.
[8]
Vapnik VN (1999) The nature of statistical learning theory. Information science and statistics, 2nd ed. Springer, New York. https://doi.org/10.1007/978-1-4757-3264-1.
[9]
Wei CC (2012) Receiver operating characteristic for diagnosis of wine quality by Bayesian network classifiers. AMR 591–593:1168–1173. https://doi.org/10.4028/www.scientifc.net/amr.591-593.1168.
[10]
World Health Organization (2003) Diet, nutrition, and the prevention of chronic diseases: report of a Joint WHO, FAO Expert Consultation [Geneva, 28 January - 1 2003 Diet, nutrition, and the prevention of chronic diseases: report of a Joint WHO/FAO Expert Consultation [Geneva, 28 January - 1 February 2002]. Accessed May 12, 2022.
[11]
World. Food safety. Who. int. Published April 30, 2020. Accessed May 12, 2022. https://www.who.int/news-room/fact-sheets/detail/food-safety.
[12]
Ye C, Li K, Jia, GZ (2020) A new red wine prediction framework using machine learning. In Journal of Physics: Conference Series 1684(1):012067 IOP Publishing.
Index Terms
- Research on red wine quality prediction model based on Deep Learning architecture.
Recommendations
Construction of Wine Quality Prediction Model based on Machine Learning Algorithm
AIVR 2021: 2021 5th International Conference on Artificial Intelligence and Virtual Reality (AIVR)In the study, our group choose a set of quality of red wine as data set. To get a more accurate result, we turn the quality into binary classification. And we try to build models to predict the quality of red wine based on machine learning algorithms, ...
A Hybrid Wine Classification Model for Quality Prediction
Pattern Recognition. ICPR International Workshops and ChallengesAbstract“Wine is bottled poetry” a quote from Robert Louis Stevenson shows the wine is an exciting and complex product with distinctive qualities that make it different from other products. Therefore, the testing approach to determine the quality of the ...
Quality evaluation of tourmaline red based on uniform color space
Based on the uniform color space $$\hbox {CIE}\,1976\hbox {L}^{{*}}\hbox {a}^{{*}}\hbox {b}^{{*}},$$CIE1976Lźaźbź, the red colors of 310 tourmalines were conducted with the research of color colorimetry. In terms of the quantitative analysis of color ...
Comments
Information & Contributors
Information
Published In
September 2023
441 pages
ISBN:9798400707667
DOI:10.1145/3627377
Copyright © 2023 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 04 December 2023
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
ICBDT 2023
ICBDT 2023: 2023 6th International Conference on Big Data Technologies
September 22 - 24, 2023
Qingdao, China
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 21Total Downloads
- Downloads (Last 12 months)21
- Downloads (Last 6 weeks)1
Reflects downloads up to 12 Aug 2024
Other Metrics
Citations
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format