An Analysis Research of White Wine Quality Using Three Machine Learning Models

Haoxuan Liu

2023

Abstract

In today’s society, wine has become an indispensable drink on people’s tables due to abundant material wealth. Understanding wine quality is crucial in this context. In this work, three popular machine learning models—Support Vector Machine (SVM), Naive Bayes, and Random Forest—are compared through analysis of the white wine dataset. The evaluation metrics employed to assess their performance include precision, recall, and F1 score, providing a comprehensive evaluation of their quality analysis capabilities on white wine data. Results indicate that Random Forest and SVM performed well, achieving satisfactory accuracy and other white wine quality analysis metrics. However, the Naive Bayes model proved unsuitable and could have performed better, underscoring the significance of model selection in machine learning for different datasets and problem domains. This study offers valuable insights into wine quality analysis, emphasizing performance variations among machine learning models. The aforementioned conclusions include noteworthy practical consequences for both the wine business and its clients.

Paper Citation

in Harvard Style

Liu H. (2023). An Analysis Research of White Wine Quality Using Three Machine Learning Models. In Proceedings of the 1st International Conference on Data Analysis and Machine Learning - Volume 1: DAML; ISBN 978-989-758-705-4, SciTePress, pages 486-491. DOI: 10.5220/0012800600003885

in Bibtex Style

@conference{daml23,
author={Haoxuan Liu},
title={An Analysis Research of White Wine Quality Using Three Machine Learning Models},
booktitle={Proceedings of the 1st International Conference on Data Analysis and Machine Learning - Volume 1: DAML},
year={2023},
pages={486-491},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012800600003885},
isbn={978-989-758-705-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Data Analysis and Machine Learning - Volume 1: DAML
TI - An Analysis Research of White Wine Quality Using Three Machine Learning Models
SN - 978-989-758-705-4
AU - Liu H.
PY - 2023
SP - 486
EP - 491
DO - 10.5220/0012800600003885
PB - SciTePress