An investigation of wine quality testing using machine learning techniques

Sathishkumar Mani, Reshmy Avanavalappil Krishnankutty, Sabaria Swaminathan, P. Theerthagiri
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引用次数: 0

Abstract

Quality is the most determining factor for any product. Optimal care and best measures are to be taken in assessing the quality of any product. This work deals with determining the quality of wine using intelligence-based learning techniques. In order to estimate the quality of wine, several experiments are performed on wine datasets. The main purpose of our work is to study and discover an efficient machine learning (ML) model that could determine the quality of wine given some Physico-chemical features. This study establishes that selecting important features to evaluate rather than all of them can lead to improved forecasts. According to the results, this approach may provide people who are not wine experts a greater opportunity to choose a fine wine.

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基于机器学习技术的葡萄酒质量检测研究
质量是任何产品最重要的决定因素。在评估任何产品的质量时,都要采取最佳的护理和最佳的措施。这项工作涉及使用基于智能的学习技术来确定葡萄酒的质量。为了估计葡萄酒的质量,在葡萄酒数据集上进行了几个实验。我们工作的主要目的是研究和发现一种有效的机器学习(ML)模型,该模型可以在给定一些物理化学特征的情况下确定葡萄酒的质量。这项研究表明,选择重要特征进行评估,而不是全部进行评估,可以改善预测。根据研究结果,这种方法可能会为非葡萄酒专家提供更大的机会来选择优质葡萄酒。
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来源期刊
IAES International Journal of Artificial Intelligence
IAES International Journal of Artificial Intelligence Decision Sciences-Information Systems and Management
CiteScore
3.90
自引率
0.00%
发文量
170
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