Wine Quality and Taste Classification Using Machine Learning Model

Anurag Sinha, Atul Kumar
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引用次数: 5

Abstract

In recent years the product quality has been one of the crucial parts for every single industry. The conventional methods for assessing the product quality are very time consuming and also not having the optimal result however with the resultant in dynamic Technology movement. We have the concepts of machine learning and data science through this technique it’s become more efficient to assess or to predict any kind of thing efficiently. In this paper, we have explored several machine learning techniques for evaluating wine quality based on different metrics and properties related to wine quality. In this paper, we have also used several machine learning algorithms to rank the quality of wines and investigate why people make the wine taste more interesting. We have selected the features using the most popular machine learning techniques. We used different types of datasets for this particular study. Keywords— Data science, machine learning, wine dataset, Logistic Regression, Stochastic gradient descent, Support Vector Classifier, Random Forest
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基于机器学习模型的葡萄酒质量和味道分类
近年来,产品质量已成为每一个行业的关键部分之一。传统的产品质量评估方法耗时长,而且由于技术的动态变化,结果也不理想。我们有了机器学习和数据科学的概念,通过这种技术,它变得更有效地评估或预测任何类型的事情。在本文中,我们探索了几种基于与葡萄酒质量相关的不同指标和属性来评估葡萄酒质量的机器学习技术。在本文中,我们还使用了几种机器学习算法来对葡萄酒的质量进行排名,并调查为什么人们会让葡萄酒的味道更有趣。我们选择了使用最流行的机器学习技术的特征。我们在这项研究中使用了不同类型的数据集。关键词:数据科学,机器学习,葡萄酒数据集,逻辑回归,随机梯度下降,支持向量分类器,随机森林
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