基于机器学习的红酒质量分类研究

Research on Wine Quality Classification based on Machine Learning

随着现代社会的飞速发展,红酒越来越大众化,然而人们对其品质分类还有些困惑。通过使用Jupyter Lab编写Python程序建立各种机器学习算法对红酒质量进行分类,并进行精度比较。结果表明K近邻模型更适合红酒质量分类。研究结果可为红酒品质的相关研究提供启示,也为人们辨认红酒品质提供参考。

With the rapid development of modern society,red wine is becoming more and more popular.However,people are still confused about its quality classification.Therefore,Jupyter Lab is used to compile Python programs to establish various machine learning algorithms to classify the quality of red wine,and compares the accuracy.The results show that K-nearest neighbor model is more suitable for the quality classification of red wine.The results can be which can provide enlightenment for the related research on the quality of red wine later,and it also can provide reference for people to identify the quality of red wine.