摘要
葡萄酒质量的判别是需要聘请专业的葡萄酒专家来品鉴的,因此必然会消耗大量的人力、物力、财力。通过算法来分析葡萄酒的各个属性指标从而确定其质量是十分必要的。但在研究过程中,发现利用常见的多元统计分析算法判别葡萄酒质量时,无论是白葡萄酒还是红葡萄酒均出现了错误率过高的情况。因此,通过有序多分类逻辑回归算法、二次邻近算法、支持向量机算法对葡萄酒质量判别过程中的瓶颈进行了研究。
Wine quality discrimination is the need to hire professional wine experts to taste,so it will inevitably consume a lot of human,material and financial resources. It is necessary to analyze the various attribute indexes of wine by algorithm to determine its quality. However,in the course of the study,it is found that when the quality of wine is judged by the common multivariate statistical analysis algorithm,the error rate is too high in both white wine and red wine. Therefore,through the ordered multi-classification logic regression algorithm,two proximity algorithm,support vector machine algorithm to study the bottleneck in the process of wine quality discrimination.
引文
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