Study on the Influence of Physicochemical Indexes on Wine Quality
DOI:
https://doi.org/10.54691/bcpbm.v15i.290Keywords:
Principal Component Analysis; AGNES Hierarchical Clustering; Decision Tree Regression.Abstract
The quality of a wine is generally determined by hiring a group of qualified wine judges to taste the wine. The quality of wine grapes is directly related to the quality of wine. To explore how the physical and chemical indicators of wine and wine grapes can reflect the quality of wine and grape to a certain extent. This article is based on 2012 Chinese college students' mathematical contest in modeling A problem of data, to score as the dependent variable, wine physical and chemical indicators as independent variables, the method of using principal component analysis of physical and chemical indexes of wine grape dimension reduction, physical and chemical indexes selection of grapes, and use the decision tree regression method to establish score and wine function relation between the physical and chemical indicators. Then, after the comparison of the results of the four clustering algorithms, the hierarchical clustering method based on Agnes algorithm was used to conduct cluster analysis on the wines. Considering the rationality of classification, red and white wines were divided into four grades, and the average value of the estimated scores of each grade was used as the benchmark score for the wines of this grade.
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