Identification of red wine categories based on physicochemical properties
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Xueting Bai, Lingbo Wang, Hanning Li
This paper mainly carried out the analysis of red wine categories. The red wine dataset is subjected to dimension reduction and clustering of samples through empirical analysis. First, factor analysis is performed on the 13 variables, and the complex variables are classified into five types of factors, namely the bitter trophic factor, the visual evaluation factor, the hue factor, the pH factor and the mineral element factor. Second, the samples were clustered by K-mean cluster analysis, and the samples were clustered into three different varieties. According to the cluster center, the characteristics of each variety can be summarized. Through a series of empirical analyses, a rough portrait of the red wine characteristics can be made and categories can be clustered in this data set.
Portrait of wine, Factor analysis, Cluster analysis, SPSS