WINE CLASSIFICATION USING LDA

Abstract: Analysis of wine categories was the primary focus of this endeavour. Through empirical research, the wine dataset is reduced in dimension and grouped into clusters. It is necessary to do a factor analysis on the 13 variables in order to separate the complicated ones into 5 categories: the bitter tropic factor; the visual assessment; colour; pH; and mineral elements. Cluster analysis using K-means clustering was used to divide the data into three distinct groups. The features of each variety may be summarised according to the cluster centre. Using a series of empirical investigations, it is possible to draw a general picture of the wine's qualities and to group them into several groups.