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Use R-studio to solve this problem. Code + Output + Explanation included.

Use the "winequality-red" dataset. The dataset describes the quality of 1599 red wines with 12 different attributes. Remove the ‘quality’ variable from the dataset

c. Cluster the 1599 red wines in the given dataset into 2 groups using hierarchical clustering. Consider Euclidean distance as the dissimilarity measure and the closest distance between two clusters as the maximum distance between them.

d. Cluster the 1599 red wines in the given dataset into 2 groups using hierarchical clustering. Consider Euclidean distance as the dissimilarity measure and the closest distance between two clusters as the average distance between them.

e. Cluster the 1599 red wines in the given dataset into 2 groups using hierarchical clustering. Consider Euclidean distance as the dissimilarity measure and the closest distance between two clusters as the minimum distance between them.

f. Visually display the clusters obtained in part c, d and e using the first two principal components (PCs)