Problems for Part II
(a)Use hierarchical agglomerative clustering with the Euclidean distance, and determine the membership of the two clusters just before the final merge.
(b)Repeat part (a) with the cosine distance. Are the results the same?
(c)Use a different linkage, and repeat parts (a) and (b).
(d)Find optimal 2-cluster arrangements based on the k-means approach using both the Euclidean and the cosine distances.
(e)Compare the results in parts (a)–(d) and comment on your findings.
2.Hierarchical agglomerative clustering assigns observations to clusters based on the nearest distance at every step in the algorithm and results in a tree with a final single ...