What are some of the pros and cons of hierarchical clustering compared to K-Means?

Pros:

• Do not have to specify the number of clusters before running the algorithm
• Results are reproducible and not subject to randomness introduced by choice of initial centroids as in K-Means

Cons:

• Requires computation of pairwise linkage matrix, which can be computationally expensive
• Results can differ based on the linkage criteria used
• Can be sensitive to noise in data