What are some pros and cons of K-Means Clustering?

Pros:

• Easy to implement
• Produces compact-shaped clusters

Cons:

• Must specify number of clusters in advance
• Sensitive to initial choices of centroids
• Not good at identifying clusters that don’t follow a globular shape