The Pros and Cons of K-Means Clustering

K-means clustering is a useful but non-probabilistic algorithm for finding clusters. However, it requires careful selection of K and lacks probabilistic predictions. Despite its limitations, approximate solutions can be easily obtained. Exploring probabilistic methods can provide deeper insight and more accurate results.