K-Means and Hierarchical Clustering

Free SOA Exam SRM (Statistics for Risk Modeling) lesson in Unsupervised Learning Techniques. 23 min read, ~3,504 words.

K-means partitions n observations into a pre-specified K clusters by minimizing within-cluster sum of squares (WCSS). You must choose K before running it. Agglomerative hierarchical clustering starts with n singletons and merges the two closest clusters at each step, producing a dendrogram. No K is required up front. Linkage method...