Hierarchical Clustering

Learn about hierarchical clustering via the agglomerative approach.

Chapter Goals:

  • Learn about hierarchical clustering using the agglomerative approach

A. K-means vs. hierarchical clustering

A major assumption that the K-means clustering algorithm makes is that the dataset consists of spherical (i.e. circular) clusters. With this assumption, the K-means algorithm will create clusters of data observations that are circular around the centroids. However, real life data often does not ...