Grouping data using agglomerative clustering

Before we talk about agglomerative clustering, we need to understand hierarchical clustering. Hierarchical clustering refers to a set of clustering algorithms that build tree-like clusters by successively splitting or merging them. This hierarchical structure is represented using a tree.

Hierarchical clustering algorithms can be either bottom-up or top-down. Now what does this mean? In bottom-up algorithms, each datapoint is treated as a separate cluster with a single object. These clusters are then successively merged until all the clusters are merged into a single giant cluster. This is called agglomerative clustering. On the other hand, top-down algorithms start with a giant cluster and successively ...

Get Python Machine Learning Cookbook now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.