Intermediate · Data
Hierarchical clustering
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. An algorithm that creates a tree-like structure of nested clusters.
Technical Definition
An algorithm that creates a tree-like structure of nested clusters.
How it works
Hierarchical clustering is a method that builds a hierarchy of clusters, represented as a tree (dendrogram). It can work by agglomerative (bottom-up) or divisive (top-down) approaches. Agglomerative starts with each data point as its own cluster and merges them, while divisive starts with one large cluster and splits it. This is useful for data with natural hierarchical structures.
Related Concepts
- Clustering — An unsupervised technique that groups similar data points without using labels.
- Unsupervised Learning — Learning patterns from data that has no labels — only the inputs.