What are the main types of clustering algorithms?

Updated May 15, 2026

Short answer

The main types are partitioning, hierarchical, density-based, and model-based clustering.

Deep explanation

Partitioning methods like K-Means split data into fixed clusters. Hierarchical clustering builds tree-like structures. Density-based methods like DBSCAN find clusters based on density. Model-based approaches assume probabilistic models like Gaussian mixtures.

Real-world example

Detecting fraud groups in banking transactions.

Common mistakes

Using KMeans for non-spherical clusters.

Follow-up questions

When should you use DBSCAN?

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