Cluster analysis

Summary

Cluster analysis groups a set of objects into clusters. Objects in the same cluster should be more similar to each other than to objects in other clusters. Unlike classification, it uses no labels known in advance. Main families of methods are centroid methods such as k-means clustering, hierarchical clustering, density-based methods and model-based clustering. There is no single best notion of a cluster, and different methods can give different answers.