Hierarchical Clustering

A type of Clustering where the number of clusters is not required. But it needs a termination condition (which could also be the number of clusters).

It creates a hierarchical decomposition of the data.

Distances between Clusters can be calculated in various ways:

  • Minimum distance
    • minimum distance between an object in one cluster and an object in the other
  • Maximum distance
    • maximum distance between an object in one cluster and an object in the other
  • Average distance
    • average distance between an object in one cluster and an object in the other
  • Mean distance
    • distance between the two centroids

Nearest Neighbors Algorithm uses minimum distance. Single-linkage MST

Methods