prbnmcn-clustering

This library implements the following clustering algorithms:

• K-means
• K-medoids (using either 'Partition Around Medoids' or the 'Voronoi Iteration' algorithms)
• Agglomerative clustering (yielding dendrograms)

A basic example can be found in the test subdirectory.

Multi-start routines are also available to pick the best out of n initial clusterings. At the time of writing, the implementation is entirely sequential.

TODOs

• many low-hanging fruits for optimization
• implement parallel multi-start routine when multicore lands