Skip to content

Clustering with k-means, k-medoids & agglomerative clustering

License

Notifications You must be signed in to change notification settings

igarnier/prbnmcn-clustering

Repository files navigation

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

About

Clustering with k-means, k-medoids & agglomerative clustering

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages