prbnmcn-clustering

Clustering library
README

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

Install
Published
27 Apr 2021
Sources
0.0.1.tar.gz
md5=a32385f08db7e94de4f167cf87b03df0
sha512=e0c9c281ccdcd5a10ed3ff6e74362aab10c44767fa6edc20f4f55e67843a5eb2efcbff5cb23052bfc3df752876151585ee4c76090f7b1fae77990f4acee81b69
Dependencies
odoc
with-doc
ocaml
>= "4.08.0"
dune
>= "2.8"
Reverse Dependencies