A good small example case can make for good documentation, also. Thanks,
-- Raul On Tue, Feb 16, 2021 at 8:18 AM Emir U <e...@usgroupltd.uk> wrote: > > It's the Voronoi algo more or less verbatim which I initially read as an > alternative implementation of PAM as opposed to an alternative to PAM. I'll > add the following bits to it and then put it up on Github if it piques an > interest: > > 1. I'll treat the distance calculation as an adverb to avoid having to > instantiate the whole distance matrix (which is never used in its entirety). > This will give it better space complexity. I'll try to make it so that it > could be run on say 1M data points. > 2. I'll add kmeans++ initialisation which should perform much better than > random. > 3. I'll use a Gaussian mixture model with spherical variance parameterised > by the medoids and sample variance in-cluster as a working model to assign > likelihood to fitted data. > 4. I'll add repeated initialisations. I.e. repeat clustering N times and > keep the initialisation with the best likelihood. > 5. I'll add a k discovery routine which uses AIC and the GMM likelihood to > find k. > 6. I'll include benchmarks against kmeans, kmedoids, affinity prop and a > couple other sklearn implementation against a couple datasets. > > ---------------------------------------------------------------------- > For information about J forums see http://www.jsoftware.com/forums.htm ---------------------------------------------------------------------- For information about J forums see http://www.jsoftware.com/forums.htm
