An Efficient Implementation of Kohonen's Self-Organizing Maps
(SOMs) with Starburst Visualizations
Description
Kohonen's self-organizing maps with a number of distinguishing features:
(1) An efficient, single threaded, stochastic training algorithm inspired by ideas from tensor algebra. Provides significant speedups over traditional single-threaded training algorithms. No special accelerator hardware required (see ).
(2) Automatic centroid detection and visualization using starbursts.
(3) Two models of the data: (a) a self organizing map model, (b) a centroid based clustering model.
(4) A number of easily accessible quality metrics for the self organizing map and the centroid based cluster model (see ).