A Very 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) A very efficient, single threaded, stochastic training algorithm based on ideas from tensor algebra. Up to 60x faster than traditional single-threaded training algorithms. No special accelerator hardware required.
(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.