An Efficient Implementation of Kohonen's Self-Organizing Maps (SOMs) with Starburst Visualizations

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 ).