An implementation of a Self Organizing Map, also known as a Kohonen map.
A self-organizing map (SOM) or self-organizing feature map (SOFM) is a type
of artificial neural network (ANN) that is trained using unsupervised learning
to produce a low-dimensional (typically two-dimensional), discretized
representation of the input space of the training samples, called a map.
See article for more information.
- Conforms to the "Microsoft All Rules" static code analysis ruleset.
- Conforms to the StyleCop 4.7 ruleset.
The sample follows the "hello world" of self-organizing maps by producing a color pallet where the colors are randomized and then organized via a self-organizing map.
An example of the output looks like this 