For questions related to different types of Self Organising Maps.
A self-organising map (SOM) or self-organising 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, and is therefore a method to do dimensionality reduction. Self-organising maps differ from other artificial neural networks as they apply competitive learning as opposed to error-correction learning (such as back-propagation with gradient descent), and in the sense that they use a neighbourhood function to preserve the topological properties of the input space.
