A<unk>  <unk>  is a type of artificial neural network that is trained using unsupervised learning to produce low-dimensional representation of the training samples while preserving the topological properties of the input space.
This makes<unk>  useful for visualizing low-dimensional views of high-dimensional data, akin to multidimensional scaling. The model was first described as an artificial neural network by the Finnish professor Teuvo Kohonen, and is<unk> etimes called a Kohonen<unk> .
Like most artificial neural networks,<unk> s operate in two modes: training and<unk> ping.  Training builds the<unk>  using input examples. It is a competitive process, also called vector quantization. <unk> ping automatically classifies a new input vector.
Self-organizing map
Triage
Quantization 
Classification template
Kick chart
Overview template
World Community Grid
Cartesian coordinate system