som

=**Self-Organizing Map**=

__**Description**__ The SOM is an algorithm used to visualize and interpret large high-dimensional data sets. Typical applications are visualization of process states or financial results by representing the central dependencies within the data on the map. The map consists of a regular grid of processing units, "neurons". A model of some multidimensional observation, eventually a vector consisting of features, is associated with each unit. The map attempts to represent all the available observations with optimal accuracy using a restricted set of models. At the same time the models become ordered on the grid so that similar models are close to each other and dissimilar models far from each other.

__**Insights**__ • Presenting high-dimensional data sets in an easy to understand visual form. • Juxtaposing data nods side by side, which makes the task of compare/contrast much easier. • Ancestry feature traces data family trees effortlessly.

__**Best practice**__ [|Thinkmap Visual Thesaurus] is an interactive dictionary and thesaurus which creates word maps that blossom with meanings and branch to related words. Its innovative display encourages exploration and learning. You'll understand language in a powerful new way.



Reference: [|Neural Networks Research Centre], Helsinki University of Technology