Exploration of Statistical and Textual Information by Means of Self-Organizing Maps
نویسنده
چکیده
The self-organizing map (SOM) converts statistical relationships between highdimensional data into geometric relationships on a low-dimensional grid. It can thus be regarded as a projection and a similarity graph of the primary data. As it preserves the most important topological relationships of the data elements on the display, it may be thought of as producing some form of abstraction. These two aspects, visualization and abstraction, can be utilized in data mining, process analysis, machine perception, and organization of document collections.
منابع مشابه
Information Visualization with Self-Organizing Maps
The Self-Organizing Map (SOM) is an unsupervised neural network algorithm that projects highdimensional data onto a two-dimensional map. The projection preserves the topology of the data so that similar data items will be mapped to nearby locations on the map. Despite the popular use of the algorithm for clustering and information visualisation, a system has been lacking that combines the fast ...
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