ESOM: An Algorithm to Evolve Self-Organizing Maps from On-Line Data Streams
نویسندگان
چکیده
An algorithm of evolving self-organizing map (ESOM) is proposed as a dynamic version of the Kohonen self-organizing map, where network structure is evolved in an on-line adaptive mode. Experiments have been carried out on some benchmark data sets as well as on macroeconomic data. Results show that ESOM is a good tool for clustering, data analysis, and visualisation.
منابع مشابه
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