ESOM-Maps: tools for clustering, visualization, and classification with Emergent SOM
نویسندگان
چکیده
An overview on the usage of emergent self organizing maps is given. U-Maps visualize the distance structures of high dimensional data sets. P-Maps show their density structures and U*-Maps combine the advantages of the mentioned maps to a visualization suitable to detect nontrivial cluster structures. A concise summary on the usage of Emergent Self-organizing Maps (ESOM) for data mining is given. The tasks of visualization, clustering, and classification as they can be performed with the Databionics ESOM Tools are described.
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