Enhancing SOM-based data visualization by linking different data projections

The self-organizing map (SOM) is widely used as a data visualization method especially in various engineering applications. It performs a non-linear mapping from a high-dimensional data space to a lower dimensional visualization space. The SOM can be used for example in correlation detection and cluster visualization in explorative manner. In this paper two tools for reeng the SOM-based visualization are presented. The rst one brings out a sharper view to the correlation detection and the second one brings additional information to the input space distance visualiza-tion. Both tools are based on linking two diierent data projections using color coding. The tools are demonstrated using a real world data example from a queuing system.

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