Free Projection SOM: A New Method For SOM-Based Cluster Visualization
نویسندگان
چکیده
In this paper an extension to the learning rule of the Self-Organizing Map (SOM) namely the Free Projection SOM (FP-SOM) is presented in order to enhance the SOM projection. The general idea of the FPSOM is to mirror the movement of weight vectors during the training process allowing their images on the map grid to move more freely between the junctions. The result of the extended training algorithm allows intuitive analysis of the similarities inherent in the input data and most important, intuitive recognition of cluster boundaries. Experiments on artificial and real data sets show the advantages of the proposed extension as a cluster visualization method. Key-Words: Data Mining, Cluster Visualization, Self-organizing Maps, High-dimensional Data Projection.
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