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When used for visualization of high-dimensional data, the self-organizing map (SOM) requires a coloring scheme such as the U-matrix to mark the distances between neurons. Even so, the structures of the data clusters may not be apparent and their shapes are often distorted. In this paper, a visualization-induced SOM (ViSOM) is proposed to overcome these shortcomings. The algorithm constrains and regularizes the inter-neuron distance with a parameter that controls the resolution of the map. Thedoi:10.1109/72.977314 pmid:18244423 fatcat:zwv7li2ej5cgvmjqqenn5w3hma