Abstract
The utilization of Self-Organizing Maps (SOM) to reprieve various knowledge data and complex datasets. Self-Organizing Maps helps in data training, getting error metrics, and convergence properties exist in SOM. Visualizing a Self-Organizing Map on data set create a visual difference in retrieving information from data. Self-Organizing Maps are capable to deliver the information regarding locations of the high dimensional groups, it also can support to catch irregular forms, and provide the understanding about the outline of the dataset applied on.
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Bhatia, M., Saru, Manani, P., Vats, P., Kumar, P. (2022). Data Visualisation Using Self-organising Maps. In: Rathore, V.S., Sharma, S.C., Tavares, J.M.R., Moreira, C., Surendiran, B. (eds) Rising Threats in Expert Applications and Solutions. Lecture Notes in Networks and Systems, vol 434. Springer, Singapore. https://doi.org/10.1007/978-981-19-1122-4_40
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DOI: https://doi.org/10.1007/978-981-19-1122-4_40
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