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Neural Network World
The Self-Organizing Map model considers the possibility of 1D and 3D map topologies. However, 2D maps are by far the most used in practice. Moreover, there is a lack of a theory which studies the relative merits of 1D, 2D and 3D maps. In this paper a theory of this kind is developed, which can be used to assess which topologies are better suited for vector quantization. In addition to this, a broad set of experiments is presented which includes unsupervised clustering with machine learningdoi:10.14311/nnw.2018.28.004 fatcat:zzghhp3sfza7jbcdz32v5wu67u