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Erschienen in:
2018 | OriginalPaper | Buchkapitel
4. Visualization of Auto-CM Output
verfasst von : Paolo Massimo Buscema, Giulia Massini, Marco Breda, Weldon A. Lodwick, Francis Newman, Masoud Asadi-Zeydabadi
Erschienen in: Artificial Adaptive Systems Using Auto Contractive Maps
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Abstract
One of the most powerful aspects of our approach to neural networks is not only the development of the Auto-CM neural network but the visualization of its results. In this chapter we look at two visualization approaches—the Minimal Spanning Tree (MST) and the Maximal Regular Graph (MRG). The resultant from Auto-CM is a matrix of weights. This weight matrix naturally fits into a graph theoretic framework since the weights connecting the nodes will be viewed as edges and the weights as the weights on these edges.