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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Mantegna, R.N. 1999. Hierarchical structure in Financial Market. European Physical Journal B: Condensed Matter and Complex Systems 11: 193–197.
Buscema, M (ed.). 2007. Squashing Theory and Contractive Map Network, Semeion Technical Paper #32, Rome, 2007.
Buscema, M. 2007. A Novel Adapting Mapping Method for Emergent Properties Discovery in Data Bases: Experience in Medical Field. In 2007 IEEE International Conference on Systems, Man and Cybernetics (SMC 2007). Montreal, Canada, October 7–10, 2007.
Buscema, M., M. Asadi-Zeydabadi, W. Lodwick, and M. Breda. 2016. The H0 Function, A New Index for Detecting Structural/Topological Complexity Information in Undirected Graphs. Physica A 447: 355–378.
McClellan, J.L., and D.E. Rmelhart. 1986. Explorations in Parallel Distributed Processing. Cambridge, MA: MIT Press.
Buscema, M., V. Consonni, D. Ballobio, A. Mauri, G. Massini, M. Breda, and R. Todeschini. 2014. K-CM: A New Artificial Neural Network. Applications to Supervised Patter Recogniction. Chemometrics and Intetelligent Systems 138: 110–119.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this chapter
Cite this chapter
Buscema, P.M., Massini, G., Breda, M., Lodwick, W.A., Newman, F., Asadi-Zeydabadi, M. (2018). Visualization of Auto-CM Output. In: Artificial Adaptive Systems Using Auto Contractive Maps. Studies in Systems, Decision and Control, vol 131. Springer, Cham. https://doi.org/10.1007/978-3-319-75049-1_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-75049-1_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-75048-4
Online ISBN: 978-3-319-75049-1
eBook Packages: EngineeringEngineering (R0)