Self-Organizing Maps in the Design and Processing of Granular Information
a high level of interaction with user — it is worth stressing that the constructs (information granules) are delineated by a human on a basis of visualization of highly dimensional data,
a solid support of the development of information granules cast in the framework of sets and fuzzy sets.
KeywordsDepression Barium Fenton
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- Bargiela, A., Pedrycz, W. (2001), Classification and clustering of granular data using SOM, IFSA-NAFIPS 2001, Vancouver (BC), July 2001, 1696–1701.Google Scholar
- Bortolan, G., Willems, J.L. (1994), Diagnostic ECG classification based on neural networks, Journal of Electrocardiology, 26, 75–79.Google Scholar
- Chidamber, S.R., CF. Kemerer (1994) A Metrics suite for object-oriented design, IEEE Transactions on Software Engineering, 20(6).Google Scholar
- Fenton, N.E., S.L. Pfleeger (1997), Software Metrics: A Rigorous and Practical Approach, PWS, London.Google Scholar
- Kohonen, T.(1982), Self-organized formation of topologically correct feature maps, Biological Cybernetics, 43.Google Scholar
- Kohonen, T., S. Kaski, K. Lagus, T. Honkela (1996), Very large two-level SOM for the browsing of newsgroups, In: Proc of the Int Conf on Artificial Neural Networks, Bochum, Germany.Google Scholar
- Li, W., S. Henry (1993) Object oriented metrics that predict maintainability, Journal of Systems and Software, 23(2) Google Scholar
- Weyuker, E.J. (1988) Evaluating software complexity measures, IEEE Transactions on Software Engineering, 14(9).Google Scholar
- Zuse, H. (1985) A Framework of Software Measurement, de Gruyter, Berlin.Google Scholar