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Self-Organizing Maps in the Design and Processing of Granular Information

  • Andrzej Bargiela
  • Witold Pedrycz
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 717)

Abstract

In this chapter, we concentrate on a granular data analysis, especially studying ways of information granulation. We show how information granules are constructed by a designer/user via a visual inspection of self-organizing maps (SOMs). SOMs are commonly used neural network architectures realizing a paradigm of unsupervised learning. The crux of the approach proposed here lies in the following
  • 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.

Keywords

Homogeneous Region Neighbor Function Information Granule Right Ventricular Hypertrophy Original Feature Space 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2003

Authors and Affiliations

  • Andrzej Bargiela
    • 1
  • Witold Pedrycz
    • 2
  1. 1.The Nottingham Trent UniversityNottinghamUK
  2. 2.University of AlbertaEdmontonCanada

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