15. Linguistic Modeling

  1. Witold Pedrycz1,2

Published Online: 27 JAN 2005

DOI: 10.1002/0471708607.ch15

Knowledge-Based Clustering: From Data to Information Granules

Knowledge-Based Clustering: From Data to Information Granules

How to Cite

Pedrycz, W. (2005) Linguistic Modeling, in Knowledge-Based Clustering: From Data to Information Granules, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/0471708607.ch15

Author Information

  1. 1

    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada

  2. 2

    Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

Publication History

  1. Published Online: 27 JAN 2005
  2. Published Print: 7 JAN 2005

ISBN Information

Print ISBN: 9780471469667

Online ISBN: 9780471708605

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Keywords:

  • conditional clustering;
  • linguistic model;
  • granular neurons;
  • blueprint of linguistic model;
  • linguistic output of model

Summary

The chapter shows how to construct linguistic models, viz. fuzzy models whose outputs come in the form of fuzzy sets (numbers) rather than single numeric entities. It is shown how conditional clustering forms a linguistic blueprint of the model and how it could be optimized. Further refinement of the model involving contexts as well as clusters in the input space is presented.