10. Fuzzy Clustering of Heterogeneous Patterns
Published Online: 27 JAN 2005
Copyright © 2005 John Wiley & Sons, Inc.
Knowledge-Based Clustering: From Data to Information Granules
How to Cite
Pedrycz, W. (2005) Fuzzy Clustering of Heterogeneous Patterns, in Knowledge-Based Clustering: From Data to Information Granules, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/0471708607.ch10
- Published Online: 27 JAN 2005
- Published Print: 7 JAN 2005
Print ISBN: 9780471469667
Online ISBN: 9780471708605
- heterogeneous data;
- parametric and nonparametric models of data;
- possibility-necessity transformation;
Discussed is clustering of heterogeneous data that are patterns whose features are information granules rather than numeric entities. Those are represented with the aid of fuzzy sets and fuzzy relations. The fundamental design phase concerns the representation of information granules for clustering and representation of results (e.g., prototypes) that leads to several mechanisms of encoding and decoding. Two fundamental approaches to clustering known as parametric and nonparametric techniques are analyzed.