Contents
This chapter continues to describe various generalizations and variations of fuzzy c-means clustering. The methods studied here are more specific or include more recent techniques. In a sense some of them are more difficult to understand than those in the previous section. It does not imply, however, that methods described in this chapter are less useful.
Keywords
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.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Miyamoto, S., Ichihashi, H., Honda, K. (2008). Variations and Generalizations - II. In: Algorithms for Fuzzy Clustering. Studies in Fuzziness and Soft Computing, vol 229. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78737-2_4
Download citation
DOI: https://doi.org/10.1007/978-3-540-78737-2_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78736-5
Online ISBN: 978-3-540-78737-2
eBook Packages: EngineeringEngineering (R0)