Generalized fuzzy c-means clustering in the presence of outlying data

Richard J. Hathaway; Dessa D. Overstreet; Yingkang Hu; John W. Davenport

doi:10.1117/12.342909

22 March 1999 Generalized fuzzy c-means clustering in the presence of outlying data

Richard J. Hathaway, Dessa D. Overstreet, Yingkang Hu, John W. Davenport

Proceedings Volume 3722, Applications and Science of Computational Intelligence II; (1999) https://doi.org/10.1117/12.342909
Event: AeroSense '99, 1999, Orlando, FL, United States

Abstract

Some data sets contain outlying data values which can degrade the quality of the clustering results obtained using standard techniques such as the fuzzy c-means algorithm. This note gives an extended family of fuzzy c-means type models, and attempts to empirically identify those members of the family which are least influenced by the presence of outliers. The form of the extended family of clustering criteria suggests an alternating optimization approach, is feasible, and specific algorithms for implementing the optimization of the models are stated. The implemented approach is then tested using various artificial data sets.

Citation Download Citation

Richard J. Hathaway, Dessa D. Overstreet, Yingkang Hu, and John W. Davenport "Generalized fuzzy c-means clustering in the presence of outlying data", Proc. SPIE 3722, Applications and Science of Computational Intelligence II, (22 March 1999); https://doi.org/10.1117/12.342909

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available