This paper gives a brief description of several well known fuzzy objective function clustering algorithms, and discusses the convergence properties of this type of algorithm. The Shape Seeker algorithm, an adaptive norm algorithm, is then described in detail, and convergence established. It is compared to the other algorithms by examining the clusterings it produces on several data sets.
| Identifer | oai:union.ndltd.org:UTAHS/oai:digitalcommons.usu.edu:etd-8058 |
| Date | 01 May 1982 |
| Creators | Haws, LaDawn |
| Publisher | DigitalCommons@USU |
| Source Sets | Utah State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | All Graduate Theses and Dissertations |
| Rights | Copyright for this work is held by the author. Transmission or reproduction of materials protected by copyright beyond that allowed by fair use requires the written permission of the copyright owners. Works not in the public domain cannot be commercially exploited without permission of the copyright owner. Responsibility for any use rests exclusively with the user. For more information contact digitalcommons@usu.edu. |
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