Determine optimum number of compact overlapped clusters using FRLVQ technique.
In: Journal of Electronics, Jg. 22 (2005-11-01), Heft 6, S. 676-680
Online
academicJournal
Zugriff:
A method, named XHJ-method, is proposed in this letter to determine the number of clusters of a data set, which incorporates with the Fuzzy Reinforced Learning Vector Quantization (FRLVQ) technique. The simulation results show that this new method works well for the traditional iris data and an artificial data set, which contains un-equally sized and spaced clusters. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Electronics is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Titel: |
Determine optimum number of compact overlapped clusters using FRLVQ technique.
|
---|---|
Autor/in / Beteiligte Person: | Xu, Wenhuan ; Huang, Qiang ; Ji, Zhen ; Zhang, Jihong |
Link: | |
Zeitschrift: | Journal of Electronics, Jg. 22 (2005-11-01), Heft 6, S. 676-680 |
Veröffentlichung: | 2005 |
Medientyp: | academicJournal |
ISSN: | 0217-9822 (print) |
DOI: | 10.1007/BF02687850 |
Sonstiges: |
|