DocumentCode
1745032
Title
Properties of deletion methods in competitive learning
Author
Macda, M. ; Miyajima, Hiromi
Author_Institution
Kurume Nat. Coll. of Technol., Japan
Volume
3
fYear
2001
fDate
6-9 May 2001
Firstpage
707
Abstract
In this paper, we describe properties of deletion methods in competitive learning. From the viewpoint of the deleting mechanisms of reference vectors, we introduce approaches termed the adaptivity and sensitivity deletions participating in the criteria of partition error and distortion error, respectively. Experimental results show the effectiveness of the present approaches in the average distortion
Keywords
errors; unsupervised learning; vectors; adaptivity deletions; competitive learning; deletion methods; distortion error; partition error; reference vectors; sensitivity deletions; Petroleum;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2001. ISCAS 2001. The 2001 IEEE International Symposium on
Conference_Location
Sydney, NSW
Print_ISBN
0-7803-6685-9
Type
conf
DOI
10.1109/ISCAS.2001.921430
Filename
921430
Link To Document