DocumentCode
3428573
Title
A novel kernel prototype-based learning algorithm
Author
Qin, A.K. ; Suganthan, P.N.
Author_Institution
Sch. of Electr. & El;ectron, Eng., Nanyang Technol. Univ., Singapore
Volume
4
fYear
2004
fDate
23-26 Aug. 2004
Firstpage
621
Abstract
We propose a novel kernel prototype-based learning algorithm, called kernel generalized learning vector quantization (KGLYQ) algorithm, which can significantly improve the classification performance of the original generalized learning vector quantization algorithm in complex pattern classification tasks. In addition, the KGLVQ can also serve as a good general kernel learning framework for further investigation.
Keywords
generalisation (artificial intelligence); learning (artificial intelligence); pattern classification; support vector machines; vector quantisation; complex pattern classification tasks; general kernel learning framework; kernel generalized learning vector quantization algorithm; kernel prototype-based learning algorithm; Convergence; Cost function; Data structures; Decision theory; Kernel; Learning systems; Loss measurement; Pattern classification; Prototypes; Vector quantization;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
ISSN
1051-4651
Print_ISBN
0-7695-2128-2
Type
conf
DOI
10.1109/ICPR.2004.1333849
Filename
1333849
Link To Document