Title :
LVQ clustering and SOM using a kernel function
Author :
Inokuchi, Ryo ; Miyamoto, Sadaaki
Author_Institution :
Graduate Sch. of Syst. & Information Eng., Tsukuba Univ., Ibaraki, Japan
Abstract :
This paper aims at discussing clustering algorithm based on learning vector quantization (LVQ) using a kernel function in support vector machines. Furthermore, self-organizing map (SOM) using a kernel function is considered. Examples of clustering using different techniques are shown and effects of the kernel function are discussed.
Keywords :
learning (artificial intelligence); pattern clustering; self-organising feature maps; support vector machines; vector quantisation; clustering algorithm; kernel function; learning vector quantization; self-organizing map; support vector machines; Clustering algorithms; Data analysis; Data visualization; Kernel; Machine learning; Organizing; Support vector machine classification; Support vector machines; Systems engineering and theory; Vector quantization;
Conference_Titel :
Fuzzy Systems, 2004. Proceedings. 2004 IEEE International Conference on
Print_ISBN :
0-7803-8353-2
DOI :
10.1109/FUZZY.2004.1375395
