Title :
Batch implementation of Growing Self-Organizing Map
Author :
Yu, Yaohua ; Alahakoon, Damminda
Author_Institution :
Clayton Sch. of Inf. Technol., Monash Univ., Clayton, VIC
fDate :
Nov. 28 2006-Dec. 1 2006
Abstract :
The growing self-organizing map algorithm (GSOM) has been developed based on SOM. With its dynamic structure, GSOM can generate feature maps without pre-determining their size. It has shown many significant advantages when processing very large data sets. These advantages could be further enhanced if the processing speed of the algorithm could be increased. This paper presents a modified version of GSOM, which implements the batch processing principle to shorten the processing time. The algorithm and experimental results showing the improved performance are presented in this paper.
Keywords :
batch processing (computers); self-organising feature maps; batch implementation; dynamic structure; growing self-organizing map; Automatic generation control; Clustering algorithms; Computational intelligence; Computational modeling; Educational institutions; Information technology; Probability density function; Size control; Space technology; Vector quantization;
Conference_Titel :
Computational Intelligence for Modelling, Control and Automation, 2006 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7695-2731-0
DOI :
10.1109/CIMCA.2006.58