DocumentCode :
1943606
Title :
Connection between Self-Organizing Maps and Metric Multidimensional Scaling
Author :
Yin, Hujun
Author_Institution :
Univ. of Manchester, Manchester
fYear :
2007
fDate :
12-17 Aug. 2007
Firstpage :
1025
Lastpage :
1030
Abstract :
The self-organizing map (SOM) and some of its variants such as visualization induced SOM (ViSOM) have been seen to yield similar results to multidimensional scaling (MDS). However the exact connection has yet been established, though similar topographic mapping results have been shown in several studies. In this paper we provide a review on the SOM and its cost function and topological measures. Then we examine its relationship with MDS from their cost functions in the aspect of data visualization. The SOM is shown to produce a quantized, qualitative scaling and while the ViSOM a quantitative or metric scaling. The SOM can also be regarded as a generalized MDS to relate two metric spaces by forming a topological mapping between them. The connection between MDS and principal manifolds is also discussed.
Keywords :
pattern recognition; self-organising feature maps; metric multidimensional scaling; principal manifolds; self-organizing maps; topographic mapping; Brain modeling; Cerebral cortex; Cost function; Data visualization; Multidimensional systems; Nerve fibers; Neural networks; Pattern recognition; Self organizing feature maps; Surface topography;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location :
Orlando, FL
ISSN :
1098-7576
Print_ISBN :
978-1-4244-1379-9
Electronic_ISBN :
1098-7576
Type :
conf
DOI :
10.1109/IJCNN.2007.4371099
Filename :
4371099
Link To Document :
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