Affiliation:
1. Kazunori Yamaguchi Laboratory, Department of General Systems Studies, Graduate School of Arts and Sciences, The University of Tokyo, Japan
Abstract
In this paper, we propose global mapping analysis (GMA) as a new method to solve multidimensional scaling (MDS). By GMA, MDS is done by an online learning rule based on stochastic approximation. GMA need not directly calculate the disparity matrix for carrying out MDS, as Oja's PCA network do not calculate the correlation matrix. So, GMA is expected to be useful for multivariate data analysis on a large scale. Actually, it was verified by numerical experiments based on artificial data that GMA can work well even if the number of the attribute N is quite large (N=10 000.)
Publisher
World Scientific Pub Co Pte Lt
Subject
Computer Networks and Communications,General Medicine
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献