Robust nonlinear dimension reduction: a self-organizing approach

Authors:
Yuexian Hou;Liyue Yao;Pilian He
Affiliations:
School of Electronic Information Engineering, Tianjin University;School of Electronic Information Engineering, Tianjin University;School of Electronic Information Engineering, Tianjin University
Venue:
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
Year:
2005

Citing 2
Cited 2

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Abstract

Most NDR algorithms need to solve large-scale eigenvalue problems or some variation of eigenvalue problems, which is of quadratic complexity of time and might be unpractical in case of large-size data sets. Besides, current algorithms are global, which are often sensitive to noise and disturbed by ill-conditioned matrix. In this paper, we propose a novel self-organizing NDR algorithm: SIE. The time complexity of SIE is O(NlogN). The main computing procedure of SIE is local, which improves the robustness of the algorithm remarkably.