Online data visualization using the neural gas network

被引：28
|
作者：
Estevez, Pablo A. [1 ]
Figueroa, Cristian J. [1 ]
机构：
[1] Univ Chile, Dept Elect Engn, Santiago, Chile
来源：
NEURAL NETWORKS | 2006年 / 19卷 / 6-7期
关键词：
neural gas; data projection; data visualization; topology preservation; distance preservation;
D O I：
10.1016/j.neunet.2006.05.024
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A high-quality distance preserving output representation is provided to the neural gas (NG) network. The nonlinear mapping is determined concurrently along with the codebook vectors. The adaptation rule for codebook positions in the projection space minimizes a cost function that favors the trustworthy preservation of the local topology. The proposed visualization method, called OVI-NG, is an enhancement over curvilinear component analysis (CCA). The results show that the mapping quality obtained with OVI-NG outperforms the original CCA, in terms of the trustworthiness, continuity, topographic function and topology preservation measures. (c) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码：923 / 934
页数：12
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