A Novel Measure for Quantifying the Topology Preservation of Self-Organizing Feature Maps

作者:Mu-Chun Su, Hsiao-Te Chang, Chien-Hsing Chou

摘要

Recently, feature maps have been applied to various problem domains. The success of some of these applications critically depends on whether feature maps are topologically ordered. In this paper, we propose a novel measure for quantifying the neighborhood preserving property of feature maps. Two data sets were tested to illustrate the performance of the proposed method.

论文关键词:neural networks, feature maps, SOM algorithm, topological property

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论文官网地址:https://doi.org/10.1023/A:1015240802059