A healing mechanism to improve the topological preserving property of feature maps

Mu Chun Su, Chien Hsing Chou, Hsiao Te Chang

Research output: Contribution to journalArticlepeer-review

Abstract

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. Several different approaches have been proposed to improve the conventional self-organizing feature map (SOM) algorithm. However, these approaches do not guarantee that a topologically-ordered feature map can be formed at the end of a simulation. Therefore, the trial-and-error procedure still dominates the procedure of forming feature maps. In this paper, we propose a healing mechanism to repair feature maps that are not well topologically ordered. The healed map is then further finetuned by the conventional SOM algorithm with a small learning rate and a small-sized neighborhood set so as to improve the accuracy of the map. Two data sets were tested to illustrate the performance of the proposed method.

Original languageEnglish
Pages (from-to)735-743
Number of pages9
JournalIEICE Transactions on Information and Systems
VolumeE85-D
Issue number4
StatePublished - Apr 2002

Keywords

  • Feature maps
  • SOM algorithm
  • Topological property

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