Off-line structural risk minimization and BARTMAP-S

Stephen J. Verzi, Gregory L. Heileman, Michael Georgiopoulos, Georgios Anagnostopoulos

Research output: Contribution to conferencePaperpeer-review

5 Scopus citations


BARTMAP-S introduced a neural network architecture with which structural risk minimization can be performed, although indirectly. BARTMAP-S as previously described is trained in an on-line fashion, consistent with the original way intended for the Fuzzy ARTMAP neural network architecture. Here we will propose an extension to BARTMAP-S for conducting off-line learning. Consequently, this alternate mode of learning will allow us to conduct structural risk minimization more directly. In this paper, we will describe the new architecture and present some empirical results to demonstrate the usefulness of structural risk minimization in learning with an ARTMAP-based neural network.

Original languageEnglish (US)
Number of pages6
StatePublished - 2002
Externally publishedYes
Event2002 International Joint Conference on Neural Networks (IJCNN'02) - Honolulu, HI, United States
Duration: May 12 2002May 17 2002


Conference2002 International Joint Conference on Neural Networks (IJCNN'02)
Country/TerritoryUnited States
CityHonolulu, HI


  • Adaptive resonance theory
  • Classification
  • Empirical risk minimization
  • Generalization performance
  • Machine learning
  • Neural networks
  • Overlapping pattern classes
  • Structural risk minimization

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence


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