An Extended TopoART Network for the Stable On-line Learning of Regression Functions

  • Marko Tscherepanow
Conference paper

DOI: 10.1007/978-3-642-24958-7_65

Volume 7063 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Tscherepanow M. (2011) An Extended TopoART Network for the Stable On-line Learning of Regression Functions. In: Lu BL., Zhang L., Kwok J. (eds) Neural Information Processing. ICONIP 2011. Lecture Notes in Computer Science, vol 7063. Springer, Berlin, Heidelberg

Abstract

In this paper, a novel on-line regression method is presented. Due to its origins in Adaptive Resonance Theory neural networks, this method is particularly well-suited to problems requiring stable incremental learning. Its performance on five publicly available datasets is shown to be at least comparable to two established off-line methods. Furthermore, it exhibits considerable improvements in comparison to its closest supervised relative Fuzzy ARTMAP.

Keywords

Regression On-line learning TopoART Adaptive Resonance Theory 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Marko Tscherepanow
    • 1
  1. 1.Applied InformaticsBielefeld UniversityBielefeldGermany